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==== Front BMC Palliat CareBMC Palliative Care1472-684XBioMed Central London 1472-684X-3-31527474410.1186/1472-684X-3-3Research ArticleBereavement care interventions: a systematic review Forte Amanda L 1forte@email.chop.eduHill Malinda 2hillme@email.chop.eduPazder Rachel 1rpazder@rosemont.eduFeudtner Chris 134feudtner@email.chop.edu1 Pediatric Advanced Care Team and Pediatric Generalist Research Group, Division of General Pediatrics, The Children's Hospital of Philadelphia, PA, USA2 Department of Social Work and Family Services, The Children's Hospital of Philadelphia, PA, USA3 The Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA4 Center for Bioethics, University of Pennsylvania, Philadelphia, PA, USA2004 26 7 2004 3 3 3 20 2 2004 26 7 2004 Copyright © 2004 Forte et al; licensee BioMed Central Ltd.2004Forte et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background Despite abundant bereavement care options, consensus is lacking regarding optimal care for bereaved persons. Methods We conducted a systematic review, searching MEDLINE, PsychINFO, CINAHL, EBMR, and other databases using the terms (bereaved or bereavement) and (grief) combined with (intervention or support or counselling or therapy) and (controlled or trial or design). We also searched citations in published reports for additional pertinent studies. Eligible studies had to evaluate whether the treatment of bereaved individuals reduced bereavement-related symptoms. Data from the studies was abstracted independently by two reviewers. Results 74 eligible studies evaluated diverse treatments designed to ameliorate a variety of outcomes associated with bereavement. Among studies utilizing a structured therapeutic relationship, eight featured pharmacotherapy (4 included an untreated control group), 39 featured support groups or counselling (23 included a control group), and 25 studies featured cognitive-behavioural, psychodynamic, psychoanalytical, or interpersonal therapies (17 included a control group). Seven studies employed systems-oriented interventions (all had control groups). Other than efficacy for pharmacological treatment of bereavement-related depression, we could identify no consistent pattern of treatment benefit among the other forms of interventions. Conclusions Due to a paucity of reports on controlled clinical trails, no rigorous evidence-based recommendation regarding the treatment of bereaved persons is currently possible except for the pharmacologic treatment of depression. We postulate the following five factors as impeding scientific progress regarding bereavement care interventions: 1) excessive theoretical heterogeneity, 2) stultifying between-study variation, 3) inadequate reporting of intervention procedures, 4) few published replication studies, and 5) methodological flaws of study design. Bereavementinterventionsystematic review ==== Body Background Give sorrow words; the grief that does not speak Whispers the o'er fraught heart and bids it break. Shakespeare, Macbeth IV, iii, 209 Grieving the death of a loved one has an ancient history: from time immemorial, cultures have provided the bereaved with advice and rituals to address – and express – the experience of grief [1]. Over the past several decades, efforts to aid the bereaved have increasingly focused on the physical and psychological morbidity, and the spiritual suffering and social isolation associated with bereavement. The resulting plethora of intervention options, ranging from mutual-help support groups to prescribed pharmacotherapy and professionally led psychotherapy, is striking, as is the panoply of settings in which bereavement care can be found: hospitals, hospices, churches, palliative care units, community-based services, and bereavement-specific foundations all provide an array of bereavement care interventions. This welter of activity testifies to the broadly valued goal of decreasing the severity of bereavement-related symptoms. Given the abundance of care options, what is the best way to care for a bereaved person? Numerous studies measuring the impact of bereavement interventions have been published in diverse journals, yet no consensus has emerged in the medical, mental health, or social work communities regarding whether one form of treatment is preferable to another [2-5]. We therefore have conducted a systematic review of bereavement care interventions. Our goal is to present a comprehensive yet coherent synthesis of the current literature that will promote the advancement in the quality of care and research on behalf of bereaved individuals. Methods Data sources To identify studies in the traditional medical literature as well as the complementary and alternative medicine literature, we searched the following databases: MEDLINE; PsychINFO; Cumulative Index to Nursing and Allied Health (CINAHL); BIOSIS Previews; ISI Science Citation Index Expanded and Social Sciences Index; Evidence Based Medicine Reviews (EBMR), including the Cochrane Database of Systematic Reviews (DSR), the Cochrane Controlled Trial Registry (CCTR), Database of Abstracts of Reviews of Effectiveness (DARE), and the American College of Physicians' (ACP) Journal Club Review; Sociological Abstracts; Alt HealthWatch; and Wilson Web from 1966 to 2003. We identified all relevant articles on bereavement care interventions by using the primary search terms of "bereaved or bereavement" and "grief", combined with secondary descriptors of "intervention or support or counselling or therapy" and "controlled or trial or design". Study selection Our inclusion criteria specified that each study: 1) addressed the treatment of bereaved individuals, and 2) included an evaluation of a selected method of therapy aimed at reducing the grief reaction due to bereavement. We considered only articles written in the English language. We then reviewed the titles and abstracts of all articles we retrieved through our initial database search, and obtained the full texts of all applicable studies. We also reviewed the references in all applicable studies for additional pertinent studies. Data extraction The full articles of all studies that met inclusion criteria and passed subsequent title and abstract reviews were retrieved and examined independently by two of the authors. Each article was reviewed for measured outcomes, patient and decedent characteristics, and intervention characteristics. These measures included sample size, type of intervention, length of intervention, patient's relationship to the deceased, time since the bereaved death, and patient demographics. Data was extracted and any disagreements were resolved through discussion, clarification, and consensus within the research team. Characteristics of reviewed studies The initial literature search generated 737 citations. Elimination of duplicate citations yielded 340 references. 2 studies, written in Chinese and Spanish, were excluded. Reviewing the titles culled the sample to 243 citations, and a review of the abstracts found 87 of these to be potentially relevant. Of these, 9 were dissertations, 2 were irretrievable, 2 were duplicate publications of the same study, and 15 were ineligible because they did not meet our inclusion criteria. The resulting set of 74 articles was subject to review for data extraction. A list of all citations found, including those excluded from this analysis, is available [see Additional file 1]. Of the 74 studies that met inclusion criteria, almost 6,000 participants within these studies experienced a multitude of losses – of parents, spouses, children, and other loved ones who had died from a wide range of causes, both sudden and protracted. The therapies utilized and outcomes evaluated varied widely. Heterogeneity among both the outcomes and the measures used to assess similar outcomes precluded an effort to summarize data across studies, even in the form of generic effect-size measures. Furthermore, for a significant portion of the studies, concerns regarding the internal or external validity of the reported results cautioned against making quantitative summary statements regarding treatment effects. Results The 74 studies selected for detailed review evaluated diverse types of interventions designed to ameliorate the adverse physical and psychological outcomes associated with bereavement. These interventions can be classified according to various schemes, including their underlying theoretical framework (ranging from Freudian psychoanalysis to neurotransmitter imbalances), the format of the intervention (individual, group, family, marital), the timing of the intervention (acute, intermittent crisis, chronic), the tasks assigned to the bereaved (ranging from verbalizing feelings to taking medication), or the population targeted for the intervention (children, adults, seniors). We chose to organize this review on the basis of the social framework used to implement the intervention (that is, either personalized structured therapeutic relationships or less personal systems-level interventions), as this attribute of the interventions emerged as the most verifiable and salient measure. Structured therapeutic relationship Eight studies feature pharmacotherapy, but only four compared active therapy to non-pharmacotherapy controls, and only one study clearly reported their random allocation method (Table 1) [6-13]. These studies targeted adults and seniors, ranged in sample size from 10–80 subjects, and used a variety of drugs, including tricyclic antidepressants (TCA), selective serotonin reuptake inhibitors (SSRI), buprioion, and benzodiazepines. Overall, these studies demonstrated a statistically significant beneficial effect of pharmacotherapy on ameliorating symptoms of depression and improving subjective sleep quality [6-11,13]. These benefits persisted only as long as the subjects continued to receive pharmacotherapy. Pharmacotherapy was found, however, to have a mixed effect on bereavement intensity as measured by symptoms of grief (i.e., Texas Revised Inventory of Grief, Inventory of Complicated Grief). For example, Warner and colleagues (2001) did not find evidence of an effect of benzodiazepines (diazepam) on bereavement-related grief intensity[12]. One study combined pharmacotherapy with psychotherapy in a 16-week double-blinded factorial design trial of nortriptyline (NT) and interpersonal psychotherapy [6]. The 80 patients were randomly assigned to one of four treatment conditions: NT plus interpersonal psychotherapy, NT plus medication clinic (i.e., no interpersonal psychotherapy), placebo pill plus interpersonal psychotherapy, and placebo pill plus medication clinic (i.e., no interpersonal psychotherapy conditions). Details of the psychotherapy were not described. While the results displayed a statistically significant benefit of nortriptyline over placebo regarding remission of depression, none of the treatment conditions were associated with diminishment of grief. Table 1 Pharmacotherapy Interventions Medication Pop CG RA Num* TSL (days) Dose DT (days) Key Outcome Measures Article Nortriptyline Senior Y Y-NE 80/66 216–279 Steady-state plasma level: 50–120 ng/mL 112 Depression (HAM-D); Grief (TRIG) Reynolds, Miller, et al, 1999** Senior Y Y-NE 27/27 210 (mean) Steady-state plasma level: 79.9+/-28.3 ng/mL Daily dose: 70.8+/-22.2 mg <180 Sleep (PSQI); Depression (HAM-D, BDI) Taylor, Reynolds, et al, 1999 Senior Y NR 30/24 276 Steady-state plasma level: 72.7 ng/mL Daily dose: 53.0 mg 112 Sleep (PSQI) Pasternak, Reynolds, et al, 1994 Senior N NA 13/13 150–750 Daily dose: 49.2 mg 9–184 Depression (HAM-D, BDI, BSI); Grief (TRIG, JGI); Sleep (PSQI) Pasternak, Reynolds, et al, 1991 Nortriptyline and Paroxetine Adult N NA 21/15 183–4158 PT Daily dose: 20–50 mg NT Daily dose: 50–160 mg 120 Depression (HAM-D); Grief (ICG); Sleep (PSQI) Zygmont, Prigerson, et al, 1998 Desipramine Adult N NA 10/9 NR Daily dose: 75–150 mg 28 Depression (HDRS, CGI, Raskin DS); Grief (Separation Distress) Jacobs, Nelson, et al, 1987 Bupropion Adult N NA 22/14 42–56 Daily dose: 150–300 mg 56 Grief (TRIG, ICG); Depression (HAM-D) Zisook, Schuchter, et al, 2001 Diazepam Senior Y Y 35/30 <14 2 mg/pill, self-administered <42 Bereavement (BPQ) Warner, Metcalfe, et al, 2001 Notes: * All Ns are reported as (starting population of bereaved individuals/bereaved population completing all follow-ups), unless only study included only one assessment. ** Study also included psychotherapy condition. Legend: Pop, Target Population; CG, Control Group; RA, Random Assignment; Num, Number of subjects; TSL, Time Since Loss; DT, Duration of Trial; NA, Not Applicable; NR, Not Reported; UC, Unclear; Y, Yes; N, No; Y-NE, Randomization mentioned, but allocation method not explicitly stated; RS, Randomization Subverted. Support groups or counselling constituted the intervention in 39 studies, of which 23 had control groups and 15 claimed random allocation, yet only three of these included clearly described allocation methods (Table 2) [14-52]. Ten of these were mutual/self-help, with the majority taking the form of informal group therapy. The remaining 29 studies were professionally led support groups targeting select subgroups including parentally bereaved children, college students, and seniors, as well as many specific adult populations. Program implementation across studies varied even further. This variation was found in terms of number of sessions (one to 25), whether the sessions proceeded with full-fledged patient-driven discussion or highly structured protocols, whether attendance was mandatory or individually motivated, as well as in the nature of the group leadership and the format (individual, group, or marital). Perhaps due to these or other differences in the interventions, some studies documented study treatment effects [22,26,29-31,33,34,52] while other studies showed no effect [15,17,27,37,46,51]. Table 2 Support/Counselling Interventions Type Format Pop CG RA Num TSL (days) DT Key Outcome Measures Article Mutual/Self-help Individual Adult Y Y-NE 162/62 ~30 NR Psychiatric Functioning (GHQ); Social Support/psychological and psychophysiological variables (author-created) Vachon, Lyall, et al, 1980 Mutual/Self-help (included professionally-lead groups) Group Senior Y RS 339/295 30–60 56, 365 days Self-Esteem (Rosenberg's Self-Esteem Scale); Life Satisfaction (LSI-A); Depression (GDS); Grief (TRIG) Caserta & Lund, 1983 Mutual/Self-help Group Senior Y N 23 34–474 21 days; 7 sessions Domain Specific State Locus of Control (Zeigler-Reid State Locus of Control Measure); Trait Locus of Control (I-E); Distress (BSI, GSI) McKibbin, Guarnaccia, et al, 1997 Mutual/Self-Help Group Adult Y Y 113/67 90–365 63 days; 9 sessions Depression (GHQ, BDI); Anxiety (STAI); Social Functioning (SAS); Social Support (SSQ) Tudiver, Hilditch, et al, 1992 Mutual/Self-help Group Adult Y Y-NE 113/112 90–365 63 days Healthcare visit rates (Family Physician, Specialist, Psychiatrist) Tudiver, Permaul-Woods, et al, 1995 Mutual/Self-help Group Adult Y N 38/21 90–750 70 days; 10 sessions Treatment Expectancy (Expectancy Scale); Depression (BDI); Avoidance, Anxiety (Social Anxiety and Distress Scale); Enjoyability (Pleasant Events Scale); Life Satisfaction (Life Satisfaction Scale) Walls & Meyers, 1985 Mutual/Self-help Group Adult Y N 721/502 ~1290 365 days; >3 sessions Depression, Anxiety, Somatization (Hopkins Symptom Checklist); Self Esteem, Well-being, Mastery (Not reported) Lieberman & Videka-Sherman, 1986 Mutual/Self-help Group Adult Y N 667/391 365–1095 365 days Depression, Anxiety, Somatization (Not reported); Self Esteem (Rosenberg 1965); Life Satisfaction, Mastery, Medication (Not reported); Social Functioning Parental Functioning Attitudes (BPQ) Videka-Sherman & Lieberman, 1985 Mutual/Self-help Group Adult N Y-NE 61/55 120–1095 84 days; 12 sessions Avoidance/Intrusion (IES); Stress Symptoms (SRRS); Depression (BDI); Mental Distress (BPRS, SCL-90); Social Functioning (SAS-SR); Overall Functioning (GAS) Marmar, Horowitz, et al, 1988** Mutual/Self-help Group Adult N NA 53/33 <730 8 sessions, optional 4 Psychosomatic Symptoms (SCL-90 subscales: somatization, obsessive-compulsive, interpersonal sensitivity, depression, anxiety, hostility, phobic anxiety, paranoid ideation, psychoticism, GSI) Rogers, Sheldon, et al, 1982 Professionally Lead Individual Adult Y NR 493/225 120 1 day; 1 session Grief (HGRC) Kaunonen, Tarkka, et al, 2000 Professionally Lead Family Adult Y Y-NE 50/30 1–2 1–120 days; up to 8 sessions General Health Questionnaire (self-rated); Anxiety, Depression (Leeds Scale) Forrest, Standish, & Baum, 1982 Professionally Lead Family Adult Y UC 334/161* <1–180 7–70 days; up to 10 sessions Medical Illness (CMI, MMPI); Psychiatric Illness (Boston Bereavement, Mood Inventory); Family Functioning (Ferriera-Winter, Bodin Drawing); Crisis Coping (Intrapersonal, Family, Job/Financial, Social); Social Cost (Gross Income, Living Expenses, Absenteeism, Economic Loss) Williams, Lee, & Polak, 1976 Polak, Egan, et al, 1975 Professionally Lead Family Adult Y UC 176/86* <1–180 7–70 days; up to 10 sessions Neurotic Symptoms Scale; Bodin Family Closeness; Crisis Coping Scale; Religious helping of others; Authoritarian Family Functioning; Depression; Monthly Income; Monthly Expenses; Social Costs; Bereavement Adjustment Williams & Polak, 1979 Professionally Lead Family Adult N NA 77/37* <1 >360 days Personal and social phenomena of death (structured interview) Oliver, Sturtevant, et al, 2001 Professionally Lead Family Child Y Y-NE 72/55 <730 15 sessions Depression (CDI, CBCL, PERI Demoralization Scale); Parental Warmth (CRPBI); Family Cohesion (Family Environment Scale); Parent perception of support (author-created scale); Family Coping (F-COPES) Sandler, West, et al, 1992 Professionally Lead Group Senior N NR 28/11 90–7300 <140 days; up to 20 sessions Social Support (ASSIS); Affect/Mood (PANAS); Emotional/Social Loneliness (ESLI) Stewart, Craig, et al, 2001 Professionally Lead Group Adult Y Y 197/166 <180 70 days; 10 sessions Grief (TRIG, GRI); Distress (POMS); Depression and Anxiety (SIGH-AD) Goodkin, Blaney, et al, 1999 Professionally Lead Group Adult Y Y-NE 242/185 0–35 77 days; 3 sessions Distress (POMS-TMD, Anxiety-tension, Depression-dejection, Anger-hostility, Confusion-bewilderment, Overall emotional disturbance); Self-Esteem (Rosenberg 1965 scale) Swanson, 1999 Professionally Lead Group Adult Y Y-NE 150/120 30–240 270 days Depression (CES-D, BDI); Anxiety (A-Sta); Somatic Symptoms (SOM); Emotional Symptoms (EMOT); Life Satisfaction (Lsat, SelfAnch) Kay, Guernsey de Zapien, et al, 1993 Professionally Lead Group Adult Y Y-NE 119/119 <180 70 days; up to 10 sessions Immunological measures (CD3+CD4+ cell count, CD3+CD8+ cell count, CD4/CD8 ratio, CD3+ cell count, CD4 cell count, Lymphocyte count, T-lymphocyte count); Neuroendocrine measure (Plasma cortisol level) Goodkin, Feaster, et al, 1998 Professionally Lead Group Adult Y Y-NE 110/80 ~730 28 days; 8 sessions Coping and Adaptation (TAT) Balk, Lampe, et al, 1998 Professionally Lead Group Adult Y Y-NE 36/36 <180 70 days; up to 10 sessions Plasma Viral Load (HIV-1 RNA copy number) Goodkin, Baldewicz, et al, 2001 Professionally Lead Group Adult Y N 159/127 42–140 Up to 25 sessions Social Support (SSES); Group Involvement (Liberman & Videka-Sherman, 1986); Depression (CES-D, POMS-D); Anger (POMS-A); Anxiety (POMS-T); Stress (IES) Levy, Derby, et al, 1993 Professionally Lead Group Adult Y N 121 30–4745 30–365 days Grief (HGRC subscales: Despair, Panic behavior, Personal growth, Blame and Anger, Detachment, Disorganization) DiMarco, Menke, & McNamara, 2001 Professionally Lead Group Adult N Y 139/107 90–17155 84 days; 12 sessions Avoidance/Intrusion (IES); Grief (TRIG); Interpersonal Distress (IIP); Social Functioning (SAS-SR); Depression (BDI); Anxiety (STAI); Mental Distress (BSI, GSI); Self-Esteem (SES); Physical Functioning (SF-36); Symptomatic Distress (SCL-90) Piper, McCallum, et al, 2001** Professionally Lead Group Adult N N 83/70 <30–8030 49 days; 7 sessions Physical, Emotional, and Social Functioning (author created measures); Self Esteem (Rosenberg, 1962); Locus of Control (I-E); Life satisfaction (Neugarten, Havighurdt, & Tobin, 1961); Attitude Toward Women (Spence & Helmreich, 1972, Gump 1972) Barrett, 1978 Professionally Lead Group Adult N NA 392/77 NR 56 days Distress (BSI); Group Process and Satisfaction (author created questionnaire) Glajchen & Magen, 1995 Professionally Lead Group Adult N NA 174/138 780 730 days Motives for joining (Lieberman 1979); Interpersonal relations (Porat 1987); Group leadership style (Porat 1987); Perceived contribution of treatment on recovery Geron, Ginsberg, & Solomon, 2003 Professionally Lead Group Adult N NA 21/21 NR 70 days; up to 10 sessions Perceived Social Support (PRQ); Perceived Stress (PSS) Davis, Hoshiko, et al, 1992 Professionally Lead Group Adult N NA 21/21 365–3650 52 days; up to 8 sessions Depression (CDI); Anxiety (HSC-25); Knowledge of Death and Bereavement (KDBQ) Stoddart, Burke, & Temple, 2002 Professionally Lead Group Adult N NA 20 90–1095 <1095 days; unlimited sessions Grief (TRIG); Social Network (SNM, SNG) Forte, Barrett, & Campbell, 1996 Professionally Lead Group Adult N NA 12/5 60–780 28 days; 8 sessions Emotional Distress (EPI); Family Adjustment (FACES-III); Social Adjustment (SAS-SR) Heiney, Ruffin, & Goon-Johnson, 1995 Professionally Lead Group Child Y Y-NE 17/17 >730 42 days; 6 sessions Self-Esteem (PH); Depression (CDI); Behavior (CBCL-TRF, CBCL-YSR) Huss & Ritchie, 1999 Professionally Lead Group Child N NA 38/29 <900 300 days; 12 sessions Depression (BID); Attitude/ Conception of Death (ATCD) Shilling, Koh, et al, 1992 Professionally Lead Group Child N NA 18/18 <730 52 days; 8 sessions Bereavement Survey (author created); Loss Resolution (LRS-Modified); Distress and Somatic Complaints (ALAC) Opie, Goodwin, Finke, et al, 1992 Professionally Lead Group Child N NA 6/6 240–1020 42 days; 6 sessions Psychological measures (Lewis Counselling Inventory, IPAT) Quarmby, 1993 Professionally Lead Group Child N NA 4/4 <90 77 days; 11 sessions Self-Esteem (Piers-Harris Self-Concept Scale); Descriptive (Risk Impact, Negative Chain Events, Opening Up Opportunities) Zambelli & DeRosa, 1992 Professionally Lead Couple/ Marital Adult Y Y-NE 57/31 NR Mean of 6 sessions Grief (TRIG); Irritability, Depression, Anger (IDA) Lilford, Stratton, et al, 1994 Notes: * Families, not individuals. ** Study also included psychotherapy condition. Legend: Type, Type of Intervention; Format, Format of Intervention; Pop, Target Population; CG, Control Group; RA, Random Assignment; Num, Number of subjects; TSL, Time Since Loss; DT, Duration of Trial; NA, Not Applicable; NR, Not Reported; UC, Unclear; Y, Yes; N, No; Y-NE, Randomization mentioned, but allocation method not explicitly stated; RS, Randomization Subverted. Several studies documented substantial spontaneous improvements in bereavement symptomology in the control groups. Kay and others (1993) report a bereavement intervention for Mexican-American widows [33]. They found that all widows improved on all depression scales, state anxiety, life satisfaction, and emotional and somatic symptom scales over the course of two years. However, those widows in the experimental support group exhibit significantly improved changes in these scores. Tudiver and colleagues (1992) conducted a mutual-help support group for recently bereaved widowers [17] that can be compared to Vachon and colleagues' (1980) and Barrett's (1978) widow studies [14,39]. Tudiver and others found significant improvement over time (baseline to eight months) for all widowers, but found no significant differences between those who received treatment and a comparison group of windowers who were on the wait list to receive treatment but had not. Psychotherapy-based treatments, another form of psychological interventions, can be done in different formats (family, group, or individual), and via different approaches. Of the 25 studies that use psychotherapy as an intervention, approaches included cognitive-behavioral, psychodynamic, psychoanalytical, and interpersonal approaches, as well as combinations of these and modality and social support (Table 3)[6,19,22,35,38,53-72]. Seventeen of these studies utilized control groups, only 13 claimed randomization, and only five of these clearly stated their method of allocation. Table 3 Psychotherapy Interventions Type Format Pop CG RA Num TSL (days) DT Key Outcome Measures Article Cognitive-behavioral Individual Senior Y N 58/NR 120–180 70 days; 4 sessions Mastery (Personal Mastery Scale); Well-being (MHI subscales, ABS Subscale, PERI self-esteem); Distress (PERI Demoralization Scales, MHI subscales) Reich & Zautra, 1989 Individual Senior N NA 4/4 540–730 98 days; 14–18 sessions Distress (SUDS); Grief (ICG); Depression (BDI); Anxiety (BAI) Harkness, Shear, et al, 2002** Individual Adult Y Y 30/25 >90 35 days; 10 sessions Avoidance/Intrusion (IES); Anxiety (SCL-90); Depression (SCL-90); Mood (POMS) Lange, van de Ven, et al, 2001 Individual Adult Y Y-NE 26/14 180–7300 70 days; 6 sessions Depression (Wakefield, BDI); Physical Symptoms (Mawson et al, 1981); Fear (FQ); Grief (TRIG); Avoidance (Bereavement Avoidance Tasks) Sireling, Cohen, & Marks, 1988 Group Adult Y Y-NE 261/147 46–229 84 days; 8 sessions Mental Distress (BSI, GSI); PTS Symptoms (TES); Grief (GES); Physical Health (HHB); Marital Strain (DAS) Murphy, Johnson, et al, 1998 Murphy, 1997 Group Adult Y Y-NE 110/80 ~730 28 days; 8 sessions Coping and Adaptation (TAT) Balk, Lampe, et al, 1998 Group Adult Y N 38/21 90–750 70 days; 10 sessions Treatment Expectancy (Expectancy Scale); Depression (BDI); Avoidance, Anxiety (Social Anxiety and Distress Scale); Enjoyability (Pleasant Events Scale); Life Satisfaction (Life Satisfaction Scale) Walls & Meyers, 1985 Group Adult N NA 8/8 >30 56 days; 8 sessions Avoidance/Intrusion (IES); Depression (BDI, SCL-90-R); Anxiety (SCL-90-R, STAI); Grief (GRI); Distress (PERI Demoralization) Sikkema, Kalichman, et al, 1995**** Group Child Y UC 19/18 <730 NR Behavior (BRIC-S, BRIC-H); Depression (DSRS); Grief (BP) Hilliard, 2001 Psycho-dynamic Individual Senior Y Y 228 ~60 <180 days; Unlimited sessions Number of Office Visits, Types of Illnesses Gerber, Wiener, Battin, et al, 1975 Individual Senior Y Y-NE 33/30 90–1170 14 days; 4 sessions Mental Distress (BSI); Depression (GDS); Hopelessness (GHS); Avoidance/Intrusion (IES); Mood (PANAS) Segal, Bogaards, et al, 1999 Individual Adult Y Y 66/56 <49 90 days; up to 9 sessions General Health(general health questionnaire) Raphael, 1977 Individual Adult Y N 72/63 60–462 12–20 sessions Avoidance/Intrusion (IES-A, IES-I); Depression (SCL-90); Anxiety (SCL-90); Total Pathology (SCL-90); Stress-Intrusion (SRRS); Neurotic Symptoms (BPRS) Horowitz, Weiss, et al, 1984 Individual Adult N Y-NE 12/6 365–3650 196 days Depression (Wakefield); Grief (TRIG) Phobic Avoidance (FQ); Hostility/Anger/Guilt (HAG); Attitude to self and deceased (author-created scales); Avoidance (Bereavement Avoidance Tasks); Physical Symptoms (Maddison & Viola, 1968); Compulsive Behavior (Compulsive Activity Checklist); Social Adjustment (Watson & Marks, 1971) Mawson, Marks, et al, 1981 Individual Adult N NA 1/1 <180 112 days; 10 sessions Grief (Grief Scale); Coping (CRI) Orton, 1994 Group Senior Y Y 150/117 <365–7300 540 days; 6 sessions Depression (BDI); Socialization (RSAS) Constantino, 1988***** Psycho-dynamic Group Adult Y Y-NE 56/53 120–330 8 sessions Depression, Anxiety, Somatization (Hopkins Symptom Checklist); Grief Intensity, Preoccupation, Guilt, Anger (Lieberman & Videka-Sherman, 1986); Psychological Distress (Bradburn Affect Balance Scale); Locus of Control (Pearlman et al, 1981); Self-Esteem (Rosenberg scale, 1965); Social Adjustment (Pearlman et al, 1981, Lieberman & Videka-Sherman, 1986) Lieberman & Yalom, 1992 Group Adult Y N 50/50 NR 90 days; 14 sessions Grief (TRIG) Sabatini, 1988–89 Group Adult N Y 139/107 90–17155 84 days; 12 sessions Avoidance/Intrusion (IES); Grief (TRIG); Interpersonal Distress (IIP); Social Functioning (SAS-SR); Depression (BDI); Anxiety (STAI); Mental Distress (BSI, GSI); Self-Esteem (SES); Physical Functioning (SF-36); Symptomatic Distress (SCL-90) Piper, McCallum, et al, 2001* Group Adult N Y-NE 61/55 120–1095 84 days; 12 sessions Avoidance/Intrusion (IES); Stress Symptoms (SRRS); Depression (BDI); Mental Distress (BPRS, SCL-90); Social Functioning (SAS-SR); Overall Functioning (GAS) Marmar, Horowitz, et al, 1988** Group Child Y N 16/16 30–365 56 days Depression (CDI); Behavior (AP, AT); Grief (BP); Family alliance (TP); Grief, family relationship (TC) Tonkins & Lambert, 1996 Group Child N NA 45/37 30–3650 70 days Trauma (CPTSRI) Salloum, Avery, & McClain, 2001 Psycho-analytic Group Adult N N 154/59 NR 84 days; 12 sessions Affect (author created); Psychodynamic Work (PWORS); Severity of objectives (author created) McCallum, Piper, & Morin, 1993 Inter-personal Individual Senior Y Y-NE 80/66 216–279 112 days; up to 16 sessions Grief (TRIG) Reynolds, Miller, et al, 1999*** Behavioral and Psycho-dynamic Individual Adult Y N 83/83 <1825 15–20 sessions Anger (State Trait Anger Inventory); Anxiety (STAI); Avoidance/Intrusion (IES); Somatic/psychoneurotic symptoms (SCL-90); (Locus of Control Scale) Kleber & Brom, 1987 Notes: * Study also included support/counselling condition. ** Treatment also included aspects of interpersonal psychotherapy. *** Study also included pharmacotherapy condition. **** Treatment also included aspects of social support. ***** Study also included social activities condition. Legend: Type, Type of Intervention; Format, Format of Intervention; Pop, Target Population; CG, Control Group; RA, Random Assignment; Num, Number of subjects; TSL, Time Since Loss; DT, Duration of Trial; NA, Not Applicable; NR, Not Reported; UC, Unclear; Y, Yes; N, No; Y-NE Randomization mentioned, but allocation method not explicitly stated. Cognitive-behavioral therapy was employed in nine trials, four of which used individual sessions while five studies used group sessions. Murphy and colleagues (1998) studied an intervention for parents bereaved by the violent death of their children [57]. The results show no treatment effect between intervention and control groups over the five main tested outcome variables. The authors then proceeded with a post-hoc subgroup analysis, which identified mothers with high Global Severity Index scores and grief at baseline as potentially benefiting from intervention during the period, while fathers who received the intervention appeared to have more posttraumatic stress disorder (PTSD) symptoms at six-month follow-up. Kleber and Brom (1987) conducted a comparative outcome study of three forms of short-term psychotherapy [69]. They compared the results of 83 patients suffering from a major loss who had been randomized into hypnotherapy (behavioral), trauma desensitization (behavioral), psychodynamic therapy, and a delayed-treatment control group. They found all three therapies successful in improving patients' conditions, but did not find any particular therapy to be significantly more effective than another. While the control group showed slight recovery, over time the three therapies were more effective in reducing symptoms of the bereavement response. Studies of psychodynamic therapy, which strives for the patient to understand and cope better with feelings by re-experiencing them and talking them through with the aid of the therapist, was found to be quite prevalent in the bereavement care literature. Overall, the results are mixed, with more support found in the group format of psychodynamic therapy than in individual therapy. Of the studies we evaluated as psychodynamic therapy, six were individual in format, seven had a group format, and eight employed control groups; five of these claimed random allocation (one additional study randomly assigned subjects to two experimental conditions but lacked a control group). Psychoanalysis, as exemplified by Freud, proceeds with an inward investigation of unconscious mental processes and childhood experiences as the principal therapeutic procedure. Problematic measurement methodology beset the one study that utilized a group format to provide a psychoanalytic-based intervention (with no details regarding the tasks assigned to the patients)[68]. This study focused primarily on the relationship between the patient's personal affect (measured by an unvalidated affect assessment scale) and a favorable treatment outcome (measured again by an ad-hoc unvalidated measure). Behavioral therapy uses learning principles (such as behavior modification, systematic desensitization, and aversion) to eliminate or reduce unwanted reactions to either external situations, one's thoughts and feelings, and bodily sensations or functions. Behavioral therapy was used in only one study, which compared traumatic desensitization to hypnotherapy and psychodynamic therapies [69]. As described in the section on cognitive-behavioral therapies above, all three therapies resulted in significant improvements from pre- to post-treatment as compared to controls, and no one therapy was found to be more effective than the others in treating bereavement-related symptoms. Interpersonal therapy aims to improve communication skills and increase self-esteem during a short time period by focusing on a patient's behaviors and social interactions with family and friends, directly teaching how better to relate to others. Only one study used interpersonal therapy as a bereavement care intervention, and this study found no effect on grief as the only measured outcome [6]. Systems-oriented interventions Seven studies featured interventions that altered the manner in which the healthcare system interacted with patients, family, and friends prior to death, guided by an underlying (yet not fully explicated) notion that interactions experienced by loved ones prior to death can influence the subsequent bereavement process (Table 4) [73-79]. Six of the seven interventions provided enhanced or augmented care, in the form of palliative care, hospice care, or care coordination. One intervention gave family members the option of witnessing resuscitation efforts [79]. Overall, the studies that reported systems-oriented interventions produced mixed results of efficacy, with only three of the seven studies showing any treatment effect, mostly in long-term follow-up ranging from 60–365 days post-death. In fact, no study found significant treatment effects when measured during the intervention. Table 4 Systems-Oriented Interventions Intervention Pop CG RA Num Time of Evaluation Key Outcome Measures Article Care Coordination Relative of cancer death Y Y 94 365 days pre-death 56 days post-death Anxiety (HADA, Leeds Depression and Anxiety Scale); Depression (HADD, Leeds Depression and Anxiety Scale); Social Support (Family Apgar Scale) Addington, MacDonald, et al, 1992 Emergency Room Relative of Emergency Room Death Y N 100/66 180–365 days post-death Changes in satisfaction of care, information received (author-created questionnaire) Adamowski, Dickinson, et al, 1993 Hospice Care Relative of cancer death Y Y-NE 96 42 days post-death 540 days post-death Depression (CES-D); Anxiety (Rand Health Insurance Study); General Health (Rand Health Insurance Study); Social Functioning Kane, Klein, et al, 1986 Palliative Care Relative of cancer death Y Y 183 60–270 days pre-death 390 days post-death Grief (TRIG2) Ringdal, Jordhoy, et al, 2001 Relative of cancer death Y NR 119/49 0–60 days post-death Anxiety, Depression, Mental Exhaustion ("observations and ratings") Haggmark & Theorell, 1988 Relative of cancer death Y N 49/37 365 days post-death Health, Anger, Mental State, Depression (Holland & Segroi's instrument) Haggmark, Bachner, & Theorell, 1991 Witnessed Resuscitation Relative of unsuccessful resuscitation Y Y 18 30 days post-death 90 days post-death Grief (TRIG1, TRIG2); Avoidance/Intrusion (IESA, IESI); Depression (BDI, HADD); Anxiety (HADA, BAI) Robinson, Makenzie-Ross, et al, 1998 Legend: Pop, Target Population; CG, Control Group; RA, Random Assignment; Num, Number of subjects; NR, Not Reported; Y, Yes; N, No; Y-NE Randomization mentioned, but allocation method not explicitly stated. Ringdal and colleagues (2001) found no significant differences between those family members whose relative received palliative care and those who received traditional care [76]. This intervention, however, was not directed to the bereaved relatives, but rather to their terminally ill relatives. The bereaved relatives did show an overall significant decline in TRIG grief scores over one year post-bereavement for both palliative and traditional care groups. Robinson (1998) examined the psychological effect of witnessing resuscitation efforts of patients in the emergency room on bereaved relatives [79]. They found no psychological differences between the control group who did not witness the resuscitation attempt and the experimental group who had the option of viewing the resuscitation effort. In fact, at the three- and nine-month follow up, the experimental group exhibited median scores lower (that is, better) than the controls on five of the eight measured scales. At nine months, the authors found the difference in TRIG2 scores approaching the 5% significance level with a reported p = 0.08. These findings provide no evidence to support the popular belief that relatives should be excluded from the resuscitation room, and provide only weak evidence of possible psychological benefit of witnessed resuscitation; they do not, however, suggest that having witnessed an unsuccessful resuscitation attempt alleviates the grief reaction of the bereaved. Discussion When reviewed systematically, the current bereavement intervention literature – notwithstanding the existence of many intriguing reports – yields few reliable conclusions to guide treatment. Good evidence supports the pharmacological treatment of depression occurring in the context of bereavement. For all other forms of intervention, however, and for all attempts to diminish grief per se, no consistent pattern of treatment benefit has been established across well-designed experimental studies. Why – despite prevalence of bereavement, the intense dedication on the part of the bereavement research community, and the multitude of peer-reviewed published bereavement studies – does the field of bereavement care lack a formidable evidence base? In order to improve the effectiveness and quality of bereavement care, this question begs to be addressed. On the basis of our systematic review of the literature, we postulate the following five factors as hindering methodical scientific progress regarding bereavement care interventions. Excessive theoretical heterogeneity As the history of science and medicine suggests, successful scientific inquiry into a topic is typically a cumulative process undertaken by a community of investigators working within a shared scientific paradigm [80,81]. The field of bereavement care intervention studies does not appear to be organized in such a manner, but instead consists of distinct groups of investigators working within disparate theoretical frameworks: pharmacologic, psychodynamic, psychoanalytic, behavioral, cognitive-behavioral, interpersonal, and social supportive theories each vie for attention. Indeed, although specification of an underlying treatment-theory conceptual model may improve causal inference [82], the bereavement care literature may be too invested in and reliant on theoretical justifications of treatments. Consequently, the compiled published reports demonstrate a cumulative 'Tower of Babel' phenomenon, with the different theory-dominated perspectives failing to engage each other meaningfully: the sum is no greater than the parts, and perhaps less. Stultifying between-study variation Treatments featured in published studies vary almost as much as the authors who tested them. One can observe substantial variation across studies regarding the type of intervention generally or regarding the specific implementation of a specific type of intervention (such as different doses of pharmaceuticals); regarding characteristics of targeted patient populations; regarding outcome measurements and study design methodology. Scrutinizing the key outcome measures listed in the accompanying tables illustrates this remarkable heterogeneity. Although these differences have been due in part to diverse treatment-theory paradigms, even studies conducted within the same theoretical paradigm often differed markedly in terms of what potential benefit was being tested, and how it was being measured. Such substantial variation between studies stymies comparison or confirmation of treatment effects. Inadequate reporting of intervention procedures and implementation Aside from the pharmacological studies, which reported the dosing of the intervention medication, very few reported studies describe the intervention procedures in sufficient detail for readers to envision clearly what tasks or activities intervention subjects were asked to perform. This under-specification prevents sensible analysis, within a class of treatments (such as cognitive-behavioral therapy), of observed differences in treatment effects (since the implementation of cognitive-behavioral therapy, for instance, may have been quite different in seemingly similar intervention studies). Few published "replication" studies Inadequate specification of intervention procedures, combined with other factors at work within the community of bereavement care investigators, may have resulted in the dearth of published replication studies. This lack of replication prevents the accumulation of a body of evidence that would confirm, refute, or refine prior estimates of treatment effects. Methodological study-design and data-analysis flaws A final factor inhibiting research progress in the realm of bereavement care interventions encompasses a number of recurring methodological flaws that greatly limit inferences regarding treatment effects. First and foremost is the omission of control groups. Control groups are essential for the valid evaluation of a bereavement intervention, particularly because of the typically self-limited course of grief: even absent any treatment, most bereaved people show "diminished pathological symptoms and fewer signs of disturbance within two years of the loss"[65]. Purported beneficial treatment effects observed in an intervention group without a suitable control group therefore may in fact be simply the natural grief remission process. A second common study design feature is the non-random assignment of study subjects into treatment and control groups, which again limits the strength of inference regarding observed 'treatment' effects, as these differences between treatment and control groups may be due to selection or assignment bias. Third, many studies measured subject outcomes using untried assessment tools that had been created on an ad hoc basis, and which may therefore have compromised measurement accuracy and inference validity. Lastly, studies that failed to demonstrate a statistically-significant difference for the main outcome measure often performed numerous post hoc subgroup analyses, a practice that negates the rigor of statistical hypothesis testing. If these five factors are indeed hampering progress towards improving bereavement care interventions and quality of care for bereaved individuals, then concrete actions could facilitate progress within the field of bereavement care, specifically: 1) Convening a consensus-building conference among key stakeholders and investigators to define a specific research agenda that would draw on a limited number of theoretical paradigms and delineate key elements of treatment theory [82]; 2) Focusing on interventions to improve key outcomes that are valued by bereaved individuals; 3) Targeting well-defined patient populations at well-defined phases of bereavement; 4) Conducting high-quality randomized controlled trial research designs, employing rigorous tests of hypotheses defined prior to the conduct of the study, and eschewing unplanned subgroup analyses; 5) Weighing the ethical arguments for and against the use of randomized control subjects in such research; 6) Increasing incentive to conduct and publish highly-comparable replication studies; and 7) Enforcing the adoption of uniform standards regarding clinical trial study reporting (such as outlined in the CONSORT statement [83]) by journal editors and the bereavement research community. Competing interests None declared. Abbreviations CG Control group NT Nortriptyline SSRI Selective serotonin reuptake inhibitors TCA Tricyclic antidepressants TRIG Texas Revised Inventory of Grief Authors' contributions AF assisted in the design of the review, conducted data collection, data abstraction, and drafted the manuscript. MH assisted in the design of the review and critically reviewed several drafts of the manuscript. RP assisted in data collection and abstraction. CF conceived of and designed the review, assisted in drafting and revision of the manuscript, and provided support and mentorship through the process. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here: Supplementary Material Additional File 1 All citations. This file contains citations to all of the studies identified by our literature search and screened for inclusion in this review, as well as other scholarly works consulted during the conduct of this review. Click here for file Acknowledgements The conduct of this review was supported in part by funds from The Children's Hospital of Philadelphia and by grant KO8 HS00002 from the Agency for Health Care Research and Quality. ==== Refs Aries P The Hour of Our Death 1981 Oxford, Oxford University Press 614 Parkes CM Bereavement counselling: does it work? Br Med J 1980 281 3 6 7407489 Schneiderman G Winders P Tallett S Feldman W Do child and/or parent bereavement programs work? Can J Psychiatry 1994 39 215 218 8044728 Chambers HM Chan FY Support for women/families after perinatal death Cochrane Database Syst Rev 2000 CD000452 10796205 Rowa-Dewar N Do interventions make a difference to bereaved parents? 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==== Front BMC Complement Altern MedBMC Complementary and Alternative Medicine1472-6882BioMed Central London 1472-6882-4-91526088410.1186/1472-6882-4-9Research ArticleComplementary and alternative medical therapies for chronic low back pain: What treatments are patients willing to try? Sherman Karen J 12Sherman.k@ghc.orgCherkin Daniel C 13Cherkin.d@ghc.orgConnelly Maureen T 45Maureen_Connelly@harvardpilgrim.orgErro Janet 1Erro.j@ghc.orgSavetsky Jacqueline B 5jacqueline_savetsky@hms.harvard.eduDavis Roger B 6rdavis@bidmc.harvard.eduEisenberg David M 5David_eisenberg@hms.harvard.edu1 Center for Health Studies, Group Health Cooperative, Seattle, Washington 98101, USA2 Department of Epidemiology, University of Washington, Seattle, Washington 98195, USA3 Departments of Family Medicine and Health Services, University of Washington, Seattle, Washington 98195, USA4 Department of Ambulatory Care and Prevention, Harvard Medical School and Harvard Pilgrim Health Care and Harvard Vanguard Medical Associates, Boston, Massachusetts 02215, USA5 Harvard Medical School Osher Institute and Division for Research and Education in Complementary and Integrative Medical Therapies, Harvard Medical School, Boston, Massachusetts 02215, USA6 Beth Israel Deaconness Medical Center, Boston, Massachusetts 02215, USA2004 19 7 2004 4 9 9 9 3 2004 19 7 2004 Copyright © 2004 Sherman et al; licensee BioMed Central Ltd.2004Sherman et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background Although back pain is the most common reason patients use complementary and alternative medical (CAM) therapies, little is known about the willingness of primary care back pain patients to try these therapies. As part of an effort to refine recruitment strategies for clinical trials, we sought to determine if back pain patients are willing to try acupuncture, chiropractic, massage, meditation, and t'ai chi and to learn about their knowledge of, experience with, and perceptions about each of these therapies. Methods We identified English-speaking patients with diagnoses consistent with chronic low back pain using automated visit data from one health care organization in Boston and another in Seattle. We were able to confirm the eligibility status (i.e., current low back pain that had lasted at least 3 months) of 70% of the patients with such diagnoses and all eligible respondents were interviewed. Results Except for chiropractic, knowledge about these therapies was low. Chiropractic and massage had been used by the largest fractions of respondents (54% and 38%, respectively), mostly for back pain (45% and 24%, respectively). Among prior users of specific CAM therapies for back pain, massage was rated most helpful. Users of chiropractic reported treatment-related "significant discomfort, pain or harm" more often (23%) than users of other therapies (5–16%). Respondents expected massage would be most helpful (median of 7 on a 0 to 10 scale) and meditation least helpful (median of 3) in relieving their current pain. Most respondents indicated they would be "very likely" to try acupuncture, massage, or chiropractic for their back pain if they did not have to pay out of pocket and their physician thought it was a reasonable treatment option. Conclusions Most patients with chronic back pain in our sample were interested in trying therapeutic options that lie outside the conventional medical spectrum. This highlights the need for additional studies evaluating their effectiveness and suggests that researchers conducting clinical trials of these therapies may not have difficulties recruiting patients. acupuncturechiropracticmassagemeditationt'ai chilow back pain ==== Body Background Back pain is one of the most common and costly health problems in developed countries, where more than half of adults suffer from this condition each year [1] and 70% to 80% suffer from it at some time in their lives [2]. Patients with back pain are often dissatisfied with standard medical care [3], especially in comparison to care provided by alternative providers [4-6]. In fact, back/neck pain is the number one condition for which Americans seek complementary or alternative medical (CAM) care. During 1997, 30% of Americans with back problems visited CAM practitioners, especially chiropractors and massage therapists, for this condition and another 18% used CAM self-care [7]. Yet, to date, few of these therapies have been adequately evaluated for effectiveness, in part because of methodological challenges including recruiting sufficient numbers of participants, designing reasonable interventions and selecting appropriate control groups. Prior to designing and conducting two pilot clinical trials evaluating the effectiveness of five different CAM therapies for chronic low back pain (LBP) in older (65+ years) and younger (20 through 64 years) adults, we sought to refine recruitment strategies. As part of this effort, we surveyed chronic low back pain patients about their interest in trying each of these five CAM therapies if included in their health plan benefits and as part of two separate clinical trials. In this descriptive and exploratory study, we also collected information about their knowledge of, experience with, and perceptions of each of these therapies. Methods Study design From April to October 2001, we conducted telephone interviews with 249 patients who were currently suffering from non-specific low back pain that had persisted at least three months. The patients were members of a non-profit managed health care system (Group Health Cooperative in the Puget Sound region of Washington State) and a large multi-specialty group practice (Harvard Vanguard Medical Associates, Boston, Massachusetts). Our goal was to interview 150 patients from Group Health and 100 patients from Harvard Vanguard who were otherwise healthy and spoke English, with 50% of the interviews from adults 65 years or older. The Institutional Review Boards of Group Health Cooperative, Seattle WA and Harvard Pilgrim Health Care, Boston, MA approved the study. Sample Using automated visit data, we identified and mailed letters to 787 patients with working phone numbers who visited a Group Health (n = 422) or a Harvard Vanguard (n = 365) primary care provider and had a diagnosis consistent with non-specific low back pain between 12 and 52 weeks previously. Because we were planning to use the results of the survey to help us refine recruitment strategies for two pilot randomized trials, our exclusion criteria for this study were those we planned to use in the subsequent trials. We therefore used the automated visit data to exclude the following individuals from our sample: • those whose back pain may have been due to a specific disease or condition (i.e., sciatica, herniated disc, spondylolisthesis, spine fracture, vertebral fracture, cancer); • those who had other pain conditions that could complicate the interpretation of trial results (rheumatoid arthritis, ankylosing spondylitis, fibromyalgia); • those who were inappropriate candidates for one or more of the clinical trial treatments (aneurism, coagulation disorders, osteoporosis) or who were unlikely to be able to give informed consent or to participate in the baseline and follow-up assessments of the trial (Alzheimers disease, dementia, major psychoses, blindness, deafness). Before administering the in-person survey, we asked eight screening questions and then excluded individuals who did not have back pain at the time of the interview or who had not had back pain for at least 12 weeks, who had previously had low back surgery, who reported having fractured a vertebrae, who were pregnant, who were involved in back-pain related litigation, who had serious health problems, or who could not speak English. We tried to contact all mailees, but could not reach 28 (7%) persons from Group Health and 73 (20%) from Harvard Vanguard despite at least seven phone calls. Among the 394 Group Health and 292 Harvard Vanguard patients who were contacted, 57 from Group Health and 81 from Harvard Vanguard refused the interview and we could not determine their eligibility status, 195 from GHC and 104 from Harvard Vanguard were ineligible upon screening, and 142 from Group Health and 107 from Harvard Vanguard were eligible and interviewed. Thus, we were able to screen 70% of all mailees for eligibility (80% from Group Health and 58% from Harvard Vanguard). All screened and eligible mailees were interviewed. In both areas, individuals aged 65 and older were more likely to refuse screening (in Seattle: 19% of 210 older adults vs. 8% of 212 younger; in Boston: 31% of 184 older adults vs. 13% of 181 younger) and those under 65 were less likely to be contacted by phone (in Seattle: 12% younger vs. 1% older could not be contacted; in Boston: 31% younger vs. 9% older could not be contacted). Most patients were ineligible because they were not experiencing back pain at the time of the interview (n = 82 from Group Health and n = 68 from Harvard Vanguard) or their pain had not persisted for three months (n = 39 from Group Health and n = 11 from Harvard Vanguard). Survey questionnaire We conducted a phone interview that lasted an average of 17.7 minutes (SD = 6.1; range = 8 to 50 minutes). It included questions about demographic characteristics (age, race/ethnicity, education); back pain characteristics (years since first episode of back pain lasting more than two weeks, number of days of pain in the last six months, bothersomeness of pain on a 0 to 10 scale, expectations of pain level one year from the time of interview, and use of medications in the past week); self-reported knowledge (measured on a five point scale) of five CAM treatments or self-care methods (acupuncture, chiropractic, massage, meditation, t'ai chi); previous use of these therapies for any reason and for back pain specifically (and helpfulness of the therapy for back pain relief); perceived harm from previous use of these therapies; expectations of helpfulness of these therapies for current back pain; willingness to try these therapies if offered by the health plan for no additional cost and for a $10 per visit co-pay; willingness to participate in two hypothetical clinical trials, one evaluating acupuncture, chiropractic, and massage and another involving massage, meditation, and t'ai chi. (Respondents were told that the control group in both trials would receive a book about self-management of back pain.) Finally, respondents were asked about which treatment they most preferred among those offered in each trial. Gender and geographic location were obtained for respondents from the enrollment files of each healthplan. General definitions of each therapy were provided only for respondents who informed the interviewers they did not know what a particular therapy was. Acupuncture was described as a system of healing that involved inserting hair thin needles into acupuncture points just beneath the skin or using other methods, such as heat, to stimulate these points, whereas chiropractic was defined as a system of therapy that uses manipulation to adjusts the spine and other body parts to "promote normal nerve functions". Massage was described as the systematic rubbing and manipulation of muscle and other tissues to relieve bodily infirmities, while meditation was defined as a "self-directed practice for relaxing the body and calming the mind". Finally, tai chi was described as a Chinese martial art that uses slow and smooth body movements and is often practiced for its purported health benefits. The survey was pre-tested on a convenience sample of 15 people (both older and younger) in Seattle and 5 people in Boston. Statistical analyses We analyzed the data using the SAS statistical software version 6.12 (SAS Institute, Cary, NC). Descriptive data were characterized using percentages or medians. For each of the five CAM therapies, we performed separate exploratory logistic regressions to identify specific characteristics associated with 1) high degree of knowledge (4 or 5 on a 5-point scale) (five separate models), 2) prior use (for any reason and for back pain) (10 separate models), 3) high expectations of helpfulness for current back pain (7 to 10 on a 0 to 10 scale) (five separate models), 4) greatest likelihood of trying therapy for no additional cost (all five therapies) and for a $10 per visit co-pay (acupuncture, chiropractic, massage only) (eight separate models), and 6) greatest likelihood of participating in each of the two hypothetical clinical trials (two separate models). Thus, a total of 30 separate logistic models were created. For each of the 30 dependent variables, we identified potential predictor variables in advance and evaluated them in preliminary models. In Table 1, the potential predictor variables evaluated in the preliminary models for each of the 28 therapy-specific dependent variables are indicated by an X. In addition, we modeled the likelihood of being "definitely willing" to participate in a hypothetical clinical trial of acupuncture, chiropractic, and massage and of being "definitely willing" to participate in a hypothetical clinical trial of massage, meditation, and t'ai chi. In both models, we evaluated the following 22 variables as potential predictor variables of being "definitely willing" to participate in the hypothetical clinical trial: demographic characteristics (age, gender, race, education, geographic location), prior use of each of the therapies included in the trial (i.e., acupuncture, chiropractic, and massage for one trial and massage, meditation, and t'ai chi for the other trial) for any reason (and for back pain), knowledge of these three included therapies, prior perceived harm from these three included therapies, years since first back pain, symptom bothersomeness, high expectations of each included CAM therapy for current back pain, number of days of back pain in last six months, and medication usage in the week prior to the interview. Table 1 Potential Predictor Variables Evaluated in 28 Therapy-Specific Logistic Regression Models Dependent Variables for Logistic Regressions Potential Predictor Variable High Knowledge of Therapy* Prior Use of Therapy* Prior Use of Therapy for Back Pain* High Expectations of Success of Therapy* Likelihood of Trying Therapy at No Cost* Likelihood of Trying Therapy for $10 Co-pay** Geographic location (Boston vs. Seattle) X¶ X X X X X Age (65+ vs. < 65) X X X X X X Gender (female vs. male) X X X X X X Race (white, non-white) X X X X X X Education (no college vs. some college) X X X X X X ≥ 5 years since first back pain X X X ≥ 90 days of LBP in last 6 mo. X X X High symptom bothersomeness (7 – 10) on a 0 – 10 scale X X X High knowledge of therapy (4 or 5) on a 1 – 5 scale X X X Prior use of therapy X X X Prior use of therapy for back pain X X X High expectations of therapy (7 – 10) on a 0 – 10 scale X X Medication usage in past week X X Prior harm from therapy X X * Separate models were done for each of the five therapies (acupuncture, chiropractic, massage, meditation, t'ai chi) ** Separate models were done for acupuncture, chiropractic, and massage. ¶An X indicates that a particular potential predictor variable was evaluated in a model with the specific dependent variable. Initially, we evaluated potential predictor variables in preliminary models containing five or fewer independent variables. Any independent variable associated with the dependent variable at a p value of 0.15 or less in a preliminary model was a candidate for the appropriate final model. We used a backwards elimination procedure to evaluate candidate predictor variables and to determine the final models [8]. All variables with a p value of 0.01 or less were retained in the final model. Odds ratios (OR) are presented along with 95% confidence intervals (95% CI). Table 4 presents the odds ratios that describe the significant associations (p < 0.01) for each of the 28 therapy – specific dependent variables. Table 4 Predictors of Knowledge of, Experience with, Expectations about, and Willingness to Try Five Complementary and Alternative Medical (CAM) Therapies Odds ratios* (95% CI) for the independent predictor variables used in the final models for each CAM therapy Dependent Variable Acupuncture Chiropractic Massage Meditation T'ai chi High Knowledge of specific therapy (4–5) Tried acupuncture: 43.6 (16.7–113.6) Tried chiropractic: 12.8 (6.2–26.7) Tried massage: 7.6 (4.0 – 14.7) Tried meditation: 11.6 (4.6–29.3) LOGISTIC NOT VALID** Bostonian: 4.8 (1.9–12.3) Previously tried specific therapy No associations Bostonian: 0.5 (0.3 – 0.8) 65+ yrs: 0.4 (0.2 – 0.7) Female: 2.5 (1.3 – 4.8) No associations Previously tried specific therapy for back pain No associations None 65+ yrs: 0.3 (0.2 – 0.6) No associations LOGISTIC NOT VALID** High expectations of specific therapy (7 – 10) 65+ yrs: 0.4(0.2 – 0.8) Knowledge: 2.9 (1.6 – 5.2) 65+ yrs: 0.3 (0.2 – 0.5) No associations No associations Tried acupuncture: 4.3 (2.1 – 9.0) Very likely to try specific therapy for free High expectations: 15.4 (3.6 – 66.1) High expectations: 27.4 (9.5 – 79.3) High expectations: 16.4 (7.4 – 36.5) High expectations: 3.6 (1.7 – 7.7) High expectations: 14.3 (5.4 – 38.3) Tried meditation: 2.4 (1.3 – 4.5) Very likely to try specific therapy for $10 /visit co-pay High expectations: 6.8 (3.0 – 15.5) High expectations: 8.1 (4.2 – 15.7) High expectations: 6.4 (3.5 – 11.4) NOT QUERIED NOT QUERIED Bostonian: 2.3 (1.4 – 4.0) Bostonian: 1.8 (1.001 – 3.2) *These odds ratios describe the significant associations (p < 0.01) for each of the 28 therapy – specific dependent variables. For example, we found that those who had tried acupuncture were 43.6 times more likely to have high knowledge of acupuncture. No other variables were related to high knowledge of acupuncture. ** These logistic regression models did not converge. Categorization for independent variables: Age (<65; 65+) Knowledge of therapy (1–3; 4–5) Gender (M; F) Expectations of therapy (missing through 6; 7+) Geography (Seattle; Boston) Prior Use of therapy (no; yes) Results Characteristics of respondents Most study participants were white, women, and had attended college (Table 2). Most had had back problems for at least five years, had experienced back pain at least 90 days in last six months, had used medications in the prior week, and expected little change in their pain in a year. Table 2 Demographic and Back Pain Characteristics of 249 Survey Respondents Characteristic Percent Location (Boston) 43 Age (< 65) 52 Women 60 White 80 Attended some college 57 At least 5 years since first back pain lasting longer than 2 weeks 60 90+ days of LBP in last 6 mo. 61 High symptom bothersomeness in the past week (≥ 7) on 0 – 10 scale 42 Used medication for LBP in the past week 56 Expect pain to be similar in a year 72 Missing data – last variable has 10 missing values (4% of all observations), 1 variable has 5 (2%), all others have 3 or fewer. Knowledge of, experience with, perceptions of, and willingness to try CAM therapies Except for chiropractic, most participants reported little or no knowledge of these therapies (Table 3). In logistic regressions, prior use of a therapy consistently predicted high knowledge of that therapy (Table 4). Table 3 Knowledge of, Experience with, Expectations about, and Willingness to Try Five CAM Therapies* Acupuncture (N = 249) Chiropractic (N = 249) Massage (N = 249) Meditation (N = 249) T'ai Chi (N = 249) Knowledge about Therapy (%)  1 – 2 (1="no knowledge") 69 44 52 72 91  3 17 22 24 15 6  4 – 5 (5="a lot of knowledge") 14 34 24 13 3 Ever tried therapy (%) 18 54 38 27 8 Ever tried therapy for LBP (%) 11 45 24 7 0.4 Median helpfulness for LBP among prior users (0 to 10 scale) 5 6 7 5 ** Pain or harm reported by prior users (%) 13 23 13 5 16 Median expectation of helpfulness for current LBP (0 to 10 scale) 5 5 7 3 5 Did not provide expectation rating (%) 25 10 9 12 24 High expectations of helpfulness for current LBP (7 to 10 on 0 to 10 scale) (%) 19 28 48 15 16 Very likely to try therapy if primary care provider thought reasonable and no extra cost (%) 64 51 69 27 41 Very likely to try therapy if primary care provider thought reasonable and $10 co-pay (%) 51 42 56 NA NA NA = Not Asked. * Each column refers to a specific therapy and the specific question about the therapy is shown in the first column. ** Only 1 person had tried t'ai chi for low back pain previously. All variables, except expectations of helpfulness of current LBP (where % are given in the table) have missing values for < 5% of respondents. More than half of the participants had tried chiropractic compared with 38% who had tried massage and substantially fewer who had tried the other therapies (Table 3). No demographic characteristics were related consistently to use of these therapies (Table 4). Chiropractic and massage were also the most commonly used of the therapies specifically for low back pain. Users of massage rated treatment helpfulness higher than did users of other therapies (Table 3). Reports of harm or increased pain were highest for chiropractic (23%) and lowest for meditation (5%). Respondents believed that massage would be most helpful for their current back pain (median rating of 7) and that meditation would be least helpful (median rating of 3) (Table 3). One quarter of all respondents were unable to rate their expectation of acupuncture or t'ai chi, compared to about 10% for the other therapies. Respondents 65 years of age or older were less optimistic than younger respondents about the helpfulness of acupuncture and massage (Table 4). High expectations of helpfulness of chiropractic were more common in those with high knowledge of this therapy and high expectations of helpfulness of acupuncture were more common among those who had tried it (Table 4). More than half of the respondents said they would be "very likely" to try acupuncture, chiropractic, or massage if provided by their health plan for no additional cost and their physician felt it was reasonable. Fewer respondents said they would be "very likely" to try meditation training (27%) or t'ai chi (41%) under those circumstances (Table 3). In logistic regression models, the strongest predictors of being very likely to try a particular therapy were high expectations of a therapy and, for meditation, prior use of the therapy (Table 4). About 80% of those very likely to try acupuncture, chiropractic, or massage for no additional cost were also very likely to try it for a $10 per visit co-pay (Table 3). Paralleling the finding for free care, the strongest predictor of willingness to try a therapy for a $10 per visit co-pay was high expectations of success for that therapy. Respondents from Boston were more willing to try acupuncture. Those reporting harm or pain from chiropractic were less willing to try this therapy again. Willingness to participate in a clinical trial More than half of respondents were "definitely willing" to participate in each of two hypothetical clinical trials about which they were asked and less than 5% were definitely unwilling to participate (Table 5). When asked which of the treatments in each trial they would most prefer, respondents preferred massage and acupuncture in the trial of acupuncture, chiropractic, and massage and, in the second trial, strongly preferred massage to meditation. However, a significant fraction (24%) expressed a preference for t'ai chi. We found no demographic, back pain, or CAM characteristics associated with being "definitely willing" to participate in the hypothetical trial of acupuncture, chiropractic, and massage. People who were "definitely willing" to participate in the hypothetical trial of massage, meditation, and t'ai chi were more likely to have high expectations of meditation (OR = 3.1, 95% CI = 1.4 – 7.0). Table 5 Willingness to Participate in Clinical Trials of CAM Therapies for Low Back Pain and Preference for Therapies Percent (N = 249) Definitely willing to participate in clinical trial of acupuncture, chiropractic, massage, and a self-help back pain book (%)* 62 Preferred treatment among above: Massage 43 Acupuncture 35 Chiropractic 18 None or Other 3 Book 1 Definitely willing to participate in clinical trial of massage, meditation, t'ai chi, and a self-help back pain book (%)** 53 Preferred treatment among above: Massage 63 T'ai Chi training 24 Book 5 Meditation training 4 None or Other 4 Missing values – < 4% of responses for each variable are missing. *Your healthplan is thinking about conducting a study evaluating several treatments for people with chronic low back pain. In this study, participants would have a one in four chance of being assigned to one of the following treatments: acupuncture, chiropractic, massage, or a book designed to help patients better understand their low back pain. Participants would be expected to try the treatment they were assigned to at least once. Participants would still retain access to their usual care and participation in this study would be free. If you were asked to take part in a study like this would you be willing to participate? ** Same question was asked, but the treatments were massage, meditation training, and t'ai chi training. Discussion Our findings suggest that many patients would be willing to try specific CAM therapies for back pain, especially if they had high expectations for their helpfulness. Interestingly, we found no consistent relationships between high expectations for a particular therapy and either previous use of that therapy or high self-perceived knowledge of that therapy. Our findings regarding knowledge, previous use, and expectations for these therapies were largely similar for Seattle and Boston and for older and younger adults. However, those over 65 years old were less likely to have high expectations of acupuncture and massage and to have tried massage previously. Since we conducted the study in two metropolitan areas where CAM use is fairly common, our results might not represent the CAM views of patients with back pain in more rural areas or in other regions of the country. Another limitation of our study was that 30% of people we attempted to contact could not be assessed for eligibility, leading to the possibility of a high non-response rate. Because we have almost no information on the characteristics of the individuals with unknown eligibility, we do not know if they differ from those included in the study, and cannot adequately estimate the magnitude and direction of potential biases regarding interest in CAM that might exist in our sample. However, the fractions of individuals who were unable to be assessed for eligibility were similar among those less than 65 years of age and those 65 and older in each metropolitan area (45% vs. 40% in Boston, respectively; 20% vs. 20% in Seattle). Respondents showed a clear preference for receiving hands-on treatments delivered by a practitioner compared to attending classes that teach self-care techniques. Whether this reflects a preference for provider-oriented, more passive, therapies or the belief that classes teaching these specific self-care therapies would be less effective is not clear. Unfortunately, our interview did not include questions about yoga, which has recently received more popular press than meditation or t'ai chi as a self-care therapy for back pain [9,10]. Survey respondents were not enthusiastic about "meditation training" as a treatment for back pain. Relatively few of those who indicated prior use of meditation for physical or mental health problems had used the forms of meditation most commonly taught in a medical setting (e.g., mindfulness meditation). Consequently, studies recruiting patients to participate in interventions including meditation training may need to carefully describe the treatment in terms of a concrete goal (e.g., stress reduction). There is still relatively little knowledge about and experience with acupuncture and t'ai chi even in Boston and Seattle where use of CAM therapies is generally high. In fact, about one – quarter of respondents were unable to provide an expectation of the helpfulness of acupuncture or t'ai chi. Nevertheless, substantial fractions of participants were willing to try acupuncture and t'ai chi as a treatment if their primary care provider thought it reasonable, and in the case of acupuncture, even if they had to pay a $10 co-pay each visit. Our finding that people in our sample reported being almost as willing to try acupuncture as massage, despite less knowledge of, expectations about and experience with it, is intriguing and requires further inquiry. Although participants in this study reported more knowledge of and experience with chiropractic, they were more enthusiastic about massage. A recent survey [11]of 46,000 Consumer Reports subscribers found that among those who had experienced back pain, the relatively few who had tried deep tissue massage rated it more favorably than those who had tried medications or physical therapy. The use of massage in this country has been growing steadily since the 1960's, with the largest increases in the 1990's [12]. In fact, in surveys of CAM use in the US population conducted in 1990 and 1997, Eisenberg et al. [7] found that massage as a treatment for various medical conditions had increased 61% over the seven-year period, while chiropractic remained fairly stable. By 1997, the estimated percentage of US adults who had used chiropractic was similar to that who had used massage, 11%. The relative popularity of massage may result from the more positive experiences of those who have tried it compared with chiropractic or acupuncture, and higher expectations that massage would be helpful for their current pain. Moreover, chiropractic users were more likely to report treatment related "harm" or "pain" than were users of massage. Implications for clinical trials Most survey respondents indicated they were "very willing" to participate in our two hypothetical clinical trials evaluating different CAM treatments for chronic back pain. Massage was the preferred treatment in both trials, but more than one in five survey respondents stated a preference for acupuncture and t'ai chi. In view of the long-standing popularity of chiropractic, surprisingly few respondents reported chiropractic as their top choice. Nonetheless the finding that massage was substantially more popular than chiropractic mirrors the results among acute low back pain patients in a clinical trial who were randomized to a choice of acupuncture, chiropractic, massage, or usual care or to usual care alone [13]. In that study, 52% of the participants said they would choose massage if given a choice, compared with only 24% who said they would choose chiropractic if given a choice. This finding could reflect the fact that many people have access to chiropractic as part of their current health care coverage [14]. Despite low levels of knowledge about t'ai chi and acupuncture, the finding that over 40% of respondents indicated they were very likely to try these therapies suggests that recruiting enough subjects for clinical trials involving these therapies may be feasible if moderate to large patient populations are available. Recruiting patients for meditation trials, however, is likely to be difficult. Consequently, when we recruited patients for a pilot trial that included a stress reduction intervention based on the principles of mindfulness meditation, we chose to describe it as "Mindfulness Based Stress Reduction" rather than mindfulness meditation. We believe that clinical trials evaluating obviously different treatments for chronic low back pain, such as massage and meditation, may have problems retaining subjects who do not receive the treatment (e.g., massage) that attracted them to the study. This problem may be exacerbated if patients have an exceptionally strong preference (or dislike) for one treatment. Inclusion of multiple CAM modalities in a single study risks tempting potential participants to sign up for the study in the hope of receiving a desired treatment, and then dropping out if they receive a different treatment. In addition, if one treatment is vastly more popular than another, it could be difficult to disentangle the effects of patient expectations and treatment efficacy per se, leading to difficulties in interpreting positive study outcomes. This problem is compounded by concerns about the subjective nature of back pain outcomes, the difficulty in masking participants to study treatment, and the strong skepticism of some researchers that CAM treatments can be effective, even when results are impressive. Masking patients to treatment is quite difficult in studies of many types of conventional as well as CAM treatments if the treatments involve a physical modality, such as massage, or active participation of the patient in the treatment, as in t'ai chi. In such circumstances, using masked outcomes assessors is important to minimize bias. We also suggest that patient (and provider) expectations for treatment and prior experience with each treatment, be measured and, if appropriate, controlled for in the analyses. Finally, if a particular therapy is shown effective in clinical trials in different populations, mechanistic studies will be important for determining how these therapies achieve their effects. Such studies are especially important to convince skeptics that CAM therapies actually have specific effects. In the meantime, the high and rising public interest in CAM therapies, especially for musculoskeletal conditions [12], highlights the importance of evaluating the effectiveness of various CAM treatments for back pain and our findings suggest that recruiting for these efforts may not be difficult. Conclusions Most patients in our sample were interested in trying options for treating chronic back pain that lie outside the conventional medical spectrum, even within the context of a clinical trial. This was true even among patients who had relatively little knowledge of or experience with the therapy. Given our limited knowledge about the effectiveness of most CAM therapies, there is a clear need for additional studies evaluating their effectiveness. Fortunately, our results suggest that researchers will not find it difficult to recruit patients interested in participating in clinical trials of many of the CAM therapies. Competing interests None declared. Authors' contributions KJS participated in the development of the questionnaire and took primary responsibility for the analysis of the data and for drafting the manuscript. DCC was the PI on one of the grants funding the study, participated in the development of the questionnaire and the analysis of the data and played a major role in drafting the manuscript. MTC participated in the development of the questionnaire and the analysis of the data. JE and JBS coordinated the project and oversaw the data collection. RBD participated in the analysis of the data and provided statistical oversight. DME was the Principal Investigator on one of the grants funding the study, participated in the development of the questionnaire and the analysis of the data. All authors read and approved the manuscript. Pre-publication history The pre-publication history for this paper can be accessed here: Acknowledgements This project was supported by grants AT00606 and AT00622 from the National Center for Complementary and Alternative Medicine. We thank the following people for their contribution to the successful completion of this study: Claire Canning, Kristin Delaney, John Ewing, Amy Fields, Christel Kratohvil, and Rene Talenti. ==== Refs Sternbach RA Survey of Pain in the United States: The Nuprin Pain Report Clin J Pain 1986 2 49 53 Frymoyer JW Back pain and sciatica N Engl J Med 1988 318 291 300 2961994 [Consumers Reports] How is your doctor treating you? Consumers Reports 1995 81 8 Cherkin DC MacCornack FA Patient evaluations of low back pain care from family physicians and chiropractors West J Med 1989 150 351 5 2525303 Greenfield S Anderson H Winickoff RN Morgan A Komaroff AL Nurse-protocol management of low back pain. Outcomes, patient satisfaction and efficiency of primary care West J Med 1975 123 350 9 128907 Overman SS Larson JW Dickstein DA Rockey PH Physical therapy care for low back pain. Monitored program of first-contact nonphysician care Phys Ther 1988 68 199 207 2963349 Eisenberg DM Davis RB Ettner SL Appel S Wilkey S Van Rompay M Kessler RC Trends in alternative medicine use in the United States, 1990–1997: results of a follow-up national survey JAMA 1998 280 1569 75 9820257 10.1001/jama.280.18.1569 Kleinbaum D Kupper L Muller K Nizam A Applied Regression Analysis and Other Multivariable Methods 1998 Pacific Grove, CA: Duxbury Press; Corliss R The power of yoga Time 2001 157 54 63 11330024 Parker – Pope T Market Stress? Try Yoga, it might also relieve your asthma, ailing back Wall Street Journal July 23, 2002 [Consumers Reports] The mainstreaming of alternative medicine Consumers Reports 2000 17 25 Kessler RC Davis RB Foster DF Van Rompay MI Walters EE Wilkey SA Kaptchuk TJ Eisenberg DM Long-term trends in the use of complementary and alternative medical therapies in the United States Ann Intern Med 2001 135 262 268 11511141 Connelly MT Hrbek A Post D Davis RB Canning C Phillips R Comparison of patient and provider perceptions of back pain severity, likelihood of improvement, and treatment preferences J Gen Intern Med 2001 Suppl 16 123 124 Kaptchuk TJ Chiropractic: Origins, Controversies, and Contributions Arch Intern Med 1998 158 2215 2224 9818801 10.1001/archinte.158.20.2215

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BMC Complement Altern Med

10.1186/1472-6882-4-9

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==== Front BMC Clin PatholBMC Clinical Pathology1472-6890BioMed Central London 1472-6890-4-21527474310.1186/1472-6890-4-2Research ArticleGene deletion of P-Selectin and ICAM-1 does not inhibit neutrophil infiltration into peritoneal cavity following cecal ligation-puncture Crockett Elahé T 1ecrocket@msu.eduRemelius Crystal 1remelius@cfl.rr.comHess Karen 1hesskare@msu.eduAl-Ghawi Hayma 1haghaw01@gwise.louisville.edu1 Departments of Physiology, College of Human Medicine, Michigan State University, East Lansing, MI, USA2004 26 7 2004 4 2 2 13 11 2003 26 7 2004 Copyright © 2004 Crockett et al; licensee BioMed Central Ltd.2004Crockett et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background Neutrophil infiltration is one of the critical cellular components of an inflammatory response during peritonitis. The adhesion molecules, P-selectin and intercellular adhesion molecule (ICAM)-1, mediate neutrophil-endothelial cell interactions and the subsequent neutrophil transendothelial migration during the inflammatory response. Despite very strong preclinical data, recent clinical trials failed to show a protective effect of anti-adhesion therapy, suggesting that the length of injury might be a critical factor in neutrophil infiltration. Therefore, the objective of this study was to determine the role of P-selectin and ICAM-1 in neutrophil infiltration into the peritoneal cavity during early and late phases of peritonitis. Methods Peritonitis was induced in both male wild-type and P-selectin/ICAM-1 double deficient (P/I null) mice by cecal ligation-puncture (CLP). Peripheral blood and peritoneal lavage were collected at 6 and 24 hours after CLP. The total leukocyte and neutrophil contents were determined, and neutrophils were identified with the aid of in situ immunohistochemical staining. Comparisons between groups were made by applying ANOVA and student t-test analysis. Results CLP induced a severe inflammatory response associated with a significant leukopenia in both wild-type and P/I null mice. Additionally, CLP caused a significant neutrophil infiltration into the peritoneal cavity that was detected in both groups of mice. However, neutrophil infiltration in the P/I null mice at 6 hours of CLP was significantly lower than the corresponding wild-type mice, which reached a similar magnitude at 24 hours of CLP. In contrast, in peritonitis induced by intraperitoneal inoculation of 2% glycogen, no significant difference in neutrophil infiltration was observed between the P/I null and wild-type mice at 6 hours of peritonitis. Conclusions The data suggest that alternative adhesion pathway(s) independent of P-selectin and ICAM-1 can participate in neutrophil migration during peritonitis and that the mode of stimuli and duration of the injury modulate the neutrophil infiltration. peritonitissepsistransgenic miceadhesion molecules ==== Body Background Sepsis is a common cause of morbidity and mortality following surgery or trauma, and is characterized by activation of a systemic inflammatory response, severe hypotension, and major damage to multiple organs [1]. Although neutrophil migration into the tissue sites is crucial for effective elimination of infection, it also plays an important role in inflammatory tissue injury. The selectins, β2 integrins (i.e., CD18: Mac-1, LFA-1) and members of the immunoglobulin gene superfamily adhesion molecules, such as ICAM-1, play a significant role in neutrophil adhesion and transendothelial migration [2-4]. The expression and activation of these adhesion molecules on neutrophils and the endothelium, as well as the presence of a chemotactic gradient (eg. chemokines) appear to be important factors in neutrophil transmigration [3]. The selectins mediate neutrophil rolling while the β-2 integrins are important for firm adhesion and transendothelial migration [2-5]. The selectin family consists of three closely related cell surface molecules with differential expression by leukocytes (L-selectin), platelets (P-selectin), and vascular endothelium (P-selectin and E-selectin) [6]. ICAM-1 is one of the major ligands that binds to β-2 integrins (i.e., Mac-1 LFA-1) and is involved in neutrophil firm adhesion to endothelial and transendothelial migration [3]. ICAM-1 is constitutively expressed at a low concentration; however, under inflammatory conditions it is highly inducible in many cell types [7]. In vivostudies have shown that administration of small molecule ligands, and/or neutralizing antibodies to the selectins, ICAM-1 or β2-integrins can protect tissues from injury following endotoxin exposure, bacterial infection, or ischemia [8-10]. However, blocking reagents have the potential to stimulate or inhibit other receptors thus confounding the results. For example, a study by Kyriakides et al. has shown that soluble P-selectin attenuated skeletal muscle reperfusion injury by inhibition of the classical complement pathway [11]. Genetically altered mice deficient in adhesion molecules have been developed, which provide an alternative approach to study the role of the adhesion molecules in neutrophil recruitment and tissue injury. Recent studies using the transgenic mice have shown results indicating that neutrophils can use different adhesion pathways to emigrate from the systemic vasculature into the tissues and that the inflammatory responses may be site specific and stimulus dependent. For example, Mizgerd et al. have demonstrated a significant reduction in neutrophil infiltration into the peritoneal cavity at 4 hours of streptoccocal peritonitis in ICAM-1 mutant mice [8]. Another study by Kamochi et al. has shown that P-selectin and ICAM-1 significantly contributed to liver and lung injury at 4 hours of systemic endotoxemia in ICAM-1 and P-selectin/ICAM-1 double mutant mice [12]. Further, Bullard et al. have shown that P-selectin and ICAM-1 double mutant mice exhibited complete loss of neutrophil migration into the peritoneum during S. pneumoniae-induced peritonitis [13]. In contrast to these studies, Serman et al. have shown no differences in survival between wild type and ICAM-1-deficient mice following an intra-peritoneal injection with E. coli, S. auerus, or P. aeruginosa [14]. More importantly, recent clinical trials of anti-adhesion therapy in an attempt to reduce injury associated with traumatic shock and reperfusion injury failed to show a significant benefit despite strong preclinical data [15]. In an attempt to understand the disparity between the preclinical and clinical trial studies, it was noted that the lengths of injury in the clinical setting were longer than those of the preclinical studies. It appears that the underlying mechanism of neutrophil infiltration with a short period of insult is different from those of injury associated with a longer period of insult [15]. Additionally, adhesion-dependent and -independent neutrophil activation and migration can differentially be regulated by target tissue and mode of stimuli. Therefore, the goal of the study presented here was to investigate the role of ICAM-1 and P-selectin in peritonitis induced by CLP under a short and longer period of injury. The model of CLP-induced peritonitis used in this study is a clinically relevant model of sepsis [16]. This model was chosen to simulate the critical polymicrobial bacteremia-induced tissue injury that occurs in septic patients. The data of this study suggest that neutrophil infiltration into the peritoneal cavity following CLP can utilize an ICAM-1 and P-selectin independent pathway. Methods All chemicals were purchased from Sigma Chemical (St. Louis, MO), unless otherwise noted. Animals Only adult male mice (i.e., 8–10 wk) were used in this study. All animals received humane care in compliance with the Guide for the Care and Use of Laboratory Animals (National Institutes of Health Publication No. 85-23, revised 1985). Experimental protocols were reviewed and approved by the Michigan State University Animal Use and Care Committee. Gene-targeted double mutant mice deficient in P-selectin and ICAM-1 (P/I double mutant), C57BL/6-Icam1tm1BaySelptm1Bay, backcrossed to C57BL/6, were used in this study. Breeding pairs of double-knockout mice were purchased directly from Jackson Laboratory (Bar Harbor, ME) and bred under the guidance of University Laboratory Animal Resources at Michigan State University. The wild-type (WT) mice were male C57BL/6, which were acclimated to the animal laboratory environment for one week before the start of experimentation. Before and after surgery, all the animals had unlimited access to food and water. Induction of peritonitis Experimental model of polymicrobial sepsis Polymicrobial sepsis was induced by CLP as previously described by Chaudry, et al. [16]. Surgical utensils were sterilized and all experimental procedures were performed under aseptic conditions. Adult male mice weighing 23 to 28 gm were anesthetized with inhaled methoxyflurane (Baxter Caribe Inc., Guayama, PR). The abdominal hair was shaved, the skin was cleaned with 75% ethanol using a sterile gauze and scrubbed with betadine solution. After drying, a 2-cm midline incision was made, the cecum was identified and ligated below the ileocecal valve using 0–5 silk suture with care being taken not to occlude the cecal valves. The cecum was punctured on both sides with a 21 G needle and gently squeezed to extrude a small amount of fecal material. The cecum was then restored to its normal position and the abdomen was closed in two layers using 5.0 nylon suture. Sham animals underwent the same procedures excluding ligation and puncture of the cecum. Experimental model of peritonitis induced by 2% glycogen Adult male mice (i.e., 8–10 wk) were lightly anesthetized by inhalation anesthesia with methoxyflurane. A volume of 2% sterile glycogen solution, equal to 10% of body weight, was injected intraperitoneally (i.p.). Six hours after glycogen inoculation, mice were euthanized and peritoneal lavage and blood samples were collected. The collected samples were identified with ID numbers to assure a blind fashion performance of the tests and data analysis. Total leukocyte and differential counts were performed as described below. Peripheral blood and tissue procurement Blood samples were obtained from the right ventricle via a left anterior thoracotomy at the time of sacrifice, using a sterile heparinized syringe containing 50 μl of heparin (100 USP Units/ml). Blood smears were prepared and stained with Wright-stain (LeukoStat, Fisher Scientific, Pittsburgh, PA) for differential cell counts. The total number of peripheral blood leukocytes was determined by lysing the red blood cells using 3% acetic acid solution with the aid of a Neubauer hemocytometer. The remaining blood was centrifuged, and plasma was collected and stored at -70°C. A portion of the liver was fixed in buffered 10% formalin and embedded in paraffin, and a second portion was snap frozen in liquid nitrogen and stored at -70°C until used for immunohistochemistry staining. Collection of peritoneal lavage fluid The peritoneal fluids were collected using repetitive (2 times) instillation and withdrawal of 2 and 5 ml respectively of sterile saline solution using a syringe with a 22 G needle. The peritoneal lavage sample was placed on ice, immediately processed for centrifugation at 4°C, and the supernatant and the cell pellet were collected separately. The cell pellet was used for total and differential cell counts. Differential cell counts were determined on cytospin preparations of peritoneal lavage stained with Wright-stain (LeukoStat). The total number of peritoneal leukocytes was determined as described above for the peripheral blood leukocyte count. Additionally, the presence of neutrophils in peritoneal lavage was confirmed by immunohistochemical staining of cytospin preparation using a primary antibody (IgG2a) specific to mouse neutrophil as described below. Further, the neutrophil content was quantified by measuring the myeloperoxidase (MPO) level of peritoneal lavage as described below. Demonstration of neutrophil recruitment by myeloperoxidase assay The MPO contents of the peritoneal lavage supernatant and the cell pellet were quantified as previously published by our laboratory [17]. Briefly, the peritoneal cell pellet was resuspended in a potassium phosphate buffer, froze at -70°C, thawed, and sonicated for 40 seconds for two cycles (Ultrasonic Convertor, Model CL4, Misonix, Farmingdale, NY). The sample was then incubated at 60°C for 2 hours followed by centrifugation at 10,000 rpm for 5 minutes at 4°C. The supernatant was collected and used for the MPO assay. The MPO activity was determined using a tetramethylbenzidine substrate kit (ImmunoPure, Pierce, Rockford, IL) and read at 450 nm using a human leukocyte MPO as the standard. One unit of MPO activity was defined as the quantity of enzyme degrading 1 μmol peroxide/minute at 25°C. Similarly, the MPO content of peritoneal supernatant was measured. Determination of neutrophil infiltration and ICAM-1 expression by Immunohistochemistry To confirm the identity of neutrophils in peritoneal lavage, immunohistochemical staining was performed using acetone-fixed cytospin cell preps. The primary antibody (clone 7/4, IgG2a) specific to mouse neutrophil (Cedarlane, Westbury, NY), the biotin-conjugated secondary antibody (PharMingen, San Diego, CA), and a Vectastain avidin-biotin complex reagent and 3,3'-diaminobenzidine chromogen kits (Vector Laboratories, Inc., Burlingame, CA) were used as previously described in detail [17]. The expression of ICAM-1 on endothelial cells was examined using acetone-fixed cryosections of the tissue. The liver was used in this study. Similarly, ICAM-1 expression was identified using a specific monoclonal antibody to mouse ICAM-1 (3E2 clone, PharmMingen, San Diego, CA) and a biotin-conjugated secondary antibody. Tissue sections were counter stained with hematoxylin (Gill's formula, Vector Laboratories) and mounted with DAKO Mounting Media (DAKO Corp, Carpinteria, CA). The samples were examined using a Nikon light microscope interfaced with a spot 24-Bit Digital Color Camera. Statistical analysis All data were expressed as means ± standard error of the mean. Comparisons between two groups were performed using an unpaired t-test by way of StatView version 5.0.1 software© for Windows. Comparisons between multiple groups and various time points were analyzed using ANOVA with subsequent Fisher's PLSD test. P ≤ 0.05 was considered significant. Results Verification of ICAM-1 and P-selectin deficiency in P/I null mice The Jackson Laboratory, where the P/I null breeding pairs were purchased, had initially tested the double knockout of the P/I null mice. In addition, the ICAM-1/P-selectin deficiency was confirmed in our laboratory in randomly selected litter mice tissue samples using RT-PCR and immunohistochemical staining of the liver tissue, as previously published by our laboratory (18). The ICAM-1 expression was determined in all the animals used in this study. Figure 1 shows ICAM-1 expression in liver tissues from the wild-type and P/I null mice by immunohistochemical staining technique. The ICAM-1 expression was constitutively present in wild-type control mice as indicated by light brown staining along the endothelium of the central vein, sinusoids, and portal vasculature (Figure 1, WT CT). The ICAM-1 expression was markedly increased in wild-type mice following CLP and continued to be evident at 24 hours of CLP (Figure 1, WT 6 h and WT 24 h). In contrast, ICAM-1 expression was absent in the tissues of P/I null mice before and after CLP treatment (Figure 1, P/I CT, 6 h and 24 h). The intestinal tissue ICAM-1 expression has also been examined, which was similar to that of the liver tissue. However, liver, due to its large endothelial cell content, serves as an excellent tissue source for ICAM-1 expression. For this reason, liver is routinely used in our studies to confirm the ICAM-1 expression. Figure 1 Immunostaining of ICAM-1 expression in WT and P/I null mice. Tissues ICAM-1 expression was determined by staining the liver sections with an anti-ICAM-1 antibody specific to mouse by applying the immunoperoxidase technique, and examined under a light NIKON microscope. The top row represents wild-type (WT) control (CT), CLP 6 h and CLP 24 h, respectively. Note the increased intensity of ICAM-1 staining of central veins (arrow heads) and sinusoids (arrows) with progression of sepsis. In contrast, ICAM-1 expression in P/I null mice liver sections was completely absent in controls, 6 h after CLP and 24 h after CLP (lower row). Control group represents mice that were not subjected to sham or CLP experimental treatment. Clinical signs of sepsis Clinical signs of sepsis were manifested as quietness, lack of response to stimulus, absence of socializing behavior, ruffled hair coat and lack of appetite. All mice subjected to CLP displayed these signs that became significant at 24 hours of CLP, and no striking differences were observed between the wild-type and P/I null mice. Effect of sepsis on leukocyte count in wild-type and P/I null mice Peripheral blood leukocytes To establish the blood cell parameters under normal physiological conditions in wild-type and P/I null mice, peripheral blood samples were collected from randomly selected mice. In this article these mice are denoted as "Control", which were not subjected to the sham or CLP operation. The leukocyte and differential counts of peripheral blood were measured. As shown in Table 1, the circulating leukocyte counts were not different between the wild-type and P/I null mice. However, the P/I null mice showed a significantly higher number of neutrophils and lower lymphocytes when compared to their wild-type counterparts (Table 1). There was no significant difference in monocyte count between the wild-type and P/I null mice. Table 1 Leukocyte and differential counts in WT and P/I null mice. Randomly selected normal mice not subjected to the sham or CLP treatment, were anesthetized and the peripheral blood and peritoneal lavage collected for leukocyte content and differential analysis. Data are expressed as mean ± SEM. Total leukocytes for peripheral blood represents the absolute number of cells X 106/ ml and for peritoneal lavage represent the absolute number of cells X 106/ lavage. The values in parenthesis denote absolute number of the cells X 106. * p ≤ 0.05 absolute number of cells of the wild-type compared to respective P/I null mice. n represents the number of mice per each group. Source Total Leukocytes (× 106) Differential (%) % Neutrophils % Lymphocytes % Monocytes Peripheral blood  WT (n = 4) 10.4 ± 1.5 26 ± 2 (2.9 ± 0.5) * 72 ± 3 (7.2 ± 0.6) * 2 ± 1 (0.3 ± 0.1)  P/I null (n = 5) 10.3 ± 1.4 69 ± 7 (6.8 ± 0.9) 32 ± 6 (3.4 ± 0.5) 2 ± 1 (0.2 ± 0.1) Peritoneal Lavage  WT (n = 6) 3.8 ± 0.9 16 ± 1 (0.6 ± 0.2) 19 ± 3 (0.8 ± 0.3) 65 ± 5 (2.4 ± 0.7)  P/I null (n = 6) 3.6 ± 1.2 3 ± 1 (0.2 ± 0.1) 54 ± 5 (1.9 ± 0.4) 43 ± 6 (1.5 ± 0.7) The induction of CLP-induced peritonitis resulted in a significant leukopenia in wild-type as well as P/I null mice as compared to their control counterparts (Table 2). It is interesting to note that although not statistically significant, leukopenia in the P/I null mice was less severe than those of the corresponding wild-type counterparts. This difference was mainly reflected by the presence of a higher number of neutrophils in the P/I null mice blood (Table 2). Similarly, CLP induced a significant neutropenia in both wild-type and P/I null mice when compared to the respective control mice. The most severe neutropenia occurred in the wild-type mice at 24 hours of CLP. In our studies peritonitis was also induced in response to 2% glycogen, which served as a positive control stimuli to induce an acute peritonitis as have previously been reported by many other investigators. As shown in Table 2, both wild-type and P/I null mice presented significant leukopenia at 6 hours of i.p. inoculation of 2% glycogen. Further, the inflammatory response to the sham operation, which elicited a trauma-induced peritonitis, caused leukopenia in both wild-type and P/I null mice. As shown in Table 2, there was a significant drop in the circulating blood leukocytes at 6 and 24 hours after the sham operation when compared to the respective control mice. However, a significant neutropenia was only present at 24 hours of the sham operation. Table 2 Peripheral blood leukocyte and neutrophil counts in WT and P/I null mice subjected to CLP and 2% glycogen-induced peritonitis. Control group represents normal mice that were not subjected to sham or peritonitis treatment. Sham (CLP) represents the CLP respective sham group. Data are expressed as mean ± SEM, representing the absolute number of cells X 106. * p ≤ 0.05 compared to respective control group; # p ≤ 0.05 wild-type compared to P/I null mice at the same time point and treatment. n represents the number of mice per each group. Experimental design WT mice Total Leukocytes (× 106 /mL) P/I null mice Total Leukocytes (× 106 /mL) WT mice Neutrophils (× 106 /mL) P/I null mice Neutrophils (× 106 /mL) Control (n = 4) 10.1 ± 1.3 10.3 ± 2.1 2.8 ± 0.7 # 6.7 ± 1.3 Sham (CLP) 6 hr (n = 4) 3.6 ± 0.6 * 4.5 ± 0.3 * 2.2 ± 0.1 # 3.8 ± 0.5 Sham (CLP) 24 hr (n = 6) 2.9 ± 0.7 * 4.4 ± 0.8 * 1.4 ± 0.3 * 2.3 ± 0.1 * CLP 6 hr (n = 6) 2.0 ± 0.4 * 3.4 ± 0.9 * 1.2 ± 0.3 * 2.8 ± 0.9 * CLP 24 hr (n = 6) 1.1 ± 0.3 * 3.8 ± 1.1 * 0.6 ± 0.2 * 2.8 ± 0.8 * 2% Glycogen 6 hr (n = 4) 3.4 ± 0.1 * 4.4 ± 0.8 * 2.5 ± 0.1 3.6± 0.6 Peritoneal leukocytes Similar to peripheral blood, the cell parameters of peritoneal fluid under normal physiological conditions in the wild-type and P/I null mice were determined in randomly selected mice. The mice were not subjected to the sham or CLP operation. As Table 1 shows, no significant difference was found in total peritoneal leukocyte counts between the wild-type and P/I null groups (i.e., WT = 3.8 ± 0.9 × 106 vs. P/I = 3.6 ± 1.2 × 106). However, it is interesting to note that monocytes/macrophages were the predominant cell type present in the peritoneal cavities of the wild-type mice, whereas in the P/I null mice lymphocytes were the predominant cell type (Table 1). Neutrophils constituted a smaller percentage of the peritoneal leukocytes in both the wild-type and P/I null mice (Table 1). Although the P/I null mice peritoneal lavage presented a lower percentage of neutrophils than those of the wild-type counterparts, the differences between the absolute numbers of neutrophil counts did not reach statistically significance (i.e., p = 0.08). Sepsis induced by CLP (i.e., 6 and 24 hr) caused a significant leukocyte infiltration into the peritoneal cavities of both wild-type and P/I null mice when compared to their corresponding sham group (Figure 2A). The peritoneal leukocyte influx consisted predominantly of neutrophils as identified by Wright staining as well as in situ immunohistochemical staining using specific monoclonal antibody to mouse neutrophil (Figure 3). As shown in Figure 2B, a significantly greater number of neutrophils infiltrated into the peritoneal cavities of wild-type mice than those of the P/I null mice at 6 hours after CLP, which reached to comparable levels at 24 hours of CLP. Although a fewer number of neutrophils were present in the peritoneal cavities of P/I null mice, the ratio of neutrophil infiltration (i.e. ratio = infiltrated peritoneal neutrophils in response to CLP/neutrophils normally present in peritoneal cavity of the control mouse) was significantly higher in the P/I null mice than those of wild-type mice. There was a 16-fold and a 33-fold increase in the ratio of peritoneal neutrophils in wild-type at 6 and 24 hours after CLP, respectively. However, in P/I null mice, the peritoneal neutrophil infiltration ratio increased 54-fold and 204-fold at 6 and 24 hours after CLP, respectively. Figure 2 Total peritoneal leukocyte and neutrophil counts in WT and P/I null mice subjected to CLP or 2% glycogen-induced peritonitis. Wild-type (WT) and P/I null were subjected either to no treatment (Control), sham (Sham CLP), CLP, or 2% glycogen. The mice were then euthanized at 6, and 24 hours of treatment, peritoneal lavages were collected and analyzed for leukocyte and neutrophil contents. Data are expressed as mean ± SEM, representing the absolute number of cells X 106 per each lavage. Significant differences existed between sham, CLP and 2% glycogen as compared to their respective control group (* p < 0.05), and as P/I null mice compared to respective wild-type at the same time period and treatment (# p ≤ 0.05). Data from six independent experiments with total sample size of 4 mice per each control and 2% glycogen group, 6 to 8 mice per each sham and 8 to 11 mice per each CLP treatment group. Figure 3 Staining of cytospin preparations from peritoneal lavage. The top three rows show the Wright staining of the cellular components of peritoneal lavages. Cellular preps from the control (CT) mice of both WT and P/I null groups demonstrating mononuclear cells as the predominant cell types (left column: WT CT, P/I CT). Control group represents mice that were not subjected to sham or CLP experimental procedures. CLP induced a significant neutrophil infiltration (arrows) at 6 and 24 hours in both WT (top row: WT 6 h, WT 24 h) and P/I null mice (second row: P/I 6 h, P/I 24 h). Neutrophils were also the predominant cell type at 6 hours of 2% glycogen-induced peritonitis in WT and P/I null mice (third row: WT 6 h, P/I 6 h). The lower row represents immunoperoxidase staining of the cells (CLP mice) using an anti-neutrophil antibody specific to mouse, verifying the neutrophils as stained in brown color (WT 6 h, P/I 6 h). Peritonitis was also examined in response to 2% glycogen. A significant leukocyte infiltration into the peritoneal cavity occurred in both wild-type and P/I groups at 6 hours after 2% glycogen injection (Figure 2A). Similar to the CLP response, the leukocyte influx into the peritoneal cavities in response to glycogen consisted predominantly of neutrophils (Figures 2B, 3). Further, sham operation caused a significant leukocyte infiltration into the peritoneal cavity of both wild-type and P/I null mice at 24 hours (Figures 2A, and 2B). Similarly, this peritoneal leukocyte influx consisted predominantly of neutrophils. Demonstration of peritoneal neutrophil recruitment by myeloperoxidase assay To further quantify the degree of neutrophil infiltration into the peritoneal cavity, the MPO levels of both the peritoneal lavage cell pellets and supernatants were measured. Although the MPO levels of the cell pellets indicated the presence of a significant number of neutrophils in the peritoneal cavity after CLP, the MPO values did not always correlate with the absolute number of infiltrated neutrophils. The Wright's staining of cytospin preparations of the peritoneal cells demonstrated highly activated phagocytes with vacuolized cytoplasm often containing numerous intracellular bacteria and in most cases with loss of cellular integrity (Figure 3). Thus, it was of concern to find out whether the MPO contents of neutrophils were released into the extracellular environment due to activation and loss of cellular integrity. To accomplish this objective, the MPO levels of the peritoneal lavage supernatants were also measured. As figure 4B shows, at 6 hours of CLP, significant levels of MPO were detected in the peritoneal lavage supernatants of both P/I null mice and wild-type animals when compared to those of the control mice. At 24 hours of CLP, further increases of MPO levels were present in the peritoneal supernatants of both mice groups. It is interesting to note that P/I null mice demonstrated a higher MPO levels in their peritoneal lavage supernatants than the wild-type counterparts. This increase may reflect a greater degree of neutrophils activation and/or loss of cell membrane integrity of the P/I null mice, and thereby the release of their MPO into the supernatant. The differences were not statistically significant. Figure 4 Neutrophil infiltration as determined by MPO contents of peritoneal cell pellet and peritoneal supernatant. Wild-type (WT) and P/I null were subjected to CLP, euthanized at specific time points, the peritoneal lavages harvested, centrifuged, and the supernatant and the cell pellet were collected separately and assayed for MPO contents. (A) Peritoneal lavage cell pellet. (B) Peritoneal lavage supernatant. Note that at 6 h after CLP, although a significant neutrophil infiltration into the peritoneal cavity of the P/I null group is present, it is significantly impaired compared to the corresponding WT group. Values are expressed as the mean ± SEM. * p < 0.05 compared to respective control group. + p ≤ 0.05 P/I null mice compared to respective wild-type at the same time period of CLP. Data from 6 independent experiments with total sample size of 8 mice per each treatment. Demonstration of neutrophil recruitment by immunohistochemistry Previous studies have indicated that tissue MPO activity can be affected by other factors (19, 20). and that MPO values may not indicate the true presence of neutrophils. Additionally, recent studies have identified MPO as the cellular component of macrophages (i.e., Kupffer cells) (21), as well as histiocytes (22). Therefore, an immunohistochemical staining technique was used to confirm the presence of neutrophils in the peritoneal cavity. The cytospin preparations of the peritoneal lavages were immunostained with a specific antibody to mouse neutrophil. Figure 3 (lower row) shows the Immunostaining of the peritoneal lavages obtained from wild-type and P/I null mice, in which neutrophils are stained in brown color. Discussion Neutrophil infiltration is coordinated by the interplay of the adhesion molecules and the chemoattractants, which plays an important role in inflammatory tissue injury. Recent clinical trials of anti-adhesion therapy did not demonstrate a protective effect in trauma-induce shock despite very strong pre-clinical data (15). Further studies to clear this disparity suggested that the model systems applied and the length of injury are important factors that might modulate the underlying mechanism of neutrophil activation and migration (15). Therefore, this study was undertaken to examine the role of P-selectin and ICAM-1 molecules in the wild-type and P/I null mice subjected to a short and longer periods of peritonitis induce by CLP. The CLP model, chosen to mimic the normal course of sepsis in humans and animals, induced the classic signs of sepsis and a significant systemic inflammatory response. This response was associated with increased leukocyte infiltration into the peritoneal cavities of both the wild-type and P/I null mice. The leukocyte influx into the peritoneal cavity consisted predominantly of neutrophils (i.e., 62–80%), which significantly increased in both wild-type and P/I null mice at 6 and 24 hours of CLP. At the early phase of CLP (i.e., 6 h), the total number of neutrophils infiltrated into the peritoneal cavities of P/I null mice were significantly lower than those of the corresponding wild-type mice, which reached to a comparable level at 24 hours of CLP. In contrast to CLP-induced peritonitis, peritonitis induced by 2% glycogen exhibited no significant differences in the number of neutrophils infiltrated into the peritoneal cavities between the wild-type and those of the P/I null mice at 6 hours (Figure 2). The results of this study suggest differential regulation of the inflammatory response and neutrophil response by mode and length of the injury. The data of this study showed that under normal physiologic environment the number of leukocytes present in peripheral blood and peritoneal lavage was comparable in the P/I null and wild-type mice. However, the ratio of neutrophils and lymphocytes were reversed between these two groups. In peripheral blood of P/I mice, neutrophils constituted a larger percentage of the leukocytes, which were significantly higher than those of the wild-type mice. In a striking contrast to the peripheral blood, the P/I null mice had a smaller number of neutrophils in their peritoneal cavities, when compared to those of the wild-type mice. Previous reports have also noted an increase in peripheral blood neutrophils in mutant mice [13]. However, to our knowledge, the decrease in peritoneal neutrophils has not been previously reported. It appears that within the normal physiologic environment, neutrophil trafficking in the peritoneal cavity is low in the P/I null mice and that neutrophil transmigration is regulated through adhesion pathways that utilize P-selectin and ICAM-1 molecules. The reason for increased circulating peripheral blood neutrophil counts in the P/I null is not known. However, this phenomenon has also been previously reported in CD18, P-sel/ICAM-1 mutant mice, and in patients with moderate or severe leukocyte adhesion deficiency [13,23,24]. Further investigation is needed to determine the following: whether hematopoiesis of neutrophils production is enhanced in the P/I null mice; removal of the neutrophils from blood circulation is reduced/delayed; and/or the neutrophil's life span has been increased. In the present study, P-selectin/ICAM-1 appears to be partially involved in neutrophil migration into the peritoneal cavity but only during the early stages of the response to CLP-induced peritonitis. Conversely, these adhesion molecules were not required for maximal neutrophil migration after trauma (i.e. sham operation) or chemically-induced peritonitis (i.e 2% glycogen) and during the late phase of CLP (i.e, 24 hours). The data suggests that there might be a functional role for these adhesion molecules during the initial stages of the inflammatory response, and as the inflammatory process progresses, deficient adhesion mechanisms are bypassed. This notion has also been proposed in leukocyte recruitment in an in vivoexperimental model of autoimmune encephalomyelitis, which is a T-cell-mediated disease. Kerfoot and Kubes have shown that during the early phase of encephalitis the leukocyte rolling was P-selectin dependent; however, with the progression of disease α4-integrin pathway was important in leukocyte rolling and adhesion [25]. Interaction of ICAM-1 expressed on the surface of vascular endothelial cells with the β2-integrins (eg., CD11b and CD18) expressed on neutrophils has shown to be a critical event mediating stable neutrophil adhesion and migration across the vascular endothelial barrier [26-28]. Although the study presented in this article suggests a non-role of ICAM-1 in neutrophil infiltration into the peritoneal cavity in response to peritonitis, it has to be noted that the P/I null mice are not a true ICAM-1 knockout. The P/I null mice may have a low level of alternatively spliced forms of ICAM-1 that could have been up-regulated on the vascular endothelium, and thereby promoting neutrophil migration [29]. Further, the lack of ICAM-1, per se, is not a critical factor that results in dysfunctional β2-integrin-mediated migration. Other adhesion molecule(s), ligand(s), and/or yet unknown counter-receptor(s) could mediate neutrophil infiltration. For example, ICAM-2, a ligand for β2-integrins, could be a potential candidate [32]. Other studies have shown a critical role of vascular cell adhesion molecule-1 (VCAM-1) in mediating neutrophil transendothelial migration and inflammatory tissue injury [30,31]. This adhesion molecule interacts with α4-integrin (α4β1, VLA-4). There is a body of evidence that α4-integrin can mediate several steps of leukocyte recruitment cascade (i.e., rolling and adhesion) through α4-integrin/MADCAM-1 (mucosal addressin cell adhesion molecule-1) and α4-integrin/VCAM-1 pathways. Vajkoczy et al., have shown that T-cells can adhere without rolling in spinal cord microvessels via α4-integrin [32]. Neutrophils express α4-integrin, and studies by Bowden et al. have demonstrated an important role of α4-integrin/VCAM-1 in CD18-independent neutrophil migration across mouse cardiac endothelium [33,34]. Additionally, the α4-integrin/VCAM-1-dependent neutrophil adhesion under flow conditions has been shown in neutrophils isolated from critically ill septic patients [35]. Neutrophil also express CD11d/CD18 and α9-integrin, which both bind VCAM-1, and could possibly, play an important role in neutrophil extravasation at sites of inflammation [36]. The importance of α4- and α9-integrin/VCAM-1 pathways in neutrophil infiltration in CLP-induced peritonitis remains unclear. It is possible that neutrophil infiltration utilizes other secondary or tertiary adhesion pathways, and/or is facilitated by proteins that mediate the function(s) of the adhesion molecules. For example, a novel glycosylphosphatidyl inositol-anchored protein (GPI-80) that may regulate β2-integrin-mediated cell adhesion and motility of neutrophils has been described [38]. Additionally, other proteins are recognized to act as ligands for β2 integrins, such as those produced during coagulation as well as complement activation and tissue factor, which could facilitate neutrophil adhesion and infiltration into the peritoneal cavity [39,40]. Moreover, the local concentrations of chemokines appear to be critical factors in dictating the local neutrophil recruitment in an acute inflammatory response [41]. It has been shown that chemokines and their receptors are involved in leukocytes migration not only by inducing chemotaxis but also by regulating integrins to trigger cell arrest in shear flow [42]. Contrary to several other studies that have demonstrated the functional importance of P-selectin in models of myocardial infarction and inflammatory lung and liver injury, the data presented in this study indicated that P-selectin is not essential for neutrophil migration into the peritoneal cavity [43-45]. In support of our data, several studies have shown that blocking of P-selectin with monoclonal antibody or deletion of P-selectin and ICAM-1 did not inhibit neutrophil infiltration and tissue injury caused by hepatic reperfusion [18], endotoxin shock (46), i.p injection of 2% glycogen [47], and intestinal inflammation [48,49]. In contrast to our results of the P/I null mouse study presented in this article, Bullard et al., have previously reported a complete loss of neutrophil migration into the peritoneum of P/I null mice during peritonitis induced by i.p. inoculation of Streptococcus pneumonia [13]. The difference could due to the length of the experimental setting. In the Bullard et al. study, the inflammatory response and neutrophil infiltration into the peritoneal cavity was studied at 4 hours of the induction of peritonitis, while, in our study neutrophil infiltration was evaluated at 6 and 24 hours of peritonitis. In support of this reasoning is the study reported by Mizgerd et al. who have shown a compromised neutrophil migration into the peritoneal cavity of E-/P-selectin and ICAM-1 mutant mice in response to the injection of Streptococcus pneumoniae at 4 hours after injection, with no impairment present at 24 hours of bacteria injection [8]. Additionallt, Mizgerd et al. demonstrated that ICAM-1 is not necessary for neutrophil migration during glycogen-induced peritonitis, as shown otherwise by other authors [9]. Further, the difference could due to the possibility that in Bullard's study the infiltrated neutrophils into the peritoneal cavity of P/I null mice became necrotic and disintegrated upon challenges with Streptococcus pneumonia organisms. In our study, the data of peritoneal supernatant MPO levels have demonstrated a significant level of MPO released into the peritoneal cavity in mice subjected to CLP (Figure 4B). In Bullard's study the MPO levels of the peritoneal lavages were not measured. Further, in our study the Wright staining as well as the in situ immunohistochemical staining of the peritoneal cells clearly confirms the presence of neutrophils in the cytospin preparations (Figure 3). The data collectively indicate that P-selectin and ICAM-1 each may have a role in neutrophil migration during early stages of acute bacterial peritonitis, but at later stages alternative pathways are recruited to mediate neutrophil migration. Functional redundancy of adhesion molecules and the cytokine production may be sufficient to compensate for the absence of P-selectin and ICAM-1 in mediating neutrophil infiltration into peritoneal cavity in response to CLP in P/I null mice. Another important difference between the results of the study presented in this article and those of previous studies may relate to the employment of essentially different models of sepsis and inflammation. While previous studies employed hemorrhagic shock-, Streptococcus- or LPS-induced peritonitis, the present study employed polymicrobial septic peritonitis as well as chemical and trauma-induced peritonitis. Published studies have shown quantitative and qualitative differences in the inflammatory response induced by gram-positive, gram-negative, polymicrobial sepsis and purified endotoxin [50-52]. These differences include: the species of bacteria employed and their respective antigens, the magnitude of leukocytic response, the magnitude and kinetics of cytokine production, and finally, mortality. Thus, the collective data suggest that the model of septic insult used to induce an inflammatory response is an important consideration. One major advantage of the model used in our study is that the relative magnitude of the inflammatory response in animals subjected to CLP-induced peritonitis is similar to those observed in septic patients [53,54]. Conclusions The data presented in this study have shown a clear, time-dependent neutrophil migration and infiltration into peritoneal cavity in responses to peritonitis, which is independent of P-selectin and ICAM-1 adhesion molecules. The negative nature of the data presented here and the failure of the anti-adhesion clinical trials, are of great importance. These findings demand innovative alternative approaches to neutrophil transmigration in inflammatory response and suggest that targets other than these adhesion molecules need to be identified. A better understanding of the mechanisms leading to neutrophil migration is critical for the development of new therapeutic strategies for treating inflammatory disease without compromising the host's immune response mechanisms. Competing interests None declared. Authors' contribution CR participated in the technical procedures for CLP, collection of blood and tissue samples, and MPO assay. KH and HA participated in preparation of tissue sample for immunohistochemistry and special staining. KH also assisted in preparation of the manuscript. EC conceived the study, and participated in its design, coordination, and preparation of the manuscript. All authors read and approved the final manuscript. Abbreviations CLP, cecal ligation-puncture; ICAM-1, Intercellular adhesion molecule-1; mAbs, monoclonal antibodies; MPO, Myeloperoxidase; P/I null mice, P-selectin/ICAM-1-deficient mice Pre-publication history The pre-publication history for this paper can be accessed here: Acknowledgments The authors wish to thank Dr. Wayne Smith, M.D., Head, Section of Leukocyte Biology, Departments of Pediatrics and Immunology, at Baylor College of Medicine, for the critical review and comments to this manuscript. 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Immunohistochemical detection of Kikuchi's lymphadenitis Di Yi Jun Yi Da Xue Xue Bao 2003 23 723 727 12865232 Wilson RW Ballantyne CM Smith CW Montgomery C Bradley A O'Brien WE Beaudet AL Gene targeting yields a CD18-mutant mouse for study of inflammation J Immunol 1993 151 1571 8 8101543 Anderson DC Springer TA Leukocyte adhesion deficiency: An inherited defect in Mac-1, LFA-1 and p150,95 glycoproteins Annu Rev Med 1987 38 175 194 3555290 10.1146/annurev.me.38.020187.001135 Kerfoot SM Kubes P Overlapping roles of P-selectin and alpha 4 integrin to recruit leukocytes to the central nervous system in experimental autoimmune encephalomyelitis J Immunol 2002 169 1000 6 12097407 Steeber DA Tang MLK Green NE Zhang XQ Sloane JE Tedder TF Leukocyte entry into sites of inflammation requires overlapping interactions between the L-selectin and ICAM-1 pathways J Immunol 1999 163 2176 2186 10438959 Forlow SB Ley K Selectin-independent leukocyte rolling and adhesion in mice deficient in E-, P- and 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el-Gabalawy H Canvin J Ma GM Van der Vieren M Hoffman P Gallatin M Wilkins J Synovial distribution of alpha d/CD18, a novel leukointegrin. Comparison with other integrins and their ligands Arthritis Rheum 1996 39 1913 21 8912515 Suzuki K Watanabe T Sakurai S Ohtake K Kinoshita T Araki A Fujita T Takei H Takeda Y Sato Y Yamashita T Araki Yoshihiko Sendo F A novel glycosylphosphatidyl inositol-anchored protein on human leukocytes: A possible role for regulation of neutrophil adherence and migration J Immunol 1999 162 4277 4284 10201959 Gross TJ Leavell KJ Peterson MW CD11b/CD18 mediates the neutrophil chemotactic activity of fibrin degradation product D domain Thromb Haemost 1997 77 894 900 9184399 Siegbahn A Cellular consequences upon factor VIIa binding to tissue factor Haemostasis 2000 2 41 7 11251340 Call DR Nemzek JA Ebong SJ Bolgos GL Newcomb DE Remick DG Ratio of local to systemic chemokine concentrations regulates neutrophil recruitment Am J Pathol 2001 158 715 720 11159209 Weber C Novel mechanistic concepts for the control of leukocyte transmigration: specialization of integrins, chemokines, and junctional molecules J Mol Med 2003 81 4 19 12545245 Chen LY Nichols WW Hendricks JB Yang BC Mehta JL Monoclonal antibody to P-selectin (PB1.3) protects against myocardial reperfusion injury in the dog Cardiovasc Res 1994 28 1414 1422 7525063 Mullingan MS Polley MJ Bayer RJ Nunn MF Paulson JC Ward PA Neutrophil-dependent acute lung injury: requirement for P-selectin (GMP-140) J Clin Invest 1992 90 1600 1607 1383277 Wickel J Mercer-Jones M Peyton JC Shrotri MS Cheadle WG Neutrophil migration into the peritoneum is P-selectin dependent, but sequestration in lungs is selectin independent during peritonitis Shock 1998 10 265 269 9788658 Essani NA Fisher MA Simmons CA Increased P-selectin gene expression in the liver vasculature and its role in the pathophysiology of neutrophil-induced liver injury in murine endotoxin shock J Leukoc Biol 1998 63 288 296 9500515 Mulligan MS Lentsch AB Miyasaka M Ward P Cytokine and adhesion molecule requirements for neutrophil recruitment during glycogen-induced peritonitis Inflamm Res 1998 47 251 255 9683032 10.1007/s000110050326 Molla M Gironella M Salas A Miquel R Perez-del-Pulgar S Conill C Engel P Biete A Pique JM Panes J Role of P-selectin in radiation-induced intestinal inflammatory damage Int J Cancer 2001 96 99 109 11291093 10.1002/ijc.1009 McCafferty DM Smith CW Granger DN Kubes P Intestinal inflammation in adhesion molecule-deficient mice: an assessment of P-selectin alone and in combination with ICAM-1 or E-selectin J Leukoc Biol 1999 66 67 74 10410991 Silverstein R Wood JG Xue Q Norimatsu M Horn DL Morrison DC Differential host inflammatory responses to viable versus antibiotic-killed bacteria in experimental microbial sepsis Infect Immun 2000 68 2301 8 10722633 10.1128/IAI.68.4.2301-2308.2000 Remick DG Newcomb DE Bolgos GL Call DR Comparison of the mortality and inflammatory response of two models of sepsis: lipopolysaccharide vs. cecal ligation and puncture Shock 2000 13 110 116 10670840 Cross AS Opal SM Sadoff JC Gemski P Choice of bacteria in animal models of sepsis Infect Immun 1993 61 2741 2744 8514375 Remick DG Bolgos GR Siddiqui J Shin J Nemzek JA Six at six: interleukin-6 measured 6 h after the initiation of sepsis predicts mortality over 3 days Shock 2002 17 463 7 12069181 10.1097/00024382-200206000-00004 Turnbull IR Javadi P Buchman TG Hotchkiss RS Karl IE Coopersmith CM Antibiotics improve survival in sepsis independent of injury severity but do not change mortality in mice with markedly elevated interleukin 6 levels Shock 2004 21 121 5 14752284 10.1097/01.shk.0000108399.56565.e7

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==== Front BMC Med EducBMC Medical Education1472-6920BioMed Central London 1472-6920-4-111527474210.1186/1472-6920-4-11Research ArticleResident interest and factors involved in entering a pediatric pulmonary fellowship Gershan William M 1wgershan@mcw.edu1 Department of Pediatrics Section of Pulmonology Medical College of Wisconsin Milwaukee, Wisconsin 53226 USA2004 26 7 2004 4 11 11 24 2 2004 26 7 2004 Copyright © 2004 Gershan; licensee BioMed Central Ltd.2004Gershan; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background Relatively little is known about interest in pediatric pulmonology among pediatric residents. The purpose of this study, therefore, was to determine at this institution: 1) the level of pediatric resident interest in pursuing a pulmonary fellowship, 2) potential factors involved in development of such interest, 3) whether the presence of a pulmonary fellowship program affects such interest. Methods A questionnaire was distributed to all 52 pediatric residents at this institution in 1992 and to all 59 pediatric residents and 14 combined internal medicine/pediatrics residents in 2002, following development of a pulmonary fellowship program. Results Response rates were 79% in 1992 and 86% in 2002. Eight of the 43 responders in 1992 (19%) had considered doing a pulmonary fellowship compared to 7 of 63 (11%) in 2002. The highest ranked factors given by the residents who had considered a fellowship included wanting to continue one's education after residency, enjoying caring for pulmonary patients, and liking pulmonary physiology and the pulmonary faculty. Major factors listed by residents who had not considered a pulmonary fellowship included not enjoying the tracheostomy/ventilator population and chronic pulmonary patients in general, and a desire to enter general pediatrics or another fellowship. Most residents during both survey periods believed that they would be in non-academic or academic general pediatrics in 5 years. Only 1 of the 106 responding residents (~1%) anticipated becoming a pediatric pulmonologist. Conclusions Although many pediatric residents consider enrolling in a pulmonary fellowship (~10–20% here), few (~1% here) will actually pursue a career in pediatric pulmonology. The presence of a pulmonary fellowship program did not significantly alter resident interest, though other confounding factors may be involved. Academic medicinecareer pathsfellowship trainingsubspecialty practice. ==== Body Background The specialty of pediatric pulmonology is relatively new, having been recognized as a pediatric sub-specialty by the American Board of Medical Sub-specialties in 1984. In 1997, there were approximately 500 board certified pediatric pulmonologists in the United States and Canada [1]. This number has increased in recent years with 708 board certified pulmonologists being identified in 2003 [2]. It has been estimated that there is one pediatric pulmonologist for every 280,000 children in the United States [1]. There are over 50 pediatric pulmonary fellowship programs in North America with approximately 30–35 fellows graduating each year. The demand for pediatric pulmonologists has increased during the past decade, with many academic centers looking for two or more pulmonologists simultaneously [3]. A recent national survey of medical directors at children's hospitals across the country found that vacancy rates for faculty in pediatric pulmonology (25 of 136 positions vacant = 18.4%) was ranked second highest, behind only pediatric endocrinology, among over 40 pediatric subspecialties [3]. Despite this demand, little is known about overall interest in this field among pediatric residents. For this reason, this study was completed to examine interest among pediatric residents in entering a pulmonary fellowship. The specific aim of this study, therefore, was to determine at our institution: 1) the level of pediatric resident interest in pursuing a pulmonary fellowship; 2) potential factors involved in development of such interest; 3) whether the presence of an active fellowship program affected resident interest in such a program. Methods This study involved the distribution of a questionnaire to all pediatric residents. The questionnaire was initially distributed in 1992 prior to institution of a pulmonary fellowship. The questionnaire was placed in the hospital mailbox of each resident. The study was repeated (and the questionnaire redistributed) in 2002 after the fellowship, which began in 1994, had been functioning for several years. To improve the response rate, the questionnaire was distributed twice, one month apart, during each time period. The questionnaire was a three-page, 18 question form that took approximately 15 minutes to complete (copy enclosed in Appendix [see Additional file 1]). The questionnaire asked several epidemiological questions (e.g. year of residency, whether medical school was attended at this institution), several questions that pertained to an individual resident's interest in entering any specialty fellowship, and approximately 12 questions specifically dealing with interest in doing a pulmonary fellowship and factors that may be either positively or negatively related to such interest. The survey utilized a flow diagram, and consequently, slightly different questions were asked depending on a resident's interest or lack of interest in a pulmonary fellowship. The study was analyzed after dividing the respondents into 2 groups: those that had considered a pulmonary fellowship during their residency ("+PF") and those that had not considered a pulmonary fellowship during their residency ("-PF"). Neither Human Subjects approval nor specific resident consent was obtained. However, all questionnaires were answered anonymously and residents were in no way coerced or forced to complete the survey. Residents who completed the form were given a certificate for a free meal at Children's Hospital of Wisconsin. Several questions were based on a 4-point Likert scale and ranked from 0 ("not at all important") to 3 ("very important") in a resident's decision to consider or not consider doing a pulmonary fellowship. Numerical responses for each survey period were averaged (mean ± SD) and ranked. Fisher's exact test was used to compare categorical variables and the Student's t-test was used to compare the means of measured variables in 2 independent samples. A p value of ≤ 0.05 was considered significant. Medical Education records were also reviewed anonymously (data collated by year of residency) in 2003 to determine residents' actual career decisions. Results The questionnaire was distributed to 52 pediatric residents (including 2 chief residents) in 1992 and to 59 pediatric residents (including 3 chief residents) and 14 medicine/pediatric residents (including 1 chief resident) in 2002. A medicine-pediatric residency program did not exist during the initial distribution period. To avoid compromising confidentiality in the relatively small medicine/pediatric group, residents were not asked to list their residency program in 2002 and consequently the 2 resident groups during that period were combined. Forty-three of the 52 residents completed the survey in 1992 (79%) compared to 63 of 73 (86%) during 2002 (p = NS). Of the 43 respondents in 1992, 30 (70%) had considered doing a fellowship in any pediatric subspecialty and of those, 15 (35% of all respondents) believed they were "very likely" to do a fellowship. Of the 63 respondents in 2002, 40 (63%) had considered doing a pediatric fellowship and 16 of those (25% of all respondents) were "very likely" to continue with fellowship training. These numbers compare with 9 of the 52 residents in 1992 (17%) who actually completed fellowship training compared to 16 of the 47 graduating residents from the 2002 survey (34%) who began fellowship training in 2003 or 2004. Eight residents (19%) in 1992 had considered a pulmonary fellowship compared to 7 residents (11%) in 2002 (p = NS). Table 1 lists these responses based on survey period and year of residency (internal medicine-pediatric residency is 4 years long). Although all residents have significant exposure to pulmonary patients during their residency, no correlation existed between interest in a pulmonary fellowship and having previously taken a one-month elective in pediatric pulmonology during residency. Three of the 15 residents who had considered a pulmonary fellowship ("+PF") had taken a pulmonary elective compared to 7 of the 91 residents who had not considered such a fellowship ("-PF"; p = 0.15). Of the 10 residents who had taken a pulmonary elective, only 2 thought that the elective experience affected their decision in considering a pulmonary fellowship (one from the +PF and one from the -PF group). Table 1 Resident response based on year of survey (1992 or 2002) and year of residency (1–5) 1992: Residency Year Resident Number Number Responded % Response +PF* -PF** 1 21 20 95% 5 15 2 19 12 63% 2 10 3 10 9 90% 0 9 4 2 2 100% 1 1 1992 totals 52 43 79% 8 35 2002: Residency Year Resident Number Number Responded % Response +PF* -PF** 1 24 22 92% 3 19 2 21 20 95% 3 17 3 22 17 77% 1 16 4 5 3 60% 0 3 5 1 1 100% 0 1 2002 totals 73 63 86% 7 56 * +PF refers to those residents who had considered doing a pulmonary fellowship during their residency. ** -PF refers to those residents who had not considered doing a pulmonary fellowship during their residency. Table 2 lists and ranks the reasons given by residents who had considered doing a pulmonary fellowship. The highest ranked factors given by +PF residents included wanting to continue one's education after residency, enjoying caring for pulmonary patients in general, and enjoying both pulmonary physiology and the pulmonary faculty. The only factor that approached a statistically significant difference for +PF between the 2 survey periods was the statement "I enjoy the tracheostomy-ventilator population," with a score of 0.6 ± 0.5 in 1992 vs. 1.6 ± 1.1 in 2002 (p = 0.057), suggesting that this factor became somewhat more important to the 2002 +PF residents in their consideration of a pulmonary fellowship. Table 3 lists and ranks reasons given by residents who had not considered doing a pulmonary fellowship. The scores given by -PF residents were generally not as high as those given by +PF residents, i.e. the factors listed were not as important to the -PF vs. the +PF residents. Major factors listed by -PF residents included not enjoying the tracheostomy/ventilator population and certain pulmonary patients in general, including chronic patients, as well as a desire to enter general pediatrics or another fellowship. The significant differences for -PF between the 2 survey periods are listed in Table 3. Table 2 Mean (± SD) scores for factors given by +PF residents (those who considered a pulmonary fellowship) Factor* 1992 Score 1992 Rank 2002 Score 2002 Rank I want to continue my education after residency 2.8 ± 0.4 1 2.4 ± 0.8 1 I enjoy pulmonary-related procedures 2.5 ± 0.8 2 2.0 ± 1.0 10 I enjoy caring for pulmonary patients 2.4 ± 0.5 3 2.4 ± 0.5 1 I like pulmonary physiology 2.4 ± 0.8 3 2.3 ± 0.8 4 I like the pulmonary faculty 2.4 ± 0.5 3 2.4 ± 0.8 1 I enjoy pulmonary inpatient coverage 2.3 ± 0.5 6 2.3 ± 0.5 4 I enjoyed working with a particular faculty member 2.1 ± 0.9 7 2.1 ± 0.7 7 I might enjoy pulmonary-related research 2.0 ± 1.2 8 1.4 ± 0.8 12 I enjoy pulmonary clinics 2.0 ± 1.0 8 2.2 ± 0.8 6 I enjoy cystic fibrosis patients 1.9 ± 1.1 10 2.1 ± 1.1 7 I enjoyed caring for a particular pulmonary patient 1.7 ± 1.3 11 2.1 ± 0.7 7 The salary would be attractive 1.1 ± 1.2 12 1.0 ± 0.8 13 I enjoy the tracheostomy/ventilator population 0.6 ± 0.5 13 1.6 ± 1.1# 11 *Each factor was scored from 0 ("not at all important") to 3 ("very important") relating to a resident's decision to consider doing a pulmonary fellowship. #2002 score approached statistically significant difference vs. 1992 score (p = 0.057). Table 3 Mean (± SD) scores for factors given by -PF residents (those who did not consider a pulmonary fellowship) Factor* 1992 Score 1992 Rank 2002 Score 2002 Rank I don't enjoy the trach/vent population 2.0 ± 1.1 1 1.9 ± 1.3 1 I want to enter general pediatrics 1.9 ± 1.2 2 1.8 ± 1.3 2 I don't enjoy certain pulmonary patients 1.6 ± 1.1 3 1.2 ± 1.1 4 There are too many chronic patients 1.5 ± 1.1 4 1.5 ± 1.1 3 I want to enter another fellowship 1.5 ± 1.2 4 1.2 ± 1.3 4 I don't know enough about it to decide 1.5 ± 1.1 4 1.0 ± 1.1 7 Not enough pulmonary patient experience 1.4 ± 1.1 7 0.6 ± 0.9# 9 I don't enjoy the BPD+ population 1.2 ± 1.0 8 1.2 ± 1.1 4 I don't think pulmonary is very interesting 0.9 ± 0.9 9 0.6 ± 0.8 9 Some of the pulmonary patients scare me 0.7 ± 0.8 10 0.8 ± 1.0 8 I can't afford being a fellow 0.7 ± 1.1 10 0.4 ± 0.8 12 The pulmonologists work too hard 0.4 ± 0.6 12 0.4 ± 0.7 12 I don't enjoy the cystic fibrosis population 0.3 ± 0.6 13 0.6 ± 0.9 9 Too few pulmonary job openings 0.3 ± 0.5 13 0.0 ± 0.2# 17 I don't enjoy the asthma population 0.2 ± 0.5 15 0.4 ± 0.8 12 Pulmonologists don't earn enough money 0.2 ± 0.5 15 0.1 ± 0.4 16 Poor experiences with pulmonary faculty 0.2 ± 0.4 15 0.3 ± 0.8 15 *Each factor was scored from 0 ("not at all important") to 3 ("very important") relating to a resident's decision to not consider doing a pulmonary fellowship. #Indicates 2002 score significantly different than 1992 score, p < 0.001. + bronchopulmonary dysplasia The last question in the survey asked residents what they thought they would be doing 5 years in the future. These responses are shown in Table 4. The majority of residents during both survey periods believed that they would be in either non-academic or academic general pediatrics in 5 years. However, when grouped together during the 2 periods, the +PF residents were less likely to see themselves in the future as general pediatricians compared to the -PF residents (p < 0.05). Interestingly, when the actual career decisions of the 1992 residents were reviewed, 35 of the 52 residents (67%) went into non-academic general pediatrics, 5 (10%) entered academic general pediatrics, 9 (17%) completed pediatric subspecialty training, 2 (4%) began a non-pediatric medical specialty, and in 1 case (2%) the eventual career decision could not be determined. Only 1 resident (from 1992 survey) in the entire group of 106 survey responders (~1%) believed they would be in the field of pediatric pulmonology in the future. This resident did complete a pulmonary fellowship at another institution and is currently in an academic pulmonary practice. Additionally, a second resident (from 1992 survey) is currently an academic pediatric pulmonologist after having initially completed one year of a different subspecialty fellowship following residency. That resident then completed a pulmonary fellowship at this institution. Lastly, there was no significant difference in the overall level of interest in a pulmonary fellowship from 1992 compared to 2002. Table 4 Anticipated professional plans of resident 5 years following survey completion Category 1992 2002 +PF -PF +PF -PF General pediatrics, non-academic 1 14.5* 2 29 Academic general pediatrics 1 5 1 8.5 Academic non-pulmonary pediatric specialty 3 12 2 16 Academic pediatric pulmonology 1 0 0 0 Non-academic non-pulmonary pediatric specialty 1 1.5 1 1.5 Non-academic pediatric pulmonology 0 0 0 0 Non-pediatric medical specialty 0 0 0 1 Non-medical vocation 0 0 0 0 Unknown 1 2 1 0 See text and footnote to Table 1 for explanation of +PF and -PF. The numbers represent actual number of residents responding. *Some residents listed 2 categories, hence their score was divided between them. Discussion This study found that a significant percentage of pediatric residents considered doing a pulmonary fellowship after their residency training, ranging from 11% in the 2002 group to 19% in the 1992 group. However, these residents also viewed themselves as less likely to enter general pediatrics perhaps suggesting that they were simply considering several pediatric subspecialties at some time during their residency training. This seems likely, as the highest scored factor by the +PF residents was the desire to continue their education after residency. Despite fairly high percentages of residents considering a pulmonary fellowship, only 1 resident in the entire group (~1%) actually believed that they would be a pediatric pulmonologist 5 years after the survey was completed. This percentage is very similar to that of first-time takers of the 1995 General Pediatrics Certifying Examination who believed they would be a pediatric pulmonologist in the future (1.1%) [4]. If one were to extrapolate this number to the entire class of graduating pediatric residents per year, about 2600 residents, approximately 30 residents would be entering the field of pediatric pulmonology each year [5]. This number is very similar to the actual number of graduating residents who enter a pediatric pulmonary fellowship each year [2]. The majority of residents who considered doing a pulmonary fellowship (8 of 15) were in their first year of residency. From personal experience, residents often consider various practice options early on in their training and frequently do not tend to narrow their choices until their second or third year of residency. This observation should be kept in mind when trying to recruit residents for pulmonary fellowship positions by seeking out those residents potentially interested in Pulmonology early on in residency rather than later. The ranking of factors that may contribute to an interest in a pulmonary fellowship were remarkably similar during the 2 time periods. The only score that approached a statistically significant difference was the statement "I enjoy the tracheostomy/ventilator population" and this score tended to increase in 2002. However, a dislike for the tracheostomy/ventilator population also received the highest score among those residents not interested in a pulmonary fellowship and was even higher than both the desire to enter general pediatrics and another fellowship program. These data may simply be a center phenomenon but might suggest a more global "disinterest" in this patient population that may need to be further studied. Two scores in the -PF resident group decreased from 1992 to 2002: not enough pulmonary patient experience to decide on a pulmonary fellowship and too few perceived pulmonary job openings. The first may be a positive reflection on the local resident experience with pulmonary patients in recent years or on the fellowship program itself though this is only speculative. The second received very low scores during both periods and may not be very relevant. However, there has been some evidence of a reversal in the prior trend of residents entering general pediatrics in recent years, suggesting greater interest among residents in fellowships [6]. On the other hand, a recent survey of practicing pediatric pulmonologists noted that 69% of respondents did not believe that there was need for additional pulmonologists in their locale [7]. Interestingly, despite recent articles relating high post-residency debt with a disinterest in entering a fellowship, this was not noted in this study with mean scores during both survey periods of less than 1.0 for the statement "I can't afford being a fellow." [8,9]. This study did not ask residents to state their current level of indebtedness. Other "job concern" factors including job availability and the workload of pulmonologists did not appear to be significant negative factors for the -PF residents. This study has certain shortcomings. This study asked residents to score specific factors that may or may not have been relevant to an individual resident. Although residents were given the opportunity to add personal comments, few did. In addition, certain patient populations, e.g those with respiratory infections, were not included as options in the survey and these omissions could cause study bias. Other factors that may contribute to residents' decisions regarding fellowship training were not addressed in this study. These factors include resident teaching by the faculty, resident gender, spouse occupation, mentor encouragement or other personal reasons [10-12]. In addition, this study involved residents in only one program and cannot be generalized to all residency programs. Although this study did not find that the presence of a pulmonary fellowship significantly affected resident interest in such a fellowship, a significant difference may have been found with a larger sample size. In fact, the study appears to be underpowered despite the high response rate. More than 250 individuals would need to have been included in the study to detect a significant difference in residents' initial interest in a pulmonary fellowship (assuming a power of 80%). In addition, other changes may have occurred within the residency program including higher loan repayments, changes in department philosophy (e.g. new department chairman), and changes in local pediatric job opportunities, which may have affected the results. Despite these limitations, this study may prove useful to those who are recruiting pediatric residents as potential pulmonary fellows. Further larger studies looking at multiple residency programs may provide more insight in the future. Lastly, studies like these help to reiterate the need for the specialty of pediatric pulmonology to "prospectively and objectively determine realistic future training needs" [13]. Conclusions Although many pediatric residents consider enrolling in a PF (~10–20% here), few (~1% here) will actually pursue a career in pediatric pulmonology. The presence of a PF program did not significantly alter resident interest, though other confounding factors may be involved. Abbreviations BPD: bronchopulmonary dysplasia PF: pulmonary fellowship +PF: those residents who considered taking a pulmonary fellowship -PF: those residents who had not considered taking a pulmonary fellowship Competing interests None declared. Pre-publication history The pre-publication history for this paper can be accessed here: Supplementary Material Additional File 1 Appendix. Resident questionnaire Click here for file Acknowledgments The author would like to thank Gloria Larsen, the Pediatric Residency Program Coordinator, for her assistance in supplying medical education residency records and also thank Dr. Robert Kliegman for his review of the manuscript. ==== Refs Committee of Workforce and Training of the American Thoracic Society The role of the pediatric pulmonary physician in the American health care system Am J Respir Crit Care Med 1997 155 1486 1488 9105100 Stockman JA IIIMiles PV Ham HP American Board of Pediatrics The program for maintenance of certification in pediatrics (PMCP) J Pediatr 2003 143 292 295 14517507 10.1067/S0022-3476(03)00441-4 O'Leary K Katz G Hollander F The shortage of pediatric subspecialists: what can children's hospitals do? Children's Hospitals Today Winter 2002 Oliver TK JrTunnessen WW JrButzin D Guerin R Stockman JA III Pediatric workforce: data from the American Board of Pediatrics Pediatrics 1997 99 241 245 9024453 Tunnessen WW JrGuerin RO Stockman JA III Pediatric workforce: data from the American Board of Pediatrics J Pediatr 2001 139 311 316 11487762 10.1067/mpd.2001.116933 Cull WL Yudkowsky BK Shipman SA Pan RJ Pediatric training and job market trends: results from the American Academy of Pediatrics third-year resident survey, 1997–2002 Pediatrics 2003 112 787 792 14523167 Redding GJ Cloutier MM Dorkin HL Brotherton SE Mulvey HJ Practice of pediatric pulmonology: results of the future of pediatric education project (FOPE) Pediatr Pulmonol 2000 30 190 197 10973036 10.1002/1099-0496(200009)30:3<190::AID-PPUL2>3.0.CO;2-P Hardie WD Jaskiewicz JA Declining pediatric subspecialty training and rising educational debt J Pediatr 2001 138 149 151 11148539 10.1067/mpd.2001.108701 The Future of Pediatric Education II The role of pediatric subspecialists Pediatrics (suppl) 2000 105 185S 189S Pan RJ Cull WL Brotherton SE Pediatric residents' career intentions: data from the leading edge of the pediatrician workforce Pediatrics 2002 109 182 188 11826193 Pan RJ Clark-Chiarelli N Peters AS Block SD Intention to practice primary care by pediatric residents: nature or nurture? Clin Pediatr 1999 38 473 479 Lovejoy FH Nathan DG Careers chosen by graduates of a major pediatrics residency program, 1974–1986 Acad Med 1992 67 272 274 1558603 Walker WA A subspecialist's view of training and pediatric practice in the next millennium Pediatrics 1998 102 636 644 9738188

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==== Front BMC Med Inform Decis MakBMC Medical Informatics and Decision Making1472-6947BioMed Central London 1472-6947-4-111527122110.1186/1472-6947-4-11Research ArticleA quantitative analysis of qualitative studies in clinical journals for the 2000 publishing year McKibbon Kathleen Ann 12mckib@mcmaster.caGadd Cynthia S 1csg@cbmi.pitt.edu1 Center for Biomedical Informatics 8084 Forbes Tower, 200 Lothrop Street, University of Pittsburgh, Pittsburgh, PA USA 15213-25822 Health Information Research Unit Department of Clinical Epidemiology and Biostatistics, McMaster University Faculty of Health Sciences Hamilton, Ontario Canada L8S 1V82004 22 7 2004 4 11 11 19 3 2004 22 7 2004 Copyright © 2004 Ann and Cynthia S; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background Quantitative studies are becoming more recognized as important to understanding health care with all of its richness and complexities. The purpose of this descriptive survey was to provide a quantitative evaluation of the qualitative studies published in 170 core clinical journals for 2000. Methods All identified studies that used qualitative methods were reviewed to ascertain which clinical journals publish qualitative studies and to extract research methods, content (persons and health care issues studied), and whether mixed methods (quantitative and qualitative methods) were used. Results 60 330 articles were reviewed. 355 reports of original qualitative studies and 12 systematic review articles were identified in 48 journals. Most of the journals were in the discipline of nursing. Only 4 of the most highly cited health care journals, based on ISI Science Citation Index (SCI) Impact Factors, published qualitative studies. 37 of the 355 original reports used both qualitative and quantitative (mixed) methods. Patients and non-health care settings were the most common groups of people studied. Diseases and conditions were cancer, mental health, pregnancy and childbirth, and cerebrovascular disease with many other diseases and conditions represented. Phenomenology and grounded theory were commonly used; substantial ethnography was also present. No substantial differences were noted for content or methods when articles published in all disciplines were compared with articles published in nursing titles or when studies with mixed methods were compared with studies that included only qualitative methods. Conclusions The clinical literature includes many qualitative studies although they are often published in nursing journals or journals with low SCI Impact Factor journals. Many qualitative studies incorporate both qualitative and quantitative methods. ==== Body Background Quantitative studies provide answers or insights for many important questions or issues in health care and clinical research. Other important questions dealing with why, how, contexts, and experiences of individuals or groups, can be best addressed using qualitative methods. Other issues benefit from interleaving or integration of both research traditions. Miller and Crabtree [1], describe their experiences working in family medicine, a clinical domain where balancing qualitative and quantitative research styles benefits both patients and their families and health care professionals. They embrace holding "quantitative objectivism in one hand and qualitative revelations in another" and encourage others to use findings from both paradigms in understanding and practicing effective health care. Creswell and colleagues expand on this theme by stating that "When used in combination, both quantitative and qualitative data yield a more complete analysis, and they complement each other" [2]. Most studies in the major clinical journals have been quantitative studies. Very few qualitative studies and even fewer that combine both qualitative and quantitative approaches are published. An example of the breadth of qualitative studies and how findings and results can be combined across paradigms is a study by Jolly and Wiles [3,4] who used mixed methods to study a nurse-led intervention for 422 adults after myocardial infarction and 175 adults with new-onset angina in 67 general practices in the United Kingdom. Their study showed statistically insignificant results at 1 month for eating healthy food, participating in exercise programs, and successful smoking cessation. Although patients in the nurse-led group were more likely to attend a rehabilitation program (37% vs. 22%, P = 0.001) attendance was disappointingly low. The researchers interviewed a group of patients using qualitative methods and found that people felt survival after a myocardial infarction indicated that the event had not been all that serious. Health care professionals often communicated simplified data about recurrence and being "back to normal" in 6 weeks. Because of these two issues, patients felt that their cardiac problems had probably been mild and therefore were not sufficiently motivated to implement major lifestyle changes. Another example of the use of mixed methods was research done by Willms and Wilson and their colleagues [5-7] on smoking cessation. They found the meanings that patients who smoked attributed to their cigarettes (peer acceptance, coping during a time of stress and feeling out of control, feeling more like an adult, and smoking as more glamorous, tough, and rebellious) had more influence on cessation than did such external conditions as nicotine gum or counseling. Until the complex issues of why individuals smoke were dealt with, few were motivated to change their attitudes towards smoking and thus stop smoking. Another effective example of integrated qualitative (ethnography) and quantitative (epidemiology) methods was a study done by Borkan and colleagues [8] to determine predictors of recovery after hip fracture in elderly patients. Traditional predictors such as age, type of break, and comorbidity, were collected by using standard questionnaires. In-depth interviews were used to collect injury narratives focusing on internal explanations of the fracture, sense of disability, and view of the future after hip fracture. None of the epidemiology factors predicted successful outcomes but those who perceived their fracture as more external or mechanical as opposed to an internal or organic problem (e.g., related to chronic disease) were more likely to have good recovery. Persons who perceived their disability in the context of autonomy, independence, and connection with the outside world also showed better ambulation at 3 and 6 months than persons with a more narrow and confined view of the fracture and its resulting disability. Donovan and colleagues [9] used mixed methods to study prostate cancer screening and treatment choices to determine why study recruitment was lower than expected. Rousseau and Eccles and their colleagues [10,11] used qualitative methods (case interviews) to explain the limited use of computerized guidelines for asthma and angina in a primary care study done in the United Kingdom. Many other examples exist; Creswell and colleagues describe 5 additional mixed methods studies in primary care as well as provide criteria for evaluating mixed methods studies [2]. We postulate that qualitative studies, either stand-alone reports or studies with mixed methods, are occurring more frequently in health care. This paper was done to describe the publishing of qualitative studies in 1 year of clinical literature, document and present the range of content and techniques in these studies, and establish a baseline for subsequent studies. We defined our sample to include all articles published in a set of major general medical, mental health, or nursing journals during 2000. We determined how many qualitative studies were published and in which journals, and extracted design methods and healthcare content, and how often studies used mixed methods and analyses. Because the nursing literature published a higher proportion of qualitative studies in our sample we also compared studies published in nursing journals with other journals to ascertain if quantitative differences exist across disciplines in the use of qualitative methods. Our analysis is a quantitative review of qualitative studies in health care in 2000. Methods The Health Information Research Unit of the Department of Clinical Epidemiology and Biostatistics, Faculty of Health Sciences at McMaster University in Hamilton, Ontario, Canada was the editorial office for four evidence-based summary journals in 2000: ACP Journal Club (internal medicine content), Evidence-Based Medicine (family/general practice content), Evidence-Based Nursing (general care nursing content), and Evidence-Based Mental Health (mental health care content). Their purpose is to provide enhanced abstracts and commentaries on important high-quality original studies and review articles for their respective clinical audiences. To identify these studies and review articles, 6 research staff read major clinical journals to ascertain if articles were in 1 or more categories of therapy, diagnosis, prognosis, etiology, economics, clinical prediction guides, differential diagnosis, and qualitative studies and if so, did each meet predefined methodology criteria for study quality[12]. For 2000 we intensified our data collection to provide data to update and develop new clinical retrieval searching hedges for MEDLINE, PsycINFO, CINAHL, and EMBASE using methods described by Haynes and colleagues[13]. One hundred and seventy journals provided data for this article. The staff of the Health Information Research Unit has established quality criteria for the 8 categories of clinical literature that must be met before articles are judged appropriate for clinical application and publication in an abstract journal. Qualitative studies have 3 criteria: • content relates to how people feel or experience certain situations, specifically those that relate to health care • data collection methods and analyses are appropriate (primary analytical mode is inductive rather than deductive) • units of collection and analysis are ideas, thoughts, concepts, phrases, incidents, or stories that become categories or themes. The reading methods have been developed during the past 13 years and inter-rater reliability kappa (chance adjusted agreement) for identifying categories and applying criteria is consistently > 80%. For this paper, KAM, one of the readers, analyzed the qualitative studies. Qualitative systematic reviews were excluded leaving only reports of original studies. These were assessed to extract journal title, qualitative study type, data collection methods, research question, persons studied, setting, and disease or health condition considered. In addition, studies with mixed methods were further analyzed although we did not use stringent criteria for assessing the quality [2] of the combination of methods. We identified mixed methods articles using a loose criterion of "some numerical or statistical analysis of quantitative data or qualitative data that had been turned into quantitative data". (An example of quantifying qualitative data is the study done by Borkan and colleagues [8] on hip fracture.) The analysis had to be fairly substantial–for example, a simple descriptive analysis of baseline demographics of the participants was not sufficient to be included as a mixed methods article. In addition, Giacomini and Cook [14,15], as part of the Evidence-Based Working Group in the Users' Guides to the Medical Literature, describe attributes that they have identified as belonging to high-quality qualitative studies: participant selection, data collection, and analysis methods. These aspects were also extracted for analysis in this report. Data were taken from article abstracts and if needed, the full text was reviewed. Methodologies assessed were phenomenology, grounded theory, ethnography, case studies, narrative analysis, participant action, critical incident techniques, and discourse analysis. Author descriptions were used and if an additional methodology was found it was added to the list of types using definitions and descriptions from the Handbook of Qualitative Analysis, 2nd edition by Denzin and Lincoln [16]. Data collection and sampling procedures were also extracted. Multiple designations were allowed. To assess the reproducibility a random 10% (n = 35) sample of citations was reviewed using predefined decision rules by another researcher trained in research methods. Results The 170 journals included 60 330 articles of which 31 496 (52%) contained original data or were review articles. 3830 of these (6%) passed criteria for being high-quality and clinically relevant in 1 of the 8 categories. 367 articles met quality criteria for original studies or reviews of qualitative studies. Table 1 lists the journals that published at least 1 qualitative study. Twelve systematic reviews were excluded leaving 355 qualitative studies for assessment. Approximately 0.6% of all articles in the 170 journals and 9% of all high-quality, clinically relevant studies were qualitative studies. The reproducibility of the categorization was measured by kappa (chance adjusted agreement): 0.92 for disease/condition, 0.83 for groups studied, 0.81 for setting, 0.73 for data collection, and 0.63 for data analysis type. The agreement for data analysis type was disappointing but not surprising in that 20% of the studies did not label their analyses necessitating assignment of analysis type by the data extractors. Agreement was low for participant selection methods (kappa 0.5) and therefore data on participant selection methods are not reported. The 355 qualitative studies appeared in 48 journals (mean 7.4 articles per journal, range 1 to 86). These 48 journals were only 28% of the 170 clinical journals being read. Most of the qualitative studies were published in nursing journals: The 17 nursing titles included 214 qualitative studies (61% of all of the qualitative studies). Few qualitative studies were published in the high-circulation, general healthcare journals. Using SCI Impact Factor ranking for 2000, only 4 of the top 20 journals (Table 2) published qualitative studies. These 4 journals published 15 qualitative studies with BMJ publishing 12. The highest-ranking journal with qualitative studies was Annals of Internal Medicine, ranked number 6. JAMA, ranked number 2, published articles about qualitative studies in 2000 [14,15] but did not publish any qualitative studies. Mixed qualitative and quantitative studies 37 qualitative studies (11%) included qualitative and quantitative methods and analyses. These were published in 17 journals with only 1 article in BMJ from the top 20 journal titles in Table 1. Social Science and Medicine published 10 of these mixed methodology studies–the most of any title studied. Content Content of the studies is shown in Table 3. Many studies dealt with a range of participants and settings. Patients (56%), family (22%), and other non-health care professionals (14%) were studied more often than health professionals (nurses (21%), physicians (11%), and others (5%)). Non health care settings occurred more often with home or similar settings being studied in 44% of studies and other community settings in 16%. Health care settings were the hospital (25%), clinic (17%), nursing home (5%), and the emergency department (2%). Disease/condition breakdowns represented common health care situations: cancer (11%), mental health (10%), pregnancy and childbirth (9%), cerebrovascular disease (10%), general issues such as vaccinations or Internet use, and nonspecific spectrum of diseases (e.g., all patients in a clinic) (12%). Many uncommon issues were also assessed. For example, Tongprateep [17] reports a phenomenology study designed to help nurses better understand essential elements of spirituality and health among rural Thai elders. Analysis of the 37 articles with mixed methods showed similar patterns for settings, persons studied, and disease/condition evaluated except that more physicians were studied (P < 0.025) and more situations dealing with injury (P < 0.001) were evaluated. For the 211 articles in Nursing journals, very little difference was also seen except that fewer physicians were studied (P < 0.001) and more studies were done outside clinical settings (P < 0.001). Phenomenology (37%), grounded theory (35%), and ethnography (18%) were used most often with some case studies (7%), narrative analysis (6%), participant action (3%) research, critical incident techniques (1%), and discourse analysis (1%) (Table 4). More than one qualitative method was used in 8% of studies. This pattern of methodology choice was similar for the 37 mixed methods studies and the 211 Nursing articles except that mixed studies methods used relatively more case studies and the Nursing studies used fewer of them (P < 0.025). The mixed methods studies did not included participatory action research, critical incident technique, or discourse analysis studies, methods that could be difficult to combine with quantitative studies. Semi-structured interviews were used (77%) with some focus groups (18%) and observation (14%). These methods are major data gathering techniques in qualitative studies. Questionnaires (7%), document analysis (6%), and structured (4%) and unstructured interviews (1%) were used less often. For mixed methods studies, patterns were similar although questionnaires were used more frequently (24% vs. 7%, P < 0.01). Nursing studies did not differ for data gathering techniques. Sampling is important in all studies–often no single right way exists for a study question. Purposive, snowball, and theoretical sampling are often used in qualitative studies and random and consecutive sampling for quantitative studies. All methods were represented in this analysis but the breakdowns are not reported because of low inter-rater agreements for categorization and missing author information. Discussion In 2000 the major clinical journals published many qualitative studies–approximately 9% of all high-quality, clinically relevant articles. Most of the qualitative studies were reports of original research although 12 (3%) were systematic reviews. Most of the qualitative studies were in nursing journals although some medical journals such as BMJ and Annals of Internal Medicine also published several. Three of the high circulation medical journals (New England Journal of Medicine, Lancet, and JAMA) and 16 of the top 20 clinical journals, based on SCI Impact Factors, did not publish any qualitative studies. This is likely a reflection on the emphasis on a positivist, numerical approach that many of these journals embrace. The difference in proportion of qualitative studiers published in nursing journals is probably because of two historical, but linked factors. Qualitative studies have roots in women's studies and the nursing profession has always dealt with the patient as much more of a whole person rather than basic sciences facts and numbers. Both of these factors lead to more emphasis on understanding and embracing qualitative methods for research and practice. This view is substantiated by the fact that MEDLINE indexes most of the qualitative studies under the term Nursing Methodology Research until 2003. A substantial proportion of the qualitative studies (11%) included both qualitative and quantitative (mixed) data. In general, these mixed methods studies were similar to the single methodology studies except they did more assessments of physicians and relied more on questionnaires to gather data for analysis. The presence of these mixed methods or multipardigmatic studies as described by Miller and Crabtree [1] and Creswell [18] is encouraging for those who espouse harnessing methodologies appropriate for exploring, explaining, and interpreting the complexities and ranges of issues in health care practice and research. It is also interesting comparing qualitative studies in Nursing and non-Nursing journals. Regardless of the differences in proportion of qualitative studies published, from a content point of view few differences exist between the Nursing and non-Nursing journals except that more physicians were studied in the non-Nursing journals and fewer studies were done in clinical settings–not unsurprising findings. This indicates that the content and methods of qualitative studies seem to be similar across disciplines or if the methods are combined with quantitative methods. This review of the publication of qualitative studies is limited in several ways. The proportion of journals studied was very low in relation to the total number of journals published. MEDLINE indexes over 4000 journals and this number is still a relatively small proportion of all journals that deal with health care. In addition, all of the journals searched were published in English so we do not know about qualitative studies in other languages. Although our criteria were relatively strict for including qualitative studies, our criteria for mixed methods studies could certainly have been stronger. We did not count the number of high-quality quantitative studies that could have included some qualitative analyses. We studied only 1 year of publishing; much could have changed since 2002. Qualitative studies provide insight into social, emotional, and experiential aspects of health and health care and as such, they have an important place in understanding health and health care. Hopefully more studies will be published and more will be published in the high impact (high circulation) journals. This paper provides a basis for measuring increases. Conclusion Qualitative studies are being done and are published in a wide range of healthcare journals. These journals however are not the highest impact journals. It is encouraging to see that the number of qualitative studies that were published in 2000 and also the number of studies that combined qualitative and quantitative methods. More can be done however to complete and publish qualitative studies, and where appropriate, integrate the best of both methodologies. Both qualitative and quantitative researchers and clinicians need to work together to make this happen. Journal editors can also encourage submission of qualitative and mixed methods studies and facilitate publication of those they do receive. List of Abbreviations SCI ISI Science Citation Index Competing interests None declared. Author Contributions This work was done in partial fulfillment of PhD requirements for KAM. Both authors have supplied intellectual input in designing and implanting the survey. KAM has collected and analyzed the data and both authors have contributed to writing the paper and agree on its content. Pre-publication history The pre-publication history for this paper can be accessed here: Acknowledgement This research was funded by the U.S. National Library of Medicine. The Hedges Team who did the data collection, entry, and verification included Nancy Bordignon, Angela Eady, Brian Haynes, Susan Marks, Ann McKibbon, Doug Morgan, Cindy Walker Dilks, Stephen Walter, Nancy Wilczynski, and Sharon Wong. Catherine Arnot Smith provided the second review methods for inter-rater agreement. Figures and Tables Table 1 Journal Title with number of Original and Review Qualitative Studies for 2000 Journal Title Number of Qualitative Studies Journal of Advanced Nursing 88 Social Science and Medicine 34 Qualitative Health Research 30 Journal of Clinical Nursing 22 Western Journal of Nursing Research 15 Cancer Nursing 14 BMJ 12 Research in Nursing and Health 12 Midwifery 10 Public Health Nursing 10 Family Practice 9 ANS Advances in Nursing Science 8 British Journal of General Practice 8 Heart and Lung 8 Journal of Nursing Scholarship 8 Patient Education and Counseling 8 Journal of Pediatric Nursing 6 Clinical Nursing Research 5 Journal of Family Practice 5 Journal of General Internal Medicine 5 Birth 4 Health Education and Behavior 4 Archives of Pediatrics and Adolescent Medicine 3 Canadian Journal of Nursing Research 3 Canadian Journal of Public Health 3 Journal of Pediatric and Oncology Nursing 3 Neonatology Review 3 Pediatrics 3 Qualitative Health Care 3 Applied Nursing Research 2 Psychiatric Services 2 Addiction 1 American Journal of Psychiatry 1 American Journal of Public Health 1 Annals of Emergency Medicine 1 Annals of Internal Medicine 1 Archives of Physical Medicine and Rehabilitation 1 Australian and New Zealand Journal of Psychiatry 1 BJOG (British Journal of Obstetrics and Gynaecology) 1 British Journal of Psychiatry 1 CMAJ (Canadian Medical Association Journal) 1 Diabetes Care 1 Fertility and Sterility 1 International Journal of Geriatric Psychiatry 1 Journal of Epidemiology and Community Health 1 Journal of Psychosomatic Medicine 1 Nursing Research 1 Western Journal of Medicine 1 Table 2 Top Health Care Journals with SCI Impact Factor for 2000 and Number of Qualitative Studies Journal Title SCI Impact Factor Qualitative Studies New England Journal of Medicine 29.521 0 JAMA 15.402 0 Archives of General Psychiatry 11.778 0 Circulation 10.893 0 Lancet 10.232 0 Annals of Internal Medicine 9.833 1 Annals of Neurology 8.480 0 Journal of the American College of Cardiology 7.082 0 Psychological Bulletin 6.913 0 Arthritis and Rheumatism 6.841 0 American Journal of Psychiatry 6.577 1 Archives of Internal Medicine 6.055 0 American Journal of Medicine 5.960 0 American Journal of Respiratory and Critical Care Medicine 5.443 0 Gut 5.386 0 BMJ 5.331 12 Hypertension 5.311 0 Diabetes Care 4.992 1 Journal of Infectious Diseases 4.988 0 Table 3 Content for Qualitative Studies (n = 355), Mixed Methodology Studies (n = 37), and Studies from Nursing Journals (n = 211) Category All studies % All studies # Mixed Methods % Mixed Methods # Nursing Journals % Nursing Journals Groups studied Patients 198 56 17 45 114 54.0 Family 78 22 9 24 52 24.6 Nurses 73 21 6 16 55 26.1 Other People 49 14 0 0 48 22.7 Physicians 38 11 8** 21 9* 4.3* Other Health Care Professionals 20 6 1 3 12 5.7 Settings Home or non institution 155 44 16 42 100 47.4 Hospital 87 25 10 26 65 30.1 Clinic 62 17 7 18 16* 7.6* Community 48 14 7 18 36 17.1 Nursing Home 19 5 2 5 13 6.2 Emergency Dept 6 2 1 3 2 0.9 Church, Jail, Other 5 1 2 5 2 0.9 Disease/Condition Various 38 11 3 8 19 9.0 Cancer 40 11 5 13 28 13.2 Mental Health 38 10 3 8 26 12.3 Pregnancy/birth 33 9 3 8 16 7.6 Cerebrovascular Disease 34 10 2 5 22 10.4 General Health 33 9 2 5 17 8.1 Frail Elderly 29 8 3 8 21 10.0 HIV/AIDS 21 6 3 8 11 5.2 Drugs/Sex Trade 13 4 2 5 7 3.3 Death and Dying 13 3 0 0 7 3.3 Diabetes 9 3 2 5 4 1.9 Critical Care 8 2 1 3 8 3.8 Injury 7 2 5* 13 5 2.4 Asthma 6 2 1 3 0 0 Pain 7 2 1 3 3 1.4 Smoking 4 1 1 3 2 0.9 Miscellaneous disease/conditions 41 12 5 13 26 12.3 *P < 0.001 **P < 0.025. Note that totals do not add to 100% because studies often included several methods, settings, diseases, or populations. Table 4 Methodologic Analysis of the Qualitative Studies (n = 355), Mixed Methods (n = 37), and Nursing Journals (n = 211) Category # All studies % All studies # Mixed Methods % for Mixed Methods # Nursing Journals % Nursing Journals Analysis Type Phenomenology 131 37 14 37 87 41.2 Grounded Theory 124 35 10 26 74 35.1 Ethnography 64 18 8 21 33 15.6 Case Studies 24 7 5 13* 9 4.3** Narratives 21 6 2 5 12 5.7 Participatory 13 4 0 0 10 4.7 Critical Incident Technique 4 1 0 0 3 1.4 Discourse Analysis 4 1 0 0 3 1.4 Data Collection Semi-structured Interviews 272 77 27 71 167 79.1 Observation 64 18 6 16 37 17.5 Focus Groups 50 14 5 13 31 14.7 Questionnaires 25 7 9*** 24 14 6.6 Documents 23 6 2 5 11 5.2 Unstructured Interviews 13 4 1 3 10 4.7 Structured Interviews 2 1 0 0 2 0.9 * P < 0.001 **P < 0.025 *** P < 0.01 ==== Refs Miller WL Crabtree BF Denzin N K and Lincoln Y S Clinical research Handbook of Qualitative Research 2001 2nd Thousand Oaks, CA, Sage Publications 607 631 Creswell JW Fetters MD Ivankova NY Designing a mixed methods study in primary care Annals of Family Medicine 2004 2 7 12 15053277 10.1370/afm.104 Jolly K Bradley F Sharp S Smith H Mant D Follow-up care in general practice of patients with myocardial infarction or angina pectoris: initial results of the SHIP trial. Southampton Heart Integrated Care Project Fam Pract 1998 15 548 555 10078796 10.1093/fampra/15.6.548 Wiles R Patients' perceptions of their heart attack and recovery: the influence of epidemiological "evidence" and personal experience Soc Sci Med 1998 46 1477 1486 9665577 10.1016/S0277-9536(97)10140-X Willms DG A new stage, a new life: individual success in quitting smoking Soc Sci Med 1991 33 1365 1371 1776050 10.1016/0277-9536(91)90280-P Gilbert JR Wilson DM Best JA Taylor DW Lindsay EA Singer J Willms DG Smoking cessation in primary care. A randomized controlled trial of nicotine-bearing chewing gum J Fam Pract 1989 28 49 55 2643672 Willms GG Best JA W Taylor D A systematic approach for using qualitative methods in primary prevention research Medical Anthropology Quarterly 1990 4 391 409 Borkan JM Quirk M Sullivan M Finding meaning after the fall: injury narratives from elderly hip fracture patients Soc Sci Med 1991 33 947 957 1745919 10.1016/0277-9536(91)90265-E Donovan J Mills N Smith M Brindle L Jacoby A Peters T Frankel S Neal D Hamdy F Quality improvement report: Improving design and conduct of randomised trials by embedding them in qualitative research: ProtecT (prostate testing for cancer and treatment) study. Commentary: presenting unbiased information to patients can be difficult.[see comment] BMJ 2002 325 766 770 12364308 10.1136/bmj.325.7367.766 Rousseau N McColl E Newton J Grimshaw J Eccles M Practice based, longitudinal, qualitative interview study of computerised evidence based guidelines in primary care.[see comment] BMJ 2003 326 314 12574046 10.1136/bmj.326.7384.314 Eccles M McColl E Steen N Rousseau N Grimshaw J Parkin D Purves I Effect of computerised evidence based guidelines on management of asthma and angina in adults in primary care: cluster randomised controlled trial.[see comment] BMJ 2002 325 941 12399345 10.1136/bmj.325.7370.941 Haynes RB ACP Journal Club: Purpose and procedure Haynes RB Wilczynski N McKibbon KA Walker CJ Sinclair JC Developing optimal search strategies for detecting clinically sound studies in MEDLINE J Am Med Inform Assoc 1994 1 447 458 7850570 Giacomini MK Cook DJ Users' guides to the medical literature: XXIII. Qualitative research in health care B. What are the results and how do they help me care for my patients? Evidence-Based Medicine Working Group JAMA 2000 284 478 482 10904512 10.1001/jama.284.4.478 Giacomini MK Cook DJ Users' guides to the medical literature: XXIII. Qualitative research in health care A. Are the results of the study valid? Evidence-Based Medicine Working Group JAMA 2000 284 357 362 10891968 10.1001/jama.284.3.357 Denzin NK Lincoln YS Handbook of Qualitative Research 2001 2nd Thousand Oaks, CA, Sage Publications Tongprateep T The essential elements of spirituality among rural Thai elders J Adv Nurs 2000 31 197 203 10632809 10.1046/j.1365-2648.2000.01212.x Creswell JW Research Design: Qualitative, Quantative and Mixed Methods Approaches 2003 2nd Thousand Oaks, CA, Sage Publications

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==== Front Cardiovasc DiabetolCardiovascular Diabetology1475-2840BioMed Central London 1475-2840-3-81527293210.1186/1475-2840-3-8Original InvestigationCiprofibrate therapy in patients with hypertriglyceridemia and low high density lipoprotein (HDL)-cholesterol: greater reduction of non-HDL cholesterol in subjects with excess body weight (The CIPROAMLAT study) Aguilar-Salinas Carlos A 1caguilarsalinas@yahoo.comAssis-Luores-Vale Andréia 2caasal@prodigy.net.mxStockins Benjamín 3bstockins@yahoo.comRengifo Hector Mario 4hrengifo@hotmail.comFilho José Dondici 5jfilho@yahoo.comNeto Abrahão Afiune 6aneto@incor.usp.brRabelo Lísia Marcílio 7lrabelo@yahoo.comTorres Kerginaldo Paulo 8ktorres@netscape.netOliveira José Egídio Paulo de 9jegpd@hotmail.comMachado Carlos Alberto 10cmachado@yahoo.comReyes Eliana 11ereyes@hotmail.comSaavedra Victor 12caasal@prodigy.net.mxFlorenzano Fernando 13fflorenzano@yahoo.comHernández Ma Victoria 14vhernandez@hotmail.comJiménez Sergio Hernandez 1sergio.hernandez@yahoo.comRamírez Erika 1erimoguel@hotmail.comVazquez Cuauhtémoc 15cuvacha@prodigy.net.mxSalinas Saul 15asolisia@prodigy.net.mxHernández Ismael 16ismael.hernandez@yahoo.comMedel Octavio 16omedel@prodigy.net.mxMoreno Ricardo 17rmoreno@hotmail.comLugo Paula 18Paula.lugo@yahoo.comAlvarado Ricardo 19ricardoalvarado@yahoo.comMehta Roopa 1rhoopa.mehta@yahoo.comGutierrez Victor 20caasal@prodigy.net.mxGómez Pérez Francisco J 1fgomezp@prodigy.net.mx1 Departamento de Endocrinología y Metabolismo. Instituto Nacional de la Nutrición, México City, Mexico2 Hospital Socor. Dept° de Aterosclerose. Rua Tupis, 1540 – 1° andar – Barro Preto – Belo Horizonte/MG-30190-062, Brazil3 Universidad De La Frontera. Departamento Medicina Interna. Av. Francisco Salazar 01145 Temuco-Chile4 Centro Médico del Pacífico. Departamento de Endocrinología. Calle 5B No. 42-16. Cali – Colombia5 CINDI – Centro de Investigações Diagnósticas Ltda. Dept° de Cardiologia. Rua Rei Alberto, 196 – Centro – Juiz de Fora/MG – 36016-300, Brazil6 Hospital São Salvador. Dept° de Cardiologia. Avenida A, 333 – Setor Oeste – Goiânia/GO – 74110-020, Brazil7 Fundação Baiana de Cardiologia. Dept° de Lípides. Rua Augusto Viana, S/N° – Canela – Salvador/BA – 40140-060, Brazil8 Prócardio. Dept° de Aterosclerose. Avenida Nascimento de Castro, 1930 – Lagoa Nova – Natal/RN – 59056-450, Brazil9 Hospital Universitário Clementino Fraga Filho. Dept° de Diabetes/Nutrição. Avenida Brigadeiro Trompowiski, S/N° – Ilha do Fundão – Rio de Janeiro/RJ – 21941-590, Brazil10 Centro de Referência de Hipertensão Arterial Diabetes e Apoio à Saúde do Idoso Dept° de Centro de Referência em Dislipidemia Rua Doutor Clementino, 200 – Belém – São Paulo/SP – 03059-030, Brazil11 Hospital Dipreca. Unidad de Asistencia Nutricional Intensiva.División Medicina Interna Vital Apoquindo 1200. Las Condes.Santiago. Chile12 Consulta Privada. Guardia Vieja 181 of. 405. Providencia. Santiago-Chile13 Hospital Del Salvador. Sección Cardiología. Av. Salvador 364. Providencia. Santiago-Chile14 Hospital Fuerza Aérea De Chile. Unidad De Cardiología.Av. Las Condes 8631. Las Condes Santiago-Chile15 Hospital de Cardiología del Centro Médico Nacional Siglo XXI (IMSS).Depto. de Estudios Metabólicos y Clínica de Lípidos.Av. Cuauhtemoc No. 330 Col Doctores.México, D. F16 Hospital Juárez de México (SSA).Unidad Coronaria.Av. Instituto Politécnico Nacional 5160 Col Magdalena de las Salinas.México, D. F17 Hospital General Regional No. 72 (IMSS).Terapia Intensiva.Filiberto Gómez S/N y Vía Gustavo Baz.Tlalnepantla, Edo. de México, Mexico18 Centro Médico Nacional de Occidente (IMSS).Departamento de Cardiología.Belisario Domínguez sin número Col. Centro.Guadalajara, Jal, Mexico19 Hospital Dr. Santiago Ramón y Cajal (ISSSTE). Departamento de Cardiología Predio Canoa S/N Col. Los Angeles. Durango, Dgo, Mexico20 Asociación De Diabéticos De Chile. Quebec 496. Santiago-Chile2004 23 7 2004 3 8 8 22 4 2004 23 7 2004 Copyright © 2004 Aguilar-Salinas et al; licensee BioMed Central Ltd.2004Aguilar-Salinas et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background Hypertriglyceridemia in combination with low HDL cholesterol levels is a risk factor for cardiovascular disease. Our objective was to evaluate the efficacy of ciprofibrate for the treatment of this form of dyslipidemia and to identify factors associated with better treatment response. Methods Multicenter, international, open-label study. Four hundred and thirty seven patients were included. The plasma lipid levels at inclusion were fasting triglyceride concentrations between 1.6–3.9 mM/l and HDL cholesterol ≤ 1.05 mM/l for women and ≤ 0.9 mM/l for men. The LDL cholesterol was below 4.2 mM/l. All patients received ciprofibrate 100 mg/d. Efficacy and safety parameters were assessed at baseline and at the end of the treatment. The primary efficacy parameter of the study was percentage change in triglycerides from baseline. Results After 4 months, plasma triglyceride concentrations were decreased by 44% (p < 0.001). HDL cholesterol concentrations were increased by 10% (p < 0.001). Non-HDL cholesterol was decreased by 19%. A greater HDL cholesterol response was observed in lean patients (body mass index < 25 kg/m2) compared to the rest of the population (8.2 vs 19.7%, p < 0.001). In contrast, cases with excess body weight had a larger decrease in non-HDL cholesterol levels (-20.8 vs -10.8%, p < 0.001). There were no significant complications resulting from treatment with ciprofibrate. Conclusions Ciprofibrate is efficacious for the correction of hypertriglyceridemia / low HDL cholesterol. A greater decrease in non-HDL cholesterol was found among cases with excess body weight. The mechanism of action of ciprofibrate may be influenced by the pathophysiology of the disorder being treated. CiprofibrateobesityHDL cholesteroltriglyceridesfibrates ==== Body Background Hypertriglyceridemia in combination with abnormally low concentrations of HDL cholesterol (High Density Lipoprotein Cholesterol) is one of the most common and atherogenic profiles of lipid metabolism [1]. In the PROCAM study [2], the 6-year incidence of coronary events in men aged between 40 and 60 years, was twelve times higher than in the control group. The prevalence of this abnormality varies among ethnic groups [3]. It is found in 13% of the Mexican adults living in urban areas [4]. It is more common in men than in women (20.9% vs 7.2%) and in some age groups (i.e. men aged 30 to 39 years) this prevalence is as high as 30%. This lipid profile is the most frequent form of dyslipidemia in the metabolic syndrome [5]. However it is also found in subjects affected by primary dyslipidemias (e.g familial combined hyperlipidemia). In the Veteran Affairs HDL Intervention Trial (VAHIT), the use of a fibrate (gemfibrozil) resulted in a 22% reduction in the incidence of cardiovascular events in subjects with low HDL cholesterol and a broad range of triglyceride values [6]. The benefit was accounted for by the positive effects obtained in cases with insulin resistance [7]. In spite of these positive results, there are few studies assessing the efficacy of other fibrates in the treatment of this form of dyslipidemia [8]. Relevant data such as the percentage of cases that achieve treatment goals are not described in the majority of these reports. Also, variables predicting a greater likelihood of achieving treatment goals remain to be identified. Our objective was to assess the efficacy and safety of ciprofibrate (100 mg/day) for the treatment of cases with hypertriglyceridemia / hypoalphalipoproteinemia in an open label, multicenter, international study. A clinically oriented approach is used for the description of the results. Materials and Methods The trial included men and post-menopausal or non-pregnant women aged between 30 and 70 years who had hypertriglyceridemia (fasting concentrations between 1.68–3.9 mM/l (150 – 350 mg/dl) and hypoalphalipoproteinemia (HDL cholesterol ≤ 1.05 mM/l (40 mg/dl) for women and ≤ 0.92 mM/l (35 mg/dl) for men). The LDL cholesterol had to be lower than 4.2 mM/l (160 mg/dl). Patients were excluded if they had an acute coronary event during the three months preceding the study, type 1 diabetes, uncontrolled hypertension, severe renal dysfunction, nephrotic syndrome or aspartate aminotransferase (AST) or alanine aminotransferase (ALT) levels > 1.5 × the upper limit of normal (ULN), or if their creatine phosphokinase (CPK) levels were > 3 × ULN. Consumption of any lipid-altering drug within the previous 4 weeks (6 months for probucol) prevented entry into the study. Patients could be receiving other concomitant medication as long as the dosage was not modified during the study. The Ethics Committee in each institution approved the protocol and every patient provided witnessed, written informed consent prior to entering the study. This was a multicenter, international, open-label study. Patients were recruited from 25 lipid clinics from México (n = 152), Brazil (n = 129), Chile (n = 78) and Colombia (n = 78). Cases fulfilling the inclusion criteria were invited to participate. The initial visit included a medical evaluation, a physical examination and the prescription of an isocaloric diet consisting of 50% carbohydrate, 30% fat, 20% protein with a cholesterol content of 200 mg [9]. Blood samples were obtained after a 9–12 h fasting period. All patients were assigned to receive ciprofibrate 100 mg at bedtime. The second and final visit was scheduled 4 months later. During this visit drug compliance and safety profile were assessed and body weight as well as laboratory parameters were measured. Drug compliance was measured by counting the returned pills. Adherence to the diet was not assessed during the study The primary efficacy parameter was the percentage change in triglycerides from baseline. Secondary efficacy parameters included the percentage change in total cholesterol, HDL cholesterol and non-HDL cholesterol from baseline. Non-HDL cholesterol was calculated by subtracting the HDL cholesterol from the total cholesterol levels. In a post hoc analysis, the percentage of cases that achieved the treatment goals proposed by the ATP-III recommendations [10] on the final visit was also estimated. At each visit, AST, ALT, fasting plasma glucose and CPK levels were measured. Clinically relevant complications were defined as either CPK > 5 × ULN accompanied by muscle pain, tenderness or weakness or ALT or AST > 3 × ULN. Patients were excluded from the study if they developed severe hyperglycemia or any other significant complication to treatment. Other reasons for premature withdrawal were lack of compliance to the medication. Cases were instructed to contact their physician in case of any side effect. All samples were analyzed in a central laboratory (Quest laboratories). In Brazil, the local laboratory of every center was used instead. Blood samples were taken after an overnight fast (≥ 9 hours). Measurements were performed during the first 24 hours after the blood was drawn; blood samples were kept at 4°C until the analysis. All laboratory analyses were performed with commercially available standardized methods. Glucose was measured using the glucose oxidase method. Total serum cholesterol and triglycerides levels were measured using an enzymatic method. HDL cholesterol levels were assessed using phosphotungstic acid and Mg2+. Statistical analysis was performed using SPSS for Windows version 10. An intention to treat analysis was used. Two sided ANOVA tests were used for assessing differences between groups for continuous variables. All categorical variables were analyzed using the chi squared test. Multiple logistic regression models were constructed for the identification of variables associated with the achievement of treatment goals. Results Four hundred thirty seven patients were included. The clinical characteristics of the study subjects are shown in table 1. Almost half of the population had a body mass index between 25 and 30 kg/m2 (n = 221); an additional 32.5% were obese (n = 142) Diabetes was present in 125 subjects (28.7%). Table 1 Baseline characteristics of the patients included in study (n = 437) Variable N = 437 Sex  Male (n(%)) 239 (54.7)  Female (n(%)) 198 (45.3) Age (years)* 54.7 ± 12.1 Body mass index (kg/m2) 28.8 ± 4.6 Diabetes (n(%)) 125 (28.7) Fasting plasma glucose (mM/l)* 5.2 ± 0.6 Family history of dyslipidemia (n(%)) 171 (39.2) Coronary heart disease (n(%)) 196 (45) Aspartate aminotranferase (mU/l) 23 ± 11 Alanine aminotransferase (mU/l) 26 ± 14 Data expressed as mean ± standard deviation. *To convert to mg/dl, multiply by 18 Both evaluations were completed in every case. The medication was stopped before the trial was completed by 117 subjects (26.7%). In the majority of cases this was not related to side effects (see below). In addition, 46 cases (10.5%) had poor compliance to the medication. The body weight remained constant in all patients. The alcohol and tobacco consumption was not modified during the study. Ciprofibrate treatment and diet had a significant beneficial effect on the lipid profile, as shown in table 2. After 4 months of treatment, plasma triglyceride concentrations were decreased by 44% (p < 0.001). HDL cholesterol concentrations were increased by 10.1% (p < 0.001). Non-HDL cholesterol was decreased by 19.2% (p < 0.001). Total cholesterol was also favorably modified (-14.9%, p < 0.001). In contrast, LDL cholesterol had a minor modification (-5.4%, p < 0.001). A significant decrease in fasting glycemia was observed in both obese and diabetic cases. This change was not found in lean subjects. Table 2 Changes in the lipid profile and clinical characteristics between baseline and post-treatment values Intention to treat analysis N = 437 Baseline Final Percent change Triglycerides (mM/l) † 3.01 ± 0.7 1.61 ± 0.8 -44 ± 33* HDL Cholesterol (mM/l)‡ 0.91 ± 0.1 0.98 ± 0.4 10 ± 52* Non-HDL cholesterol (mM/l)‡ 4.57 ± 0.9 3.61 ± 1.5 -19 ± 36* Cholesterol (mM/l)‡ 5.5 ± 0.9 4.57 ± 1.8 -14.9 ± 35* LDL Cholesterol (mM/l)‡ 3.1 ± 0.9 2.8 ± 1.3 -5.4 ± 59* Mean ± standard deviation are presented. *p < 0.001 †To convert to mg/dl multiple by 89 ‡To convert to mg/dl multiple by 38 The achievement of treatment goals is the ultimate aim of lipid-lowering therapy. Almost half of the cases had reduced their triglyceride concentrations below 1.68 mM/l (150 mg/dl) (n= 191(43.7%). HDL cholesterol levels above 1.05 mM/l (40 mg/dl) were found in 51% of the cases (n = 223). Also, a significant proportion of the subjects (63.15%, n = 276) achieved the non-HDL cholesterol goal 4.2 mM/l (< 160 mg/dl). The LDL cholesterol goal < 3.4 mM/l (< 130 mg/dl) was attained by 56.2 % (n = 246). A full correction of the hypertrigliceridemia / low HDL cholesterol occurred in 129 subjects (29.5%). Many of them also had a non-HDL cholesterol level below 4.2 mM/l (160 mg/dl) (n = 101, 23.1%) The lipid response during treatment differed between cases with a body mass index above or below 25 kg/m2. As is shown in figure 1, the percentage change in HDL cholesterol was higher in lean subjects. In contrast, the non-HDL cholesterol concentration had a significantly greater reduction among subjects with excess body weight. Both differences remained significant even after adjusting for age and gender. The lipid profile did not differ between these groups during the initial visit. Figure 1 The percentage of change in the lipid parameters is different in cases with a body mass index above 25 kg/m2 compared to the response observed in lean individuals during treatment with ciprofibrate and diet. Patients with diabetes had moderate hyperglycemia during the study. Their fasting glycemia was 7.7 ± 2.6 mM/l (139 ± 47 mg/dl) at baseline. A small but statistically significant decrease in glucose concentration was observed at the end of the trial (5.7 ± 3 mM/l, 104 ± 54 mg/dl p < 0.001). At baseline, their lipid profile differed, from the non-diabetic subjects, only with regards to higher triglyceride concentrations (3.13 ± 0.97 vs 2.95 ± 0.66 mM/l, p < 0.001). The lipid response to ciprofibrate and dietary treatment did not differ from that observed in the whole group. Individuals with a family history of dyslipidemia (n = 171) had higher cholesterol, triglycerides and LDL cholesterol at baseline compared to the rest of the population. The lipid response to treatment was similar to that reported in the whole group. Multiple regression models were constructed to identify variables associated with the achievement of the treatment goals. For every target value, the main determinants were the baseline value and the percentage change after treatment. No other parameter provided additional information in any of the models. Thus, we analyzed the variables associated with the percentage change during treatment. The non-HDL cholesterol model provided more information compared to models derived from the other lipid parameters. In the non-HDL cholesterol model, a body mass index greater than 25 kg/m2, the triglyceride response and the coexistence of cholesterol above 5.2 mM/l (200 mg/dl) (mixed hyperlipidemia) were predictors for a greater non-HDL cholesterol response (table 3). For both, the HDL cholesterol and the triglycerides models, the inclusion of a body mass index < 25 kg/m2 added little information and had only borderline statistical significance. No other clinically relevant variable was associated with the percentage change of any other lipid parameter. Table 3 Multiple regression model using as dependent variable percent of change in non-HDL cholesterol concentration Variable Beta coefficient ± standard error p value Constant 14.4 ± 2.6 < 0.001 BMI < 25 kg/m2 7.6 ± 3.6 0.036 Mixed hyperlipidemia 0.82 ± 0.2 0.003 Percent of change of triglycerides 0.68 ± 0.4 < 0.001 Correlation coefficient = 0.647, r2 = 0.419, p = 0.001 BMI, Body mass index Liver function tests were not modified by the treatment. No patient had a significant alteration of any of the laboratory tests. There were no incidents of either myopathy or liver dysfunction. No persistent elevations in ALT, AST or CPK, defined as clinically relevant, were reported during the course of the study. Discussion The combination of hypertriglyceridemia / low HDL cholesterol is a common abnormality of lipoprotein metabolism and is associated with increased cardiovascular risk. Our data show that ciprofibrate and an isocaloric diet are an effective treatment for this dyslipidemia. However, there was significant variation in response to treatment between individuals. Excess body weight may be an important determinant of the lipid response. It is associated with a greater degree of non-HDL cholesterol reduction and a relatively smaller elevation in HDL cholesterol. A significant improvement in plasma triglycerides and HDL cholesterol concentrations resulted from the administration of ciprofibrate and dietary modifications. Our results are in agreement with previous studies [11-15]. This study differs from previous reports due to its design. We wanted to assess the lipid response to ciprofibrate in a real life environment. Hence, the highly controlled conditions of a randomized, double blind study were avoided. Also, we limited our inclusion criteria to subjects with hypertriglyceridemia / low HDL cholesterol, instead of including subjects with a wide variety of lipid profiles. The results are in accordance with the uncontrolled design of the study. By the use of ciprofibrate and isocaloric diet, almost half of the cases achieved the triglyceride goal (1.68 mM/l, 150 mg/dl). HDL cholesterol levels above 40 mg/dl were found in 51% of the cases. The full correction of the combination of hypertriglyceridemia / low HDL cholesterol occurred in a third of the population. This rate is similar to that reported for the LDL cholesterol goals achieved by the use of statins. Thus, our results reflect the strengths and limitations of treating this lipid abnormality in an uncontrolled setting. A large range of lipid responses was observed between individuals. There are few reports designed to analyse the determinants of the lipid response to fibrates. Robins reported a lower HDL cholesterol elevation with a fibrate when insulin resistance is present [7]. In this report, a lower HDL cholesterol response was observed in patients with excess body weight (body mass index above 25 kg/m2) in comparison to that found in lean individuals. Since excess body weight is strongly associated with insulin resistance [16,17], our observations may be in agreement with the findings of Robins. Interestingly, the presence of insulin resistance was associated with the lowest incidence of coronary events in the VAHIT study. In our report, obese individual had a larger decrease in non-HDL cholesterol levels. The greater response in non-HDL cholesterol observed in our obese (and possibly insulin resistant) subjects may be one possible explanation for the greater benefit found in insulin resistant subjects during the VAHIT study. Our data suggest that the mechanism of action of ciprofibrate may be altered by the pathophysiology of the disorder being treated. The same phenomenon has been observed with the use of statins [18,19]. The greater reduction in non-HDL cholesterol in subjects with excess body weight could be explained by an increased clearance of remnants, IDL and VLDL particles. Ciprofibrate may enhance their clearance either by decreasing the concentration of the apolipoprotein CIII (an inhibitor of the lipolytic activity of the lipoprotein lipase) [20-22] or by increasing the mass and activity of lipoprotein lipase [23]. Genes encoding apolipoprotein CIII and lipoprotein lipase contain a PPAR-alpha response element; hence their expression may be modified during treatment with a fibrate [24]. Additional studies are needed to identify other possible determinants of the lipid response to treatment with a fibrate. Several limitations of the study must be recognized. The uncontrolled design resulted in a relatively high rate of drug discontinuation. However, this phenomenon is a common finding in studies done in open populations assessing the adherence to different lipid-lowering medications [25]. To overcome this limitation, an intention to treat analysis was used. Also, the lack of a run-in period in which the effect of diet could be measured and the absence of information about the adherence to the diet prevented us from discerning to what extent the observed result was due to fibrate alone. Finally, some of the conclusions, like the identification of the determinants of the lipid response, came from a post hoc analysis. In conclusion, ciprofibrate is effective in the treatment of patients with hypertriglyceridemia / low HDL cholesterol. Significant reductions in triglycerides and non-HDL cholesterol resulted from ciprofibrate therapy. In addition, higher HDL cholesterol levels were found at the end of the treatment. Excess body weight alters the lipid response to ciprofibrate. A greater non-HDL cholesterol lowering is achieved in subjects with excess body weight compared to that found in lean individuals. Controlled trials are needed to compare the lipid-lowering effects of ciprofibrate in groups of subjects defined by their adiposity or other markers of insulin resistance. Competing interests This study was supported by an educational grant provided by Sanofi-Synthelabo. It included the study expenses and it will cover the article processing charge. No other competing interest need to be declared Author contributions CAAS participated in the design of the study, performed the statistical analysis and drafted the manuscript. AALV participated in the design of the study and in the preparation of the manuscript. FJGP participated in the design of the study and in the preparation of the manuscript. All other authors were responsible of the inclusion and follow-up of the study subjects. All authors read and approved the final manuscript. Acknowledgments This study was supported by an unrestricted grant from SANOFI-Synthelabo ==== Refs Jeppesen J Hein HO Suadicani P Gyntelberg F High triglycerides/low high density lipoprotein cholesterol, ischemic electrocardiogram changes, and risk of ischemic heart disease Am Heart J 2002 145 103 108 12514661 10.1067/mhj.2003.45 Assmann G Schulte H Cullen P New and classical risk factors – The Munster heart study (PROCAM) Eur J Med Res 1997 2 237 242 9182651 Stong K Bonita R the SuRF Report1 Surveillance of risk factors related to non-communicable diseases: Current status of global data 2003 Geneva, World Health Organization Aguilar-Salinas CA Olaiz G Valles V Ríos JM Gómez Pérez FJ Rull JA Rojas R Franco A Sepúlveda J High prevalence of low HDL cholesterol concentrations and mixed hyperlipidemia in a Mexican nation wide survey J Lipid Res 2001 42 1298 1307 11483632 Groop L Orho-Melander M The dysmetabolic syndrome J Intern Med 2001 250 105 120 11489060 10.1046/j.1365-2796.2001.00864.x Bloomfield Rubins H Robins SJ Collins D Fye CL Anderson JW Elam MB Faas F Linares E Schaefer EJ Schectman G Wilt T Wittes J for the Veterans Affairs High-Density Lipoprotein Cholesterol Intervention Trial Study Group Gemfibrozil for the secondary prevention of coronary heart disease in men with low levels of high density lipoprotein cholesterol. Veterans Affairs High – Density Lipoprotein Cholesterol Intervention Trial Study Group N Engl J Med 1999 341 410 418 10438259 10.1056/NEJM199908053410604 Robins S Bloomfield Rubins H Faas F Schaefer E Elam M Anderson J Collin D on behalf of the VA-HIT Study Group Insulin resistance and cardiovascular events with low HDL cholesterol Diabetes Care 2003 26 1513 1517 12716814 Faergeman O Hypertriglyceridemia and the fibrate trials Curr Opin Lipidol 2000 11 609 614 11086334 10.1097/00041433-200012000-00007 Betteridge DJ Khan M Review of the guidelines for management of dislipidemia Baillieres Clin Endocrinol Metab 1995 9 867 890 8593129 Expert panel on detection, evaluation and treatment of high blood cholesterol in adults Executive summary of the third report of the National Cholesterol Education Program (NCEP) Expert panel on detection, evaluation and treatment of high cholesterol in adults (adult treatment panel III) JAMA 2001 285 2486 2497 11368702 Cattin L Da Col PG Feruglio FS Finazzo L Rimondi S Descovich G Manzato E Zambon S Crepaldi G Siepi D Efficacy of ciprofibrate in primary type II and IV hyperlipidemia: the Italian Multicenter Study Clin Ther 1990 12 482 488 2289217 Betteridge DJ Ciprofibrate: a profile Postgrad Med J 1993 69 S42 S47 8497456 Bruckert E Dejager S Chapman MJ Ciprofibrate therapy normalizes the atherogenic low density lipoprotein subspecies profile in combined hyperlipidemia Atherosclerosis 1993 100 91 102 8318067 Goa K Barradell L Plosker G Bezafibrate Drugs 1996 52 725 753 9118820 Knipscheer H de Valois C van den Ende B Wouter J Kastelin J Ciprofibrate versus gemfibrozil in the treatment of primary hyperlipidemia Atherosclerosis 1996 124 S75 S81 8831919 Ferrannini E Natali A Bell P Cavallo-Perin P Lalic N Mingrone G Insulin resistance and hypersecretion in obesity J Clin Invest 1997 100 1166 1173 9303923 Schmidt MI Duncan BB Watson RL Sharrett AR Brancati FL Heiss G A metabolic syndrome in whites and African-Americans: the Atherosclerosis Risk in Communities baseline study Diabetes Care 1996 19 414 418 8732701 Aguilar Salinas CA Barrett H Schonfeld G Metabolic modes of action of statins in hyperlipoproteinemias Atherosclerosis 1998 141 203 207 9862169 10.1016/S0021-9150(98)00198-1 Hugh P Barrett R Watts GF Kinetic studies of lipoprotein metabolism in the metabolic syndrome including effects of nutritional interventions Curr Opin Lipidol 2003 14 61 68 12544663 10.1097/00041433-200302000-00011 Shachter N Apolipoproteins C-I and C-III as important modulators of lipoprotein metabolism Curr Opin Lipidol 2001 12 297 304 11353333 10.1097/00041433-200106000-00009 Fu T Mukhopadhyay D Davidson NO Borensztajn J The PPAR alpha agonist ciprofibrate inhibits apolipoprotein B mRNA editing in LDL receptor-deficient mice: Effects on plasma lipoproteins and the development of atherosclerotic lesions J Biol Chem 2004, Apr 27 Guerin M Le Goff W Frisdal E Schneider S Milosavljevic D Bruckert E Chapman MJ Action of ciprofibrate in type IIb hyperlipoproteinemia: modulation of the atherogenic lipoprotein phenotype and stimulation of high-density lipoprotein-mediated cellular cholesterol efflux J Clin Endocrinol Metab 2003 88 3738 46 12915663 10.1210/jc.2003-030191 Gaw A Evidence based approach for the management of mixed hyperlipidemia Atherosclerosis 1998 137 S97 S100 9694548 Barbier O Torra IP Duguay Y Blanquart C Fruchart JC Glineur C Staels B Pleiotropic actions of peroxisome proliferator-activated receptors in lipid metabolism and atherosclerosis Arterioscler Thromb Vasc Biol 2002 22 717 26 12006382 10.1161/01.ATV.0000015598.86369.04 Tsuyuki RT Bungard TJ Poor adherence with hypolipidemic drugs: a lost opportunity Pharmacotherapy 2001 21 576 582 11349746 10.1592/phco.21.6.576.34541

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Cardiovasc Diabetol. 2004 Jul 23; 3:8

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Cardiovasc Diabetol

10.1186/1475-2840-3-8

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==== Front World J Surg OncolWorld Journal of Surgical Oncology1477-7819BioMed Central London 1477-7819-2-251527294010.1186/1477-7819-2-25Case ReportA unique dedifferentiated tumor of the retroperitoneum Karmali Shahzeer 1karmalis@ucalgary.caBenediktson Halligrimur 2benedikt@ucalgary.caTemple Walley 3walleyte@cancerboard.ab.caBathe Oliver F 3bathe@ucalgary.ca1 Department of Surgery, University of Calgary, Calgary, AB, Canada2 Department of Pathology, University of Calgary, Calgary, AB, Canada3 Departments of Surgery and Oncology, University of Calgary, Calgary, AB, Canada2004 23 7 2004 2 25 25 30 4 2004 23 7 2004 Copyright © 2004 Karmali et al; licensee BioMed Central Ltd.2004Karmali et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background Dedifferentiated liposarcomas represent heterogeneous tumors with lipomatous and nonlipomatous elements starkly juxtaposed. It is thought that the high grade nonlipomatous elements of the tumor portend a worse prognosis. Case Presentation A 19.8 kg heterogeneous retroperitoneal tumor was successfully and completely resected. Because of its extent, no additional treatment modalities were practicable. The tumor soon recurred. The recurrent tumor differed from the primary tumor in that it was more homogeneous, consisting mainly of nonlipogenic, calcific tissue. Conclusions Dedifferentiated liposarcomas are known to have a very high recurrence rate. The biological behavior of dedifferentiated liposarcomas is likely dictated by the most aggressive element of these heterogeneous tumors. ==== Body Background Sarcomas arising from the retroperitoneum are rare tumors, accounting for 10–15% of all soft tissue sarcomas [1]. Liposarcoma is the single most common soft tissue sarcoma and accounts for at least 20% of all sarcomas in adults [1]. Classification of liposarcoma into four types, based on morphologic features and cytogenic aberrations, is now widely accepted [2]. These four types are (a) well differentiated; (b) dedifferentiated; (c) myxoid/round cell and (d) pleomorphic. The extent of differentiation, as reflected by histological grade, remains the most important determinant of clinical course and of ultimate prognosis for patients with liposarcoma after resection. The following case illustrates the great morphological and biological heterogeneity of these tumors. A very rapid recurrence was observed, and this recurrence was considerably less heterogeneous than the primary tumor, consisting mainly of the calcific, nonlipomatous component. Case presentation A 65-year-old male presented with a three-week history of progressively worsening abdominal distension. He denied any abdominal pain but stated that he noticed an increased frequency of bowel movements. His past medical history was unremarkable. On examination, he was afebrile and had a hugely distended abdomen with an immobile, nontender mass occupying all four quadrants of the abdomen. Computed tomographic (CT) scan revealed a large, heterogeneous lobulated mass occupying most of the abdomen (Figure 1). The peripheral component appeared lipomatous and the margins of this component were difficult to estimate accurately. There was also a heterogeneous nonlipomatous component that contained areas of lesser density, as well as a central stellate region of calcifications. The preoperative differential diagnosis included a retroperitoneal sarcoma (especially dedifferentiated liposarcoma), desmoid tumor, undifferentiated carcinoma, carcinoid or sclerosing mesenteritis; lymphoma was also considered. Figure 1 CT appearance at multiple cuts (A – E) of a huge retroperitoneal mass with lipomatous and nonlipomatous components. The nonlipomatous component (arrow X, Panel D) contains calcific elements. Note the posterior extension of the lipomatous component (arrow Y, Panel D), which extends superiorly (Panels A – C). The exact boundaries of this component are difficult to appreciate on CT. While neoadjuvant chemotherapy and radiation comprise a frequent approach for retroperitoneal sarcomas at our institution, the extent of the tumor made this approach unfeasible. Resection was therefore planned unless an intraoperative biopsy revealed lymphoma. Resection was accomplished through a T-type incision (Figure 2), and entailed removal of the right kidney, terminal ileum, ascending colon, sigmoid colon and the left spermatic cord structures, all of which were intimately attached to the mass. Encasement of the external iliac artery and vein was also encountered near the end of the procedure. This was not fully appreciated preoperatively, as that component of the tumor was so much less conspicuous on CT than the rest of the tumor, given its fatty consistency (Figure 1E). The mass was split in half to facilitate dissection from the iliac vessels. An anastomosis was constructed from descending colon to rectum. A transverse colon mucous fistula and an ileostomy were brought out, as the ileum was dusky at the end of the procedure. Figure 2 Operative exposure of the tumor through a T-type abdominal incision. The tumor was submitted for histological examination in two parts measuring, 30.0 × 10.0 × 6.5 cm and 32.0 × 20.0 × 10.0 cm, weighing 19.8 kg in total (Figure 3). On gross examination the mass was variegated, with fleshy and solid cystic degeneration containing areas of osseous consistency. Microscopic examination revealed a juxtaposition of well differentiated liposarcoma and a spindle cell sarcoma with heterologous chondrosarcomatous elements consistent with a dedifferentiated liposarcoma (Figure 4). Figure 3 En bloc resection specimen of heterogeneous tumor with attached organs. Note the lipomatous regions (A), the calcified areas (B), and the remaining nonlipomatous component (C). Figure 4 Histologic appearance of various elements of the tumor as sampled in different regions. A. Well differentiated liposarcoma. B. Low grade spindle cell component. C. Cellular spindle cell component. D. Chondrosarcomatous component. The patient was discharged from hospital on the seventh postoperative day. He was followed in the surgical oncology outpatient clinic monthly. Four months after resection the patient had a follow-up CT scan, which demonstrated an intra-abdominal recurrence consisting almost completely of a calcified, nonlipomatous tumor (Figure 5). The patient died one month later. Figure 5 CT appearance at multiple cuts (A – D) of the recurrent tumor. The recurrence was more homogeneous than the primary tumor, consisting almost completely of the calcific component of the nonlipomatous portion of the tumor. Discussion The patient in our case manifested the dedifferentiated variant of liposarcoma. The term "dedifferentiated liposarcoma" refers to the development of a high grade nonlipogenic sarcoma juxtaposed to a well differentiated liposarcoma [3]. The majority (80 – 90%) occur primarily de novo, although secondary dedifferentiation can occur with multiple recurrences of a well differentiated liposarcoma [4]. CT and Magnetic resonance imaging scans typically reveal well defined nonlipomatous masses associated with fatty tumor; the transition between the two components is characteristically abrupt, although blended transitions are seen in about 20% of cases [5]. Calcifications appear in about 30% and usually correspond to osseus metaplasia, although they may represent osteosarcomatous or chondrosarcomatous elements. The most frequent phenotype of dedifferentiation is that of a high grade pleomorphic malignant fibrous histiocytoma-like sarcoma [4,6]. Other phenotypes observed include leiomyosarcomatous, rhabdomyosarcomatous, osteosarcomatous and angiosarcomatous elements, as well as other nonlipogenic elements [3,7]. A further distinctive pattern in some cases is the presence of micronodular spindle cell whorls, often associated with ossification [8]. Among liposarcomas, the presence of features of the dedifferentiated variant strongly portends a worse prognosis. The overall 5-year survival of dedifferentiated liposarcomas is 20%; the 5-year survival of well differentiated liposarcomas is 83% [9]. Dedifferentiated liposarcomas recur locally in 40 – 83% and distant metastases appear in 15 – 30% [4,7,9]. Therefore, histomorphologic features impact outcomes related to retroperitoneal liposarcomas. While generally the phenotype of the nonlipogenic component does not impact prognosis of dedifferentiated liposarcomas, the presence of calcifications has been identified as an adverse prognostic factor [5]. In the present situation, it is obvious that the biologically most aggressive component consisted of the calcified (chondrosarcomatous) component. That is, the recurrence was less heterogeneous than the primary tumor, as it had widespread and dense calcifications, but no obvious lipomatous elements. Complete resection of the tumor is perhaps the most important factor determining long-term survival. Unfortunately, the rate of complete respectability is only about 53% [10]. As illustrated in the present case, in addition to the limitations imposed by the retroperitoneal anatomy, another obstacle to successfully obtaining margins is the difficulty in distinguishing normal retroperitoneal fat from the lipogenic component of the tumor [9]. This was illustrated by the underestimation of the extent of the tumor around the iliac vessels. Moreover, the intraoperative decision to remove the kidney was made in view of the difficulty in distinguishing normal perinephric fat and neoplastic fat; kidney was not involved with tumor, once examined microscopically. Indeed, in a series of retroperitoneal liposarcomas from Memorial Sloan-Kettering Cancer Center, nephrectomy was performed in 38% of patients, although the number in which kidney was actually involved on pathology was not reported [9]. Thus, anatomical constraints and difficulty distinguishing more differentiated fatty tumor from normal fat limit the surgeon's ability to confidently and completely remove all neoplastic elements. Conclusions Dedifferentiated liposarcomas represent aggressive variants of liposarcomas. Each morphological element of these heterogeneous tumors may manifest completely different biology. The overall biological behavior of dedifferentiated liposarcomas is likely dictated by the most aggressive element, which typically resides in the nonlipomatous portion of the tumor. Competing Interests None declared. Authors Contributions SK, HB, WT, and OB made substantial contributions to the intellectual content of the paper, in the interpretation of data, and in drafting the manuscript. All authors read and approved the final manuscript. Acknowledgements Written consent was obtained from the patient's relatives for publication of this study. ==== Refs Brady MS Brennan MF allen-Mersh TG Soft tissue sarcoma Surgical Oncology 1996 Longon: Chapman and Hall 401 20 Fletcher CD Akerman M Dal Cin P de Wever I Mandahl N Mertens F Mitelman F Rosai J Rydholm A Sciot R Tallini G van den Berghe H van de Ven W Vanni R Willen H Correlation between clinicopathological features and karyotypes in lipomatous tumors Am J Pathol 1996 148 623 630 8579124 Nascimento AG Dedifferentiated liposarcoma Semin Diagn Pathol 2001 18 263 266 11757866 Henricks WH Chu YC Goldblum JR Weiss SW Dedifferentiated liposarcoma: A clinicopathological analysis of 155 cases with a proposal for an expanded definition of dedifferentiation Am J Surg Pathol 1997 21 271 281 9060596 10.1097/00000478-199703000-00002 Tateishi U Hasegawa T Beppu Y Satake M Moriyama N Primary dedifferentiated liposarcoma of the retroperitoneum. Prognostic significance of computed tomography and magnetic resonance imaging features J Comput Assist Tomogr 2003 27 799 804 14501373 10.1097/00004728-200309000-00019 Coindre JM Mariani O Chibon F Mairal A De Saint Aubain Somerhausen N Favre-Guillevin E Bui NB Stoeckle E Hostein I Aurias A Most malignant fibrous histiocytomas developed in the retroperitoneum are dedifferentiated liposarcomas: A review of 25 cases initially diagnosed as malignant fibrous histiocytoma Mod Pathol 2003 16 256 262 12640106 10.1097/01.MP.0000056983.78547.77 McCormick D Mentzel T Beham A Fletcher CD Dedifferentiated liposarcoma: clinicopathologic analysis of 32 cases suggesting a better prognostic subgroup among the pleomorphic sarcomas Am J Surg Pathol 1994 18 1213 1223 7977944 Nascimento AG. Kurtin PJ Guillou L Fletcher CD Dedifferentiated liposarcoma: a report of nine cases showing a peculiar neural-like (whirling) pattern associated with metaplastic bone formation Am J Surg Pathol 1998 22 945 955 9706974 10.1097/00000478-199808000-00004 Singer S Antonescu CR Riedel E Brennan MF Histologic subtype and margin of resection predict pattern of recurrence and survival for retroperitoneal liposarcoma Ann Surg 2003 238 358 371 14501502 10.1097/01.sla.0000086542.11899.38 Bevilacqua RG Rogatko A Hajdu SI Brennan MF Prognostic factors in primary retroperitoneal soft tissue sarcomas Arch Surg 1991 126 328 334 1998475

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World J Surg Oncol

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==== Front Health Res Policy SystHealth Research Policy and Systems1478-4505BioMed Central London 1478-4505-2-41527293910.1186/1478-4505-2-4ResearchProposed methods for reviewing the outcomes of health research: the impact of funding by the UK's 'Arthritis Research Campaign' Hanney Stephen R 1stephen.hanney@brunel.ac.ukGrant Jonathan 2jgrant@rand.orgWooding Steven 2wooding@rand.orgBuxton Martin J 1martin.buxton@brunel.ac.uk1 Health Economics Research Group, Brunel University, Uxbridge, Middlesex UB8 3PH, UK2 RAND Europe, Grafton House, Cambridge CB5 8DD, UK2004 23 7 2004 2 4 4 3 3 2004 23 7 2004 Copyright © 2004 Hanney et al; licensee BioMed Central Ltd.2004Hanney et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background External and internal factors are increasingly encouraging research funding bodies to demonstrate the outcomes of their research. Traditional methods of assessing research are still important, but can be merged into broader multi-dimensional categorisations of research benefits. The onus has hitherto been on public sector funding bodies, but in the UK the role of medical charities in funding research is particularly important and the Arthritis Research Campaign, the leading medical charity in its field in the UK, commissioned a study to identify the outcomes from research that it funds. This article describes the methods to be used. Methods A case study approach will enable narratives to be told, illuminating how research funded in the early 1990s was (or was not) translated into practice. Each study will be organised using a common structure, which, with careful selection of cases, should enable cross-case analysis to illustrate the strengths of different modes and categories of research. Three main interdependent methods will be used: documentary and literature review; semi-structured interviews; and bibliometric analysis. The evaluative framework for organising the studies was previously used for assessing the benefits from health services research. Here, it has been specifically amended for a medical charity that funds a wide range of research and is concerned to develop the careers of researchers. It was further refined in three pilot studies. The framework has two main elements. First, a multi-dimensional categorisation of benefits going from the knowledge produced in peer reviewed journal articles through to the health and potential economic gain. The second element is a logic model, which, with various stages, should provide a way of organising the studies. The stock of knowledge is important: much research, especially basic, will feed into it and influence further research rather than directly lead to health gains. The cross-case analysis will look for factors associated with outcomes. Conclusions The pilots confirmed the applicability of the methods for a full study which should assist the Arthritis Research Campaign to demonstrate the outcomes from its funding, and provide it with evidence to inform its own policies. ==== Body Background The growing concern for the benefits from health research to be studied Health research funding bodies are under increasing pressure to demonstrate the outcomes, or benefits, of the research that they fund [1-6]. Traditional peer review of research focussed on the outputs in terms of journal articles, the training of future researchers and the development of careers. These are still seen as important, but in some analyses they have been merged into broader multi-dimensional categorisations of the benefits from health research [7,8]. The onus hitherto has been on public sector funding bodies. There is a general recognition in the UK, however, of the importance of the role of the medical charities: they fund approximately one third of UK medical research – a level 'unparalleled elsewhere in the world and nor is it found in other areas of science' [9]. Therefore, in an era of accountability, public involvement in research issues and growing competition for contributions, some medical charities see the virtue in being able to demonstrate the outcomes of the research they fund. Not all the pressures, however, are external and some funding bodies, including the Wellcome Trust, which is an endowment and not collection-based charity, are being pro-active in their attempts to identify and track the outcomes of the research they fund. One factor relevant for both public sector and charity funding bodies is the recognition that assessing the benefits from their research may assist in identifying research strategies most likely to produce benefits [2,7,10,11]. Concerns such as those above led a UK medical charity, the Arthritis Research Campaign (ARC), to approach RAND Europe with the idea of conducting an assessment of the long-term outcomes from research that they have funded. The purpose of this paper is to set out the aims of the study and the methods being adopted. In particular, it will show how an existing generic approach to the assessment of benefits from health research [7,12] has been adapted to meet the needs of this specific study. After providing the background to the study, the paper describes the methods to be adopted. These were initially agreed after a consultative phase in which the evaluative framework was refined on the basis of interviews with six key actors who have played various roles within ARC and advice from ARC's Development Committee, which acts as the steering group for this project. They were then confirmed following a pilot stage in which three case studies were conducted; some examples from the pilot studies, which endorsed the feasibility of the proposed approach, will be given to illustrate the account of the methods. The increasing attention on musculoskeletal conditions and the role of the Arthritis Research Campaign (ARC) Attention is being drawn to the increasing scale of the burden of musculoskeletal conditions, and the associated costs, in various ways including through the establishment of the Bone and Joint Decade 2000–2010 and the recent collaborative report with the World Health Organization (WHO) [13]. At the same time, there is a realisation that the benefits of research in this area are sometimes less immediately apparent than in some other fields. For example, two classic studies of the economic benefits from biomedical research [14,15] both highlighted arthritis as an area where research and higher medical care expenditure may have comparatively little impact on mortality. Furthermore, one recent attempt to put a monetary value on the benefits from health research in Australia [16] adapted a method developed in the USA [17] and again demonstrates the difficulties of undertaking such analysis in the musculoskeletal field. These observations might suggest that a more careful and wide-reaching assessment of benefits from research is particularly needed in the field of arthritis. ARC is the leading medical charity in this field in the UK and one of the largest collection-based medical charities in the UK. The Research Outputs Database (ROD) records the funding acknowledgements on all UK biomedical papers contained on the citations indices of the Institute for Scientific Information [18]. Analysis conducted on ROD reveals ARC to be, 'in a dominant position within the UK in the arthritis subfield' [19]. ARC's funding is associated with more arthritis publications than that from either the Medical Research Council (MRC) or the Wellcome Trust. It spent almost £22 million in the year 2001–2002; its major aim 'is to support the highest quality research into the cause, cure and treatment of arthritis and musculoskeletal diseases' [20]. It adopts a variety of funding modes for a range of types of research including its support of two research centres. The preliminary interviews, described above, highlighted the importance of the work by Marc Feldmann and Sir Ravinder Maini at one of these, the Kennedy Institute of Rheumatology in London, in developing anti-Tumour Necrosis Factor (anti-TNF) therapy as an effective treatment for rheumatoid arthritis and other autoimmune diseases. The pair won the 2003 Albert Lasker Award for Clinical Medical Research for this discovery. Objectives of the evaluation/research questions Within the general climate of an increased emphasis on the outcomes from research, four main objectives were specified for the particular study described in this article: • Review and document outcomes for ARC research grants • Illustrate the strengths and weaknesses of different modes of research funding • Identify factors associated with translation of research, and attempt to develop 'early indicators' of likely successful translation • Identify 'good news stories' and vignettes of the research process for use by ARC in public engagement and fund raising activities. Methods Rationale for using a case study approach Traditional methods of peer review have long been favoured by medical research funding bodies for evaluating research, but bibliometric methods have had a variable history. An early move by the National Institutes of Health (NIH) to establish a publications' database was cancelled by the 1980s 'as too expensive for the management information it produced' [21]. The MRC in the UK reviewed the possibility of making greater use of bibliometric measures to inform per review of major long term programmes, but the steering group established to oversee the review concluded that, 'bibliometric analysis would not add sufficient value to peer review to be worthwhile routinely and should not be introduced into MRC procedures' [22]. Nevertheless, there are circumstances where bibliometric analysis can provide research funding bodies with useful information [19] and, as discussed below, they can be incorporated into broader case studies. On its own, however, it is unlikely to provide much information about the longer-term outcomes from research funding. The Economic and Social Research Council (ESRC) in the UK commissioned a project to identify the impact of their research on non-academic audiences. It involved tracing the activity of the participating researchers after their projects ended and mapping the networks of researchers and relevant non-academic users and potential beneficiaries [23]. The study concluded that the preferable way to determine and assess the existence of impacts of socio-economic research on non-academic audiences 'is through detailed, project-by-project qualitative analysis' [23]. Such an approach probably entails adopting a case study approach, and there is a long history of applying the case study approach to examine the utilisation of research [24]. Indeed, where the emphasis is on demonstrating the outcomes from health research, a case study approach has mainly been used [7,25] and been recommended for use in future studies [4,26,27]. Case studies will enable narratives or stories to be told to illuminate how the research funded in the early 1990s was translated (or not) into practice; each case, therefore, could potentially provide an illustrative example of the outcomes from ARC research. Furthermore, the planned 16 case studies will be based on a variety of modes of ARC research funding and types of research. They will also be organised using a common structure. This should enable cross-case study analysis to demonstrate (via illustrative case studies) the strengths and weaknesses of different modes of funding and categories of research. It should also facilitate the identification of factors associated with the translation of research, perhaps through various phases, into policies, products, and clinical practice that produce a health gain. The evaluation framework described below was developed in a way that incorporates previous experience and knowledge on these issues [7,12,24,26,28]. This should ensure that questions are asked about a range of factors that previous experience suggests are likely to be related to the translation of research. Additionally, because the evaluation framework includes a multi-dimensional categorisation of benefits from research, the full range of outputs and outcomes relevant to different types of research, and modes of funding, will be looked for in the studies. The case studies will, in part, be conducted to see if they produce evidence consistent with existing hypotheses about factors linked to the translation of research and the role of different modes of research funding and types of research. But they will also be exploratory and should allow the generation of new hypotheses, particularly ones specifically relevant for research funding from a medical charity. Timescale In deciding the time window to use for selecting case studies, a compromise usually has to be made between the quality of records/likely ability of researchers to recall their activities and the selection of grants whose outputs have had sufficiently long to develop [29]. The latter point was important in this study because the aim was to move beyond considering traditional outputs and also examine outcomes such as health gains. ARC instituted a new computerised database during the early 1990s and all their grants awarded since 1990 are held on this database. Prior to this, only paper records of unknown completeness were available. As an appropriate compromise between the various factors, we therefore decided to select grants that were awarded between 1990 and 1994. Selection of cases Within a case study approach it is unlikely that the selection of cases will follow a straight-forward sampling logic in which those selected are assumed to be representative of a larger group [30]. Nevertheless, in adopting a multi-case approach the project aims to ensure not only that the benefits from the full range of modes of funding and types of research can be illustrated, but also that there is scope for some cross-case analysis. The selection of cases will, therefore, be somewhat purposive. Case studies based on four modes of funding will be included: institute grant, programme grant, project grant and fellowships. ARC-funded researchers will also be divided into three groups on the basis of their qualifications: basic researchers, clinical researchers, and Allied Health Professionals (AHP) such as physiotherapists. In their classic case study analysis of research utilisation, Yin and Moore [24] went to considerable lengths to ensure that they were including only studies where it was thought there had been utilisation. We do not propose to go that far, but, given that the idea is to illuminate the outcomes, it is considered desirable to concentrate on studies where it is thought there is a reasonable chance that there will be something to show. When examining the outcomes of research, even a stratified sampling approach is not thought to be sufficient because most impact usually comes from a small number of studies [23]. As a first step, we shall identify all publications in the relevant period from the principal investigators awarded ARC funds. Then, the researchers will be classified according to the journal impact factors (see below) of the journals in which their articles appear. The aim will be to draw up shortlists of possible researchers to include in the study: those in the top decile and those the middle of the range, with the final selection made on the basis of advice from ARC's Development Committee. Organisation of data collection For case studies it is appropriate to use multiple sources of evidence converging on the same issues [4] and adopt a process of triangulation [27,30]. Three main interdependent methods will be used: documentary and literature review; semi-structured interviews with key informants; and bibliometric analysis. They will be applied in a partially overlapping way. Documentary and literature review We will read key project documents including the original research grant proposals, referees' reports and end of project reports. On the basis of the end of year reports from researchers, and the interviews (see below), we will also identify and read the core publications attributed to the research grant and any subsequent publications such as key citing papers, relevant clinical guidelines etc. Semi-structured interviews with key informants There will be about three interviews per case study. They will be based on a semi-structured interview schedule informed by the evaluation framework described below. They will, therefore, explore the origins of the research and the primary outputs such as the publications. In this way the initial list of publications identified as being related to the project will be refined. Furthermore, there will be a full exploration not only of the contribution to research training and career development, but also of any translation of the research findings into product development, policy and practice. In each case study the initial interviews will be with members of the relevant research team. Then snowballing techniques will be used to identify the people who might be able to provide most information about how the research has influenced subsequent research or been translated into product development, policy and practice. Bibliometric analysis Bibliometric approaches can play a useful role in the analysis of the research funded by specific biomedical research-funding bodies [19,31]. In the current analysis, the list of research papers published as a result of the project will first be refined as described above. Following that, bibliometric analysis will be conducted to record various matters including: the full funding acknowledgements; number of authors; citation counts; and comparison of number of citations with the journal impact factor of the publishing journals. This analysis will be conducted by a further part of the research team: those responsible for maintaining the ROD described above. Clearance and validation In every case a draft copy of the case study report will be sent to the principal investigator for comment. Such a step is an important part of the validation process and not just a matter of professional courtesy [24]. Evaluation framework for ARC case studies There are two elements in the evaluation framework adopted to organise the case studies being conducted in the assessment of the outcomes from ARC-funded research. Building on the framework developed by Buxton and Hanney [7,12], the two elements consist of a multi-dimensional categorisation of benefits from health research, and a model of how best to assess them. A logic model such as this helps facilitate assessment rather than pretending to be a precise model of how research utilisation occurs. The framework has been developed in various ways to meet the particular circumstances of ARC-funded research, which is often basic and investigator-led. There are many steps involved in assessing outcomes from research. One of the key advantages in taking a detailed approach, such as that described below, is that it enables the issue of the counter-factual to be addressed. In other words, what would the world have looked like without the specific research being examined? The categories of payback The multi-dimensional category of payback provides the evaluation criteria for the outputs and outcomes from ARC funding. The 5 main categories are: a) Knowledge production b) Research targeting, capacity building and absorption c) Informing policy and product development d) Health benefits e) Broader economic benefits. Each can be considered in turn, with various sub-categories explored and possible measures described. Knowledge production The knowledge produced by research is the first output and is contained in various publications and patent applications. Any type of publication can be considered, but it is generally thought that peer reviewed articles are the most important and, at least for biomedical research in industrialised countries, it is thought reasonable to assume that the overall output of research publications is fairly represented by peer-reviewed papers in international journals [19]. In addition to counting the number of publications, their quality and their impact can be assessed in various ways. The quality of knowledge production has traditionally been assessed by peer review, but various other methods can be applied. Papers that are accompanied by an editorial are often seen as being of particular significance. For those studies that are included in a systematic review there are now formal quality assessment techniques [32], as there are for reviews appearing in an overview [28]. Citation analysis can be applied to assess the impact the specific article is having within the research community [33,34]. Previous experience suggests that knowledge production will be particularly important for basic research, and certainly, on average, papers in basic research journals tend to be cited more frequently than ones in clinical journals [19,35]. A journal's 'impact factor' is based on the average number of times an article in the journal is cited; it can provide a short-hand version of citation analysis by giving some indication of the importance of the journal in which an article appears. The use of impact factors in analysis of biomedical research has been criticised [36] but, provided care is taken [37], it has been shown to be of some value [19]. Particularly when considering research that might be aimed at potential users outside the research community, it is often desirable to use a range of publication outlets including those journals with the highest readership among the groups at whom the research is targeted. In some fields these might well be journals that do not have an impact factor but are, nevertheless, significant as vehicles for dissemination of the knowledge produced [38-40]. Research targeting, capacity building and absorption The better targeting of future research is frequently a key benefit from research, especially from research that is more basic and/or methodologically oriented. An indication of this comes from citation analysis. The enhanced targeting can be of the research conducted both by others and by the original researcher(s). Where follow-on research, especially by members of the original research team, is clearly associated with the original research it can be useful to obtain information on the source and amount of such funding [39]. As is developed in the paragraph below, one of the key roles of a medical charity can be to fund research in its field that will help to open up questions/issues that will then attract further funding from the general research funders such as the MRC and the Wellcome Trust. Research training can be provided both as a result of the employment of staff on research projects and programmes, and through explicit funding for research training and career development [1]. One measure of research training, which may appear crude but has nevertheless been used in previous studies, is the number and level of higher or research degrees resulting, either totally or in part, from the research funding [1,14,39,41]. The career development of arthritis researchers goes much wider than specific training and is of considerable importance to ARC which aims to ensure that the pool of researchers in this field is a strong as possible. The reasoning is that this, in turn, should help ensure that arthritis as a topic is able to gain an appropriate share of the research funding available from general medical research funders. Some of ARC's funding schemes aim explicitly to provide career development, and for other researchers the receipt of a project grant from ARC can be important in advancing their career in research. Interviews can address this. Furthermore, they may also enable us to consider how far career development based on ARC funding helps propel some researchers into positions within the health-care system where they can play a role in ensuring that the later stages of translating research findings into outcomes are achieved. Informing policy and product development Research can be used to inform policymaking in a wide range of circumstances and the key issue is that policymaking involves those in positions of authority making choices that have a special status within the group to which they apply [27]. Policymaking is interpreted very broadly here and refers not just to national policies of the government, but also includes: policies made by managers at many levels within a health service; policies agreed at national or local level by groups of health-care practitioners in the form of clinical or local guidelines; policies developed by those responsible for training/education/inspection in various forms including training packages, curricula and audit and evaluative criteria [3]; and policies about media campaigns run by health-care providers. Basic research is less likely than that from clinical researchers or AHP to be used to inform policy. Various methods have been proposed for analysing the impact of research on health policymaking, including documentary review and interviews [26,27]. The position of systematic reviews is a little complex. They are themselves a form of research, but inclusion of a study in a systematic review is a form of secondary output and might lead on to further use. At a similar level, although involving very different processes, research can also be used to inform product development [38]. Informing policies and product development are conceptually similar in that there generally has to be some subsequent adoption of the policy, or product, before the health and economic benefits can accrue [7]. Health benefits Benefits in terms of health gains might be viewed as the 'real' payback or outcomes from health research. Greater effectiveness of health-care resulting from research-informed drugs or procedures should lead to increased health. Various measures of health gain exist, but for arthritis the emphasis, in most cases, is likely to be on those that assess reduction in pain or disability, and increase in mobility. While the benefits from arthritis research will not generally be measured in terms of life years gained, in some circumstances they might be captured by using Quality Adjusted Life Years (QALYs). This is often seen, in countries such as the UK, as a more appropriate approach than using Disability Adjusted Life Years (DALYs) [42]. There have been recent attempts to put a monetary valuation on the reduction in mortality and morbidity as a result of health research [16,43], but that is not being proposed for this study. At an overall level, it is possible that figures for the potential population who could benefit from the new drug or procedure could be identified, along with information about the level of benefit that individual patients might receive. If knowledge about adoption levels was then also taken into consideration it might be possible to indicate overall levels of benefit. This category of benefits can be thought of as going wider than health gain, and some aspects can be seen as benefits to the health sector more generally. Cost savings in the provision of health-care may result from research-informed changes in the organisation of services or in the particular therapies delivered. It might be necessary to consider various issues here. These include whether potential savings have in practice been realised – either as cash savings or as the release of resources for other valuable uses [44]. Furthermore, it would be important to check whether costs are not simply being transferred elsewhere. Improvements could also arise in the process of health-care delivery and these could be measured by techniques such as patient satisfaction surveys [7]. Broader economic benefits A range of benefits can accrue to the national economy from the commercial exploitation of research. These can take the form of employment and profits resulting from the manufacture and sale of drugs and devices [45]. The national economy could also benefit from exports and/or import substitution [46,47]. Whilst there is a danger of double counting, it is probably also important to adopt a human capital approach and focus on the value of production gained from having a healthy workforce. This can be measured by examining the reduction in days off work. Typically, in a human capital approach, potential future earnings are calculated for people who, as a result of advances in medical research, can continue to contribute to national production [14,15,48]. Those who use it, however, share the concerns that such an approach to assessing the benefits from research could have equity implications in that it would seem to favour research relevant for those of working age. This concern might be relevant here, in that many who suffer most from arthritis are retired, but reducing the days off work caused, for example, by low back pain, could be important. The economic burden of low back pain has been identified [49] and the potential role of research in reducing it was recently highlighted in a wide-ranging discussion of the benefits from medical research in the USA [50]. Model for assessing the outputs and outcomes The second element of the evaluation framework is the logic model. Its various stages are shown on Figure 1 and provide a way of organising the case studies. At least seven stages and two interfaces are identified and although they are presented in a linear form, the reality is much more complicated and there is also considerable feedback [7,12]. Figure 1 Model for Organising the Assessment of the Outcomes of Health Research. Sources: Adapted from previous versions of the Buxton/Hanney model for assessing the payback from health research [12,27]. Stage 0: Topic/issue identification Interface A: Project specification and selection Stage 1: Inputs to research Stage 2: Research processes Stage 3: Primary outputs from research Interface B: Dissemination Stage 4: Secondary outputs – policymaking and product development Stage 5: Adoption by practitioners and public Stage 6: Final outcomes While it is not possible totally to tie the categories of benefits to certain stages of the model, it is possible to identify broad correlations: categories a) and b) (knowledge and research benefits respectively) are together considered to be the primary outputs from research; category c) (informing policy and product development) relates to the secondary outputs; and categories d) and e) (health and broader economic benefits respectively) are the final outcomes. This approach can be incorporated into the analysis of each stage in turn as is set out below, where a few examples, drawn from the pilot studies, are used to illustrate how the framework seemed to be working in practice but could be refined in certain ways. Stage 0: Topic/issue identification The topic or issue identification stage covers the generation of the original ideas for the research. Its nature can vary considerably depending on whether the main driving force is internally generated by the researcher, or externally generated [27]. Most ARC funding falls into the former category: for many researchers the topics will be curiosity-driven and based on examination of the existing stock or pool of knowledge and opinions about where gaps, and/or opportunities, exist and further research could advance understanding. Such factors will also inform more clinical and AHP researchers, but here consideration of clinical needs could also be a factor and might be based on personal experience of treating patients, as became clear in the interview with the principal investigator in one of the case studies. Where research topics are externally generated, the identification of the issue comes from a process of needs assessment that could involve analysis either just within the scientific community or more widely. In the latter case, many groups could be involved. These include not only members of the wider research community and representatives of research funding bodies, but also potential users and beneficiaries of the research drawn from some combination of the wider political, professional, industrial and societal environment. Interface A: Project specification and selection The nature of the activities at Interface A will vary depending on the type of issue identification. Where the topics are externally generated, there are potential difficulties in ensuring both that the research community is actively engaged with the priorities that have been identified and that the project specification meets the needs as identified [27]. Where the issues are internally generated, the interface involves traditional processes of the researcher developing a detailed proposal and submitting it for peer review. Most of the issues are internal to the scientific world, but there is still a key interface between individual researchers and ARC as the research-funding body. Documentary analysis of ARC files provided information in the pilots that sometimes highlighted issues about how far the proposal was subject to changes as a result of the review process. It also proved useful, however, to supplement this with questions in the interviews. Stage 1: Inputs to research It can be important to consider not only the financial inputs, including any beyond the specific ARC funding, but also the experience of the research team and the knowledge base on which they built. Part of the idea behind examining any other funding brought in to support ARC research is again to see how far ARC funding is helping to facilitate the funding of arthritis research by general funders of health research: is ARC funding studies that produce findings that others believe are worth further investigation? The pilot studies confirmed that the complexities of identifying the exact funding streams behind any piece of research were best addressed by using a case study approach involving initial documentary review and following up issues in interviews. The pilots involved a case where other contributory funding contributed to what was clearly an ARC project, and therefore little attempt was made to portion out credit for outcomes to any funder other than ARC. In another case, however, the research was part of a stream of ARC-funded work and an effort was made to try to draw boundaries around what would be appropriate to include in the case study. Stage 2: Research processes Consideration can be given to how appropriate the proposed methods for a study turned out to be, and whether any difficulties were encountered. In some cases it could be relevant to explore how far potential users were involved at this stage. It is possible that difficulties identified at this stage could explain later problems with translation or uptake of the research findings. Stage 3: Primary outputs from research Knowledge production, as represented by the various types of publications, is a major primary output from the research. Various ways of measuring this were discussed above. The pilots also showed that the interviews used to refine the lists of publications from the specific funding in question, could also sometimes help to identify where non-conventional sources were being used as outlets for publications. Most of the primary outputs will feed into the stock of knowledge. The research benefits in terms of targeting future research represent either feedbacks to further research conducted by team members, or findings that feed into the stock of knowledge and help target future research of others. An example from one pilot study showed not only how the principal investigator used her project to inform her own further work, but was also able to contribute to a much larger collaborative project. Interviews in another study showed that the research had informed considerable further work in industry, but as yet this had not led to any product development. Under the framework being used, it is possible to give that ARC-funded work considerable credit for informing the further research, but record its limited impact at the subsequent stages. Capacity building can also be seen as a primary output. Accounts were given, in pilot study interviews, of the research training and higher degrees that resulted from the research. Interface B: Dissemination Dissemination is usually seen as being somewhat more active than the mere production of academic publications containing the knowledge. There are, however, clear overlaps between some activities. Sometimes it is possible to record not just dissemination activities but also the successful transfer of research findings to potential users in the political, industrial, professional environment and wider society. Previous analyses of how to increase the implementation of research findings [28] will help inform the issues being examined in the case studies at the dissemination and later stages. Presentations to potential academic and user groups, and media activities, are major ways of disseminating findings, as are the production of brief summaries of findings targeted at specific user groups. In previous case studies, attention has also focused on the way some researchers conduct study days, or training, based on the approach developed by their research and these can be highly effective dissemination mechanisms [51]. The pilots provided an example of the importance of this and, indeed, of the role of individual researchers in networking and disseminating information. Stage 4: Secondary outputs–policymaking and product development As noted above, policymaking and product development activities can result in a wide range of secondary outputs, and various methods are needed to identify research-informed policies. In one case study, a review of a database revealed that one project had been cited in a clinical guideline unbeknown to the research team, whereas in another pilot it took interviews to identify that the research was informing local guidelines and care pathways. The use of the research in systematic reviews was also revealed in various ways in the pilot studies. Where the research seems to have resulted in secondary outputs it is useful to explore the factors that have led to this. In relation to product development, if research findings are incorporated into the process of developing a product, for example a new drug for arthritis, this can be seen as an important secondary output. In the preliminary set of interviews, most people referred to how ARC-funded research had played a key role in the production of anti-TNF therapy for arthritis. In a pilot study, interviews revealed the extent to which industry's attempts to use one stream of research for product development had not, so far, been successful. Stage 5: Adoption by practitioners and public For the research findings incorporated into secondary outputs to result in final outcomes there usually has to be some behavioural change by practitioners, and/or the public. This may involve take-up of new drugs or procedures as set out in a secondary output such as a guideline from the National Institute for Clinical Excellence (NICE). Sometimes the adoption comes as a direct result of the primary outputs, as when clinicians – often at the cutting edge – decide to implement research findings even prior to the development of clinical guidelines. Either way, it is important to try to establish the adoption or take-up rates and to explore how far the behavioural change can be attributed to the specific research findings, as opposed to other factors such as a more general change in climate of opinion in relation to, for example, the importance of exercise. In one pilot study where interventions based on research filtered into practice, a series of interviews was used to attempt to identify both the precise role of the specific ARC-funded project and possible levels of uptake. The role of the public in responding to informed advice – often research-based – is seen as increasingly important, especially in a field such as arthritis [52]. Various factors can be explored here. These include the extent to which patient behaviour might change as a result of interactions with health-care providers who promote research-based messages, and how far the public might respond directly to publicity about research findings when they are used, for example, in media campaigns encouraging participation in preventative activities [28]. Stage 6: Final outcomes The final outcomes are the health and broader economic benefits identified in categories d) and e) above. These are increasingly seen as being the ultimate goal of health research funding, but their precise estimate in practice often remains difficult [5-7]. In one pilot study, it was possible to produce audit figures from one area where there is known to have been local implementation of the research findings. Planned analysis and synthesis Each of the 16 cases will be written up as a narrative organised according to a common structure based on the various stages of the logic model. Each study should potentially, therefore, provide illumination as to the processes that could lead to outcomes and illustrations of such outcomes. In addition, the common structure of each case should facilitate some cross-case analysis that will not only look for common factors associated with research that has led to outcomes, but also see how far such outcomes are associated with different modes of funding and types of research. Some of this analysis should be based on the previous findings that are embedded into the evaluation framework: for example, basic research might be expected to produce a reasonable number of knowledge outputs but be less likely than clinical or AHP research to inform policies. Some other aspects of the analysis, however, are likely to be exploratory: detailed analysis of factors related to the role of medical charity research in contributing to outcomes appear, as yet, not to be well established. Conclusions This paper sets out the aims and methods to be adopted in an innovative study to review the outcomes of the research funded by the Arthritis Research Campaign, one of the leading medical charities in the UK. At a time of growing emphasis on both accountability and evidence-based policy making, it is important for research-funding bodies to be able to show the results of their funding and base their policies on analyses of the processes involved in producing outcomes [53]. Based on the results of the piloting, a decision was made to go ahead with the full study. Finally, one of the challenges for the future will be to operationalise such analysis on a regular, and therefore less resource intensive, manner. It is hoped that the study will also shed light on these practical considerations, and do so in a way that will enable a system to be developed that meets the specific needs of the particular research funding body [4], in this case ARC. Competing interests The work was funded by ARC. Authors' contributions JG led the design of the study, with all authors making contributions. SH drafted the article with contributions from all authors. Acknowledgements The research team are grateful to ARC, not only for funding the project but also for the considerable support and constructive comments made by the members of ARC's Development Committee who act as the steering group for this project. We also gratefully acknowledge the assistance given by those people associated with ARC who agreed to be interviewed at the preliminary stages when the evaluative framework was being refined, and those who participated in the pilot studies. 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Higher Education Funding Council for England, Research Report 01/64 2001 Bristol: Higher Education Funding Council for England 81 95 Leong AL Euller-Ziegler L Patient advocacy and arthritis: moving forward Bull World Health Organ 2004 82 115 120 15042233 Grant J Hanney S Buxton M Academic medicine: time for reinvention. Research needs researching [Letter] BMJ 2004 328 48 14703558 10.1136/bmj.328.7430.48-a

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==== Front BMC GenetBMC Genetics1471-2156BioMed Central London 1471-2156-5-211527968110.1186/1471-2156-5-21Research ArticleThe "Goldilocks Effect" in Cystic Fibrosis: identification of a lung phenotype in the cftr knockout and heterozygous mouse Craig Cohen J 1ccohen@lsuhsc.eduLundblad Lennart KA 24lennart.lundblad@uvm.eduBates Jason HT 2jason.h.bates@uvm.eduLevitzky Michael 1mlevit@lsuhsc.eduLarson Janet E 3jlarson@ochsner.org1 Departments of Medicine and Physiology, Louisiana State University, School of Medicine, New Orleans, LA, 70112 USA2 The University of Vermont, Vermont Lung Center, Burlington, VT 05405-0075, USA3 Ochsner Children's Research Institute, Ochsner Clinic Foundation, New Orleans, LA 70121, USA4 Department of Clinical Physiology, Malmö University Hospital, Lund University, Malmö S-205 02 Sweden2004 27 7 2004 5 21 21 18 5 2004 27 7 2004 Copyright © 2004 Craig Cohen et al; licensee BioMed Central Ltd.2004Craig Cohen et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background Cystic Fibrosis is a pleiotropic disease in humans with primary morbidity and mortality associated with a lung disease phenotype. However, knockout in the mouse of cftr, the gene whose mutant alleles are responsible for cystic fibrosis, has previously failed to produce a readily, quantifiable lung phenotype. Results Using measurements of pulmonary mechanics, a definitive lung phenotype was demonstrated in the cftr-/- mouse. Lungs showed decreased compliance and increased airway resistance in young animals as compared to cftr+/+ littermates. These changes were noted in animals less than 60 days old, prior to any long term inflammatory effects that might occur, and are consistent with structural differences in the cftr-/- lungs. Surprisingly, the cftr+/- animals exhibited a lung phenotype distinct from either the homozygous normal or knockout genotypes. The heterozygous mice showed increased lung compliance and decreased airway resistance when compared to either homozygous phenotype, suggesting a heterozygous advantage that might explain the high frequency of this mutation in certain populations. Conclusions In the mouse the gene dosage of cftr results in distinct differences in pulmonary mechanics of the adult. Distinct phenotypes were demonstrated in each genotype, cftr-/-, cftr +/-, and cftr+/+. These results are consistent with a developmental role for CFTR in the lung. ==== Body Background Cystic fibrosis (CF) is a progressive disease primarily affecting the intestines, lungs, and pancreas. The gene responsible for CF was identified in 1989 [1] as coding for the cystic fibrosis transmembrane conductance regulator (cftr), a membrane chloride channel. CF is one of the most common autosomal recessive diseases in Caucasians with a carrier rate of 3–4% [2], and is characterized by recurrent infection and chronic inflammation. Recently it was found that infants with CF demonstrate changes in forced expiratory volume in 1 second (FEV1), functional residual capacity (FRC), and other parameters of lung function prior to the onset of recurrent infection [3-5]. Soon after the CF gene was discovered, a knockout mouse was developed. This mouse demonstrates subtle changes in epithelial cell phenotype, including alterations in secretory glycoconjugates and changes in secretory vesicles [6]. Monocytic infiltrates and altered lung mechanics have also been found [7]. Unfortunately, the cftr knockout mouse does not develop overt lung disease, which has severely limited its usefulness. However, the availability of new methods for pulmonary testing in rodents [8,9] now presents the opportunity to re-examine the cftr knockout mouse for functional lung changes. In the present study, therefore, we examined pulmonary function in young adult cftr -/-, cftr +/-, and cftr+/+ S489x mice in an effort to establish a lung phenotype. Results Effect of cftr gene dosage on pressure-volume (PV) curves Routine evaluation of dynamic lung function employs the stepwise variation in air volume on both the inflation and deflation phases of a single breath. Measurement of airway pressures at each step results in the classic pressure-volume (PV) curve which is dependent upon both lung structure and interfering pathology. PV curves were measured in triplicate, starting from positive end-expiratory pressure (PEEP) values of 0, 3, and 6 cmH2O in S489X mice at 30–60 days of age following genotyping for the normal and mutant cftr alleles. The 3 cmH2O PEEP curves obtained for each genotype are presented in Figure 1A. Note that these PV curves all begin at V = 0 ml, which is the FRC defined by the 3 cmH2O PEEP. The PV curves obtained at PEEP levels of 0 and 6 cmH2O were similar. Figure 1 Relationship between cftr genotypes and PV curves. Littermates from 30–60 days of age were genotyped and individuals with cftr+/+ (Black), cftr+/- (Green), and cftr-/-(Red) were evaluated using pressure volume curve analysis at Peeps of 0, 3, and 6. A: PV curve at PEEP 3; B: Calculated Cst for all PV curves; C: Calculated hysteresis for PV curves in A. All measures were corrected individually for lung weight. Error bars are +/- standard deviation. *p < 0.05 when compared to cftr+/+ and **p < 0.05 when compared to cftr+/-. The static compliance (Cst) of the lungs, which reflects elastic recoil at a given pressure, was calculated from the slopes of the PV curves. As shown in Figure 1B, the static compliance of the homozygous knockout lung was significantly decreased compared to the homozygous normal lung (p < 0.01)). Furthermore, Cst was significantly reduced in both cftr+/+ (p < 0.001) and cftr-/- (p < 0.001) as compared to age-matched cftr+/- mice. Hysteresis was altered among the 3 genotypes (Figure 1C). A statistically significant increase in hysteresis was observed in both cftr+/- (P < 0.0001) and cftr+/+ mice (p < 0.05) compared to cftr-/- mice. These data suggest the presence of a gene dosage effect in which an altered lung structure in the heterozygous animals leads to an elevated compliance relative to the two homozygous animals. Lung weights were measured and no statistically significant differences were observed among the three genotypes (Figure 1D). Airway mechanics of cftr deficient lungs We applied the forced oscillation method to the mice and determined respiratory mechanical input impedance [10,11]. We fit the constant-phase model of respiratory mechanics [12] to impedance (Zrs) and determined values for airway resistance (Raw), tissue damping (G), and tissue elastance (H). Figure 2 shows that Raw, G, and H were significantly reduced in the cftr+/- mice as compared to both cftr+/+ and cftr-/- animals (Panels A, C, & D) at all PEEP levels. Raw also decreased with PEEP in a similar fashion in all three genotypes. In contrast, Raw, H and G were significantly increased in the cftr-/- mice compared with cftr+/+ and cftr+/-, and showed a greater dependence on PEEP (Panels A, C & D). The ratio G/H, termed hysteresivity (both the low and high frequency), was not significantly affected by either genotype or PEEP (Panel E). Thus, the absence of either 1 or 2 copies of the cftr gene had significantly different effects on the phenotype of the lung. Paradoxically, the absence of only one cftr copy resulted in a greater lung compliance (lower elastance) than if neither or both copies were present. Figure 2 Variation in respiratory mechanic among cftr genotypes. Values for Raw(A), G(B), H(C), and η(D) were determined by fitting the constant-phase model to measurements of Zrs from cftr+/+ (Black), cftr+/- (Green) and cftr-/- (red) genotypes. All measures were normalized by multiplication by lung weight. Error bars are +/- standard deviation. *p < 0.05 when compared to cftr+/+ and **p < 0.05 when compared to cftr+/-. Discussion The usefulness of the cftr knockout mouse as a model of cystic fibrosis has been severely limited by its failure to demonstrate readily measurable lung disease, the primary cause of morbidity and mortality in humans [13]. However, in the present study use of sophisticated measurements of lung function revealed a functional lung phenotype in the knockout mouse (Table 1); the complete absence of cftr in the lung of young adult animals resulted in decreased Cst and η and increased Raw, G and H as compared to normal littermate controls. Table 1 Relative effect of genotype on lung function compared to that observed in the cftr+/+ mouse. Genotype PV curve position Cst PV Hysteresis Raw G H η cftr+/- ← ↑ ↑ ↓ ↓ ↓ ↔ cftr-/- → ↓ ↓ ↑ ↑ ↑ ↔ A particularly intriguing further observation was that Cst and hysteresis in cftr+/- mice was significantly higher than in cftr+/+ animals while G and H were decreased. As this was not associated with any pathology such as emphysema, we conclude that it represents a functionally different lung from that of the cftr+/+. Our data thus reveal a remarkable inverse correlation between the effect of one and two non-functional copies of the cftr gene. What do these data mean in terms of lung structure? The knockout animal has cystic fibrosis by definition, and our data now show it to also have lung disease manifest as a reduced compliance and increased resistance. These changes could reflect changes in the intrinsic mechanical properties of the parenchyma, or simply a reduction in lung volume. The former effect could include alterations in the biophysical properties of the air-liquid interface in the lungs, and would be expected to result in a change in η[14]. Indeed, because cftr is a chloride channel and is thought to be involved in water balance, a change in surface tension in the lung, and consequently in η, might be expected. However, as shown in Figure 2 and Table 1, although G and H both increase, they do so in the same proportion so there is no significant change in η between the three cftr genotypes. On the other hand, lung weights were not different among the different groups of mice, so the decreased compliance and increased resistance of the cftr-/- animals was not simply due to their having smaller lungs than control animals. This suggests that the parenchymal structure in the lungs of the homozygous and heterozygous animals were organized differently, in a manner that affected G and H similarly. As documented in numerous publications, the mouse strain used in the present study does not develop chronic inflammatory disease up to the age (30–60 days) used in this study (for review see [15]). On the other hand, Broaches-Carter et al. [16] have shown that cftr levels are highest in the developing lung and decrease 75-fold at birth. In utero over-expression of cftr has also been shown to affect lung growth and development[17], and the severity of disease in the knockout mouse has been shown to be influenced by genetic background [18]. These data thus suggest that cftr may affect the early development of the lung in a manner that is affected by the interaction of other genes. Are there any functional consequences for increased lung compliance in the heterozygous cftr animals? Interestingly, there is no decrement in lung function in human heterozygotes [19-21]. Also, the heterozygote frequency for CF in humans is higher than expected, likely reflecting a selective advantage because there is no evidence for genetic drift [22,23]. Indeed, selective advantage in CF has been proposed to reflect resistance to tuberculosis, influenza and cholera [24]. When one looks in nature for other examples of heterozygous advantage, the sickle cell trait which confers resistance to malaria [25] is perhaps the only such recognized genetic trait in humans. In Norway rats, a single Mendelian gene controls resistance to Warfarin, an anticoagulant used to control rat populations; homozygous wild-type rats are killed by Warfarin and homozygous mutant allele animals are highly susceptible to vitamin K deficiency [26]. The results of the present study indicate that a similar selective advantage may pertain to cftr, something we term a "Goldilocks Effect". That is, while two defective copies of the gene are detrimental and two normal copies are satisfactory, one normal and one defective gene may results in an optimal dosage for lung development. Further studies of pulmonary mechanics in cftr knockout mice should reveal additional genetic loci that modulate the influence of cftr on lung growth and development. Corresponding studies in humans should be useful in evaluating the effect of therapies on reversing altered pulmonary function in the CF patient. Conclusions Using sophisticated techniques to a evaluate rodent pulmonary function; a distinct, readily quantifiable lung phenotype was identified in the cftr knockout mouse. In addition, the cftr+/- mouse had a distinguishable pulmonary function phenotype from that observed in either the homozygous normal or mutant genotype mice. These data are consistent with CFTR-dependent, physiologic changes in the structure and function of the lung. Methods Mouse strain The S489X mouse 5th generation backcross to C57Bl/6 has been maintained by random mating for the past 8 years. This colony has a 100% mortality rate among cftr knockouts by 45 days of age unless the animals are placed on an elemental liquid diet and corncob bedding upon weaning [27]. Mice 30–60 days of age from our S489X mouse colony were genotyped for the normal and mutant cftr alleles. Age and litter matched cftr+/+ and cftr+/- were used for each cftr-/- mouse examined. Six animals were included in each group. All experiments were approved by the animal care and use committee. Pulmonary function tests The mice were anesthetized with intra-peritoneal pentobarbital (90 mg/kg) and the trachea was dissected free of surrounding tissue and cannulated with a 20-gauge cannula. The animals were then connected to a small animal ventilator (flexiVent, SCIREQ Inc. Montreal, PQ, Canada) and ventilated with a tidal volume of 10 ml/kg; inspiratory:expiratory ratio of 66.67%, respiratory rate of 150 breaths/minute, and maximum pressure of 30 cmH20. PEEP was controlled by submerging the expiratory limb from the ventilator into a water trap. Each animal was paralyzed with pancuronium bromide (0.5 mg/kg) and allowed to equilibrate on the ventilator until spontaneous breathing ceased (5 minutes). Respiratory mechanics To measure Zrs, mechanical ventilation was interrupted and the animal was allowed to expire against the set level of PEEP for 1 s. We then applied an 8 s broad-band volume perturbation signal to the lungs with the flexiVent, after which ventilated was resumed. This was repeated at PEEP levels of 0, 3 and 6 cmH2O. The volume perturbation signal consisted of the superposition of 18 sine waves having frequency spaced roughly evenly over the range 0.25 Hz to 19.625 Hz. Zrs was calculated from the displacement of the ventilator's piston and the pressure in its cylinder as described previously [10,11]. Correction for gas compressibility as well as resistive and accelerative losses in the flexiVent, connecting tubing and the tracheal cannula were performed as described previously [28] using dynamic calibration data obtained by applying volume perturbations through the tubing and tracheal cannula first when it was completely closed and then when it was open to the atmosphere. We interpreted the measurement of Zrs in terms of the constant phase model [12] where Raw is a frequency independent Newtonian resistance reflecting that of the conducting airways[29], Iaw is airway gas inertance, G characterizes tissue damping, H characterizes tissue stiffness (elastance), i is the imaginary unit, α links G and H, and f is frequency. We also calculated a quantity known as hysteresivity (η = G/H), which is believed to increase when regional heterogeneities develop in the lung [30]. Raw, G and H were all normalized by multiplication by lung weight. PV curves Starting at the FRC defined by the PEEP, the flexiVent was programmed to deliver seven inspiratory volume steps for a total volume of 0.8 ml followed by seven expiratory steps, pausing at each step for 1 s. Plateau pressure (P) at each step was recorded and related to the total volume (V) delivered to produce a quasi-static PV curve. Cst was calculated from the slope of each curve [31], and was normalized by division by lung weight. Zrs measurements at each PEEP level and PV curves were obtained in triplicate. Data were statistically evaluated using paired t-test with p < 0.05 being taken as significant Acknowledgement This work was supported by the Ochsner Clinic Foundation and NIH grants R01 HL-67273 and NCRR COBRE P20 RR-15557. The authors thank Dr. Conrad Hornick for his assistance. ==== Refs Riordan JR Rommens JM Kerem B Alon N Rozmahel R Grzelczak Z Zielenski J Lok S Plavsic N Chou JL et al. Identification of the cystic fibrosis gene: cloning and characterization of complementary DNA Science 1989 245 1066 1073 2475911 Raman V Clary R Siegrist KL Zehnbauer B Chatila TA Increased prevalence of mutations in the cystic fibrosis transmembrane conductance regulator in children with chronic rhinosinusitis Pediatrics 2002 109 E13 11773581 Hart N Polkey MI Clement A Boule M Moxham J Lofaso F Fauroux B Changes in pulmonary mechanics with increasing disease severity in children and young adults with cystic fibrosis Am J Respir Crit Care Med 2002 166 61 66 12091172 10.1164/rccm.2112059 Sharp JK Monitoring early inflammation in CF. Infant pulmonary function testing Clin Rev Allergy Immunol 2002 23 59 76 12162107 10.1385/CRIAI:23:1:059 Tepper RS Zander JE Eigen H Chronic respiratory problems in infancy Curr Probl Pediatr 1986 16 305 359 3022989 Cohen JC Morrow SL Cork RJ Delcarpio JB Larson JE Molecular pathophysiology of cystic fibrosis based on the rescued knockout mouse model Mol Genet Metab 1998 64 108 118 9705235 10.1006/mgme.1998.2683 Kent G Oliver M Foskett JK Frndova H Durie P Forstner J Forstner GG Riordan JR Percy D Buchwald M Phenotypic abnormalities in long-term surviving cystic fibrosis mice Pediatr Res 1996 40 233 241 8827771 Allen JT Spiteri MA Growth factors in idiopathic pulmonary fibrosis: relative roles Respir Res 2002 3 13 11806848 10.1186/rr162 Pillow JJ Wilkinson MH Neil HL Ramsden CA In vitro performance characteristics of high-frequency oscillatory ventilators Am J Respir Crit Care Med 2001 164 1019 1024 11587990 Gomes RF Shen X Ramchandani R Tepper RS Bates JH Comparative respiratory system mechanics in rodents J Appl Physiol 2000 89 908 916 10956333 Hirai T McKeown KA Gomes RF Bates JH Effects of lung volume on lung and chest wall mechanics in rats J Appl Physiol 1999 86 16 21 9887108 Hantos Z Daroczy B Suki B Nagy S Fredberg JJ Input impedance and peripheral inhomogeneity of dog lungs J Appl Physiol 1992 72 168 178 1537711 10.1063/1.352153 Geiser M Zimmermann B Baumann M Cruz-Orive LM Does lack of Cftr gene lead to developmental abnormalities in the lung? Exp Lung Res 2000 26 551 564 11076312 10.1080/019021400750048090 Fredberg JJ Stamenovic D On the imperfect elasticity of lung tissue J Appl Physiol 1989 67 2408 2419 2606848 Stotland PK Radzioch D Stevenson MM Mouse models of chronic lung infection with Pseudomonas aeruginosa: models for the study of cystic fibrosis Pediatr Pulmonol 2000 30 413 424 11064433 10.1002/1099-0496(200011)30:5<413::AID-PPUL8>3.3.CO;2-0 Broackes-Carter FC Mouchel N Gill D Hyde S Bassett J Harris A Temporal regulation of CFTR expression during ovine lung development: implications for CF gene therapy Hum Mol Genet 2002 11 125 131 11809721 10.1093/hmg/11.2.125 Larson JE Delcarpio JB Farberman MM Morrow SL Cohen JC CFTR modulates lung secretory cell proliferation and differentiation Am J Physiol Lung Cell Mol Physiol 2000 279 L333 41 10926557 Haston CK McKerlie C Newbigging S Corey M Rozmahel R Tsui LC Detection of modifier loci influencing the lung phenotype of cystic fibrosis knockout mice Mamm Genome 2002 13 605 613 12461645 10.1007/s00335-002-2190-7 Hallett WY Knudson A. G., Jr. Massey F. J., Jr. Absence of detrimental effect of the carrier state for the cystic fibrosis gene Am Rev Respir Dis 1965 92 714 724 5846055 Byard PJ Davis PB Pulmonary function in obligate heterozygotes for cystic fibrosis Am Rev Respir Dis 1988 138 312 316 3195830 Davis PB Byard PJ Heterozygotes for cystic fibrosis: models for study of airway and autonomic reactivity J Appl Physiol 1989 66 2124 2128 2545657 Pritchard DJ Cystic fibrosis allele frequency, sex ratio anomalies and fertility: a new theory for the dissemination of mutant alleles Hum Genet 1991 87 671 676 1937468 Romeo G Devoto M Galietta LJ Why is the cystic fibrosis gene so frequent? Hum Genet 1989 84 1 5 2691388 Gabriel SE Brigman KN Koller BH Boucher RC Stutts MJ Cystic fibrosis heterozygote resistance to cholera toxin in the cystic fibrosis mouse model Science 1994 266 107 109 7524148 Bayoumi RA The sickle-cell trait modifies the intensity and specificity of the immune response against P. falciparum malaria and leads to acquired protective immunity Med Hypotheses 1987 22 287 298 3295496 10.1016/0306-9877(87)90193-9 Greaves JH Ayres PB Multiple allelism at the locus controlling warfarin resistance in the Norway rat Genet Res 1982 40 59 64 7141222 Larson JE Morrow SL Happel L Sharp JF Cohen JC Reversal of cystic fibrosis phenotype in mice by gene therapy in utero Lancet 1997 349 619 620 9057739 Bates JH Schuessler TF Dolman C Eidelman DH Temporal dynamics of acute isovolume bronchoconstriction in the rat J Appl Physiol 1997 82 55 62 9029198 Tomioka S Bates JH Irvin CG Airway and tissue mechanics in a murine model of asthma: alveolar capsule vs. forced oscillations J Appl Physiol 2002 93 263 270 12070213 Lutchen KR Hantos Z Petak F Adamicza A Suki B Airway inhomogeneities contribute to apparent lung tissue mechanics during constriction J Appl Physiol 1996 80 1841 1849 8727575 Salazar E Knowles JH An Analysis of Pressure-Volume Characteristics of the Lungs J Appl Physiol 1964 19 97 104 14104296

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==== Front BMC Musculoskelet DisordBMC Musculoskeletal Disorders1471-2474BioMed Central London 1471-2474-5-221527967910.1186/1471-2474-5-22Research ArticleInjuries at a Canadian National Taekwondo Championships: a prospective study Kazemi Mohsen 1mkazemi@cmcc.caPieter Willy 2yshin516@yahoo.com1 Department of Clinical Studies, Canadian Memorial Chiropractic College, Toronto, Ontario, Canada2 School of Health Sciences, Science University of Malaysia, Kelantan, Malaysia2004 27 7 2004 5 22 22 11 3 2004 27 7 2004 Copyright © 2004 Kazemi and Pieter; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background The purpose of this prospective study was to assess the injury rates in male and female adult Canadian Taekwondo athletes relative to total number of injuries, type and body part injured. Methods Subjects (219 males, 99 females) participated in the 1997 Canadian National Taekwondo Championships in Toronto, Canada. Injuries were recorded on an injury form to documents any injury seen and treatment provided by the health care team. These data were later used for this study. The injury form describes the athlete and nature, site, severity and mechanism of the injury. Results The overall rate of injuries was 62.9/1,000 athlete-exposures (A-E). The males (79.9/1,000 A-E) sustained significantly more injuries than the females (25.3/1,000 A-E). The lower extremities were the most commonly injured body region in the men (32.0 /1,000 A-E), followed by the head and neck (18.3/1,000 A-E). Injuries to the spine (neck, upper back, low back and coccyx) were the third most often injured body region in males (13.8/1,000 A-E). All injuries to the women were sustained to the lower extremities. The most common type of injury in women was the contusion (15.2/1,000 A-E). However, men's most common type of injury was the sprain (22.8/1,000 A-E) followed by joint dysfunction (13.7/1,000A-E). Concussions were only reported in males (6.9/1,000 A-E). Compared to international counterparts, the Canadian men and women recorded lower total injury rates. However, the males incurred more cerebral concussions than their American colleagues (4.7/1,000 A-E). Conclusions Similar to what was found in previous studies, the current investigation seems to suggest that areas of particular concern for preventive measures involve the head and neck as well as the lower extremities. This is the first paper to identify spinal joint dysfunction. ==== Body Background With the inclusion of Taekwondo as a medal sport in the 2000 Olympic Games interest has gained momentum from participants, national governments and scientists alike. With increased participation, the issue of safety becomes very important and timely. The rules and regulations with regards to these Championships were that of the World Taekwondo Federation [1]. All athletes were sixteen years of age and older and held black belt first degree as a minimum requirement to compete. At the time of data collection, punches were allowed to the front of the torso in the area covered by the chest protector worn by the athletes. No punches were allowed to the head or other parts of the body. Kicks were allowed to the torso and head, the latter of which was covered by a helmet similar to the one worn in amateur boxing. Regardless of the area of contact, only one point was granted by the referees for a successful blow. One could win the match by means of a knockout, therefore, contact was encouraged. There was a change of rules introduced in 2003, which included granting two points for head shots and an additional point for an eight-count knockout [1]. Prospective studies on Taekwondo injuries sustained at single tournaments have been conducted before [1-3]. For instance, Zemper and Pieter [2] found injury rates for American elite male Taekwondo athletes to be 127.4/1,000 athlete-exposures and for females, 90.1/1,000 athlete-exposures. One athlete-exposure (A-E) refers to one athlete being exposed to the possibility of being injured. Since there are always two athletes competing during any one bout, there are two athlete-exposures per bout [2,3]. In a later study, Pieter et al. [3] reported injury rates of 139.5/1,000 A-E and 96.5/1,000 A-E for European men and women, respectively. In neither study were the differences tested for statistical significance. However, at a recreational tournament in the United Kingdom, the men (51.3/1,000 A-E) sustained statistically significantly more injuries than the women (47.6/1,000 A-E) [4]. It is not clear why the men in the studies mentioned above sustained more injuries. Sample size may be a factor. For instance, in a prospective study covering multiple Taekwondo tournaments, Pieter and Zemper [5] reported a statistically significantly higher injury rate for the women (105.5/1,000 A-E versus 95.1/1,000). In the largest prospective judo injury study to date, young and adult females (130.6/1,000 A-E) incurred a higher injury rate than their male counterparts (122.6/1,000 A-E) [6]. In addition to sample size, the number of female competitors is also lower [5,6]. As expected in a collision sport, the contusion was the most frequently occurring injury type in both male and female Taekwondo athletes [2-4]. At the elite level, more serious injuries such as fractures and cerebral concussions also occur [3,7]. Men seem to incur more of these serious injuries [2,3]. Less information is available in karate, for the authors have not consistently reported the injuries by gender. Based on what is known from prospective studies on elite karate athletes, the men also seem to incur more serious injuries, some of which have led to time loss [8,9]. The body region most frequently affected in single tournaments involving both recreational and elite Taekwondo athletes is the lower extremities, especially the (instep of the) foot [2-4]. Since full-contact or Olympic Taekwondo is characterized by kicking, this should come as no surprise. There is a lack of data on gender differences in injuries to body region and body part in karate. Most prospective studies combined the injury rates for males and females [e.g., [8]]. Using a prospective design, Pieter [10] reported that the head and neck sustained most of the injuries in both elite male and female karate athletes. There is also scarce information on male-female comparisons on body regions injured in judo athletes. Our own studies in judo seem to indicate that in the women, the upper extremities are mostly affected, while in the men, the head and neck as well as the lower extremities are injured most often [11,12]. In line with the frequent use of the legs in Taekwondo, the main injury mechanism was found to be delivering or receiving a kick [2,5]. Further analysis revealed that the roundhouse kick was most often implicated, especially in men [3,4,13]. The fact that injuries occur as a result of receiving a kick may be partially related to unblocked attacks, which has led to the recommendation for the coaches to work on improving the blocking skills or evasive maneuvers of their athletes [2]. The purpose of this study was to identify and compare the rates of injury in Canadian male and female Taekwondo competitors relative to total number of injuries, type, body part injured and mechanism. Methods Subjects (219 males and 99 females) participated in the 1997 Canadian National Taekwondo Championships in Toronto, Canada. Injuries were recorded on an injury form to document any injury seen and treatment provided by the health care team as it was required by law. The first author was the only person who kept the injury forms and entered the data, therefore, keeping the identity of athletes confidential. Oral consent was obtained from the athletes for assessment and providing therapy. Data describe the athlete and nature, site, severity and mechanism of the injury. No reliability and validity information for the instrument is available and this study was carried out to pre-test the injury data collection form (Figure 1). Injuries were diagnosed by the tournament physician (MK), who has been the national team chiropractic physician for several years and is an experienced (black belt) Taekwondo athlete himself. One injury form was filled out by the attending physician for each time the athlete reported a new injury. However, at each presentation there could be more than one injury reported on the same Injury Report form. For the purposes of this study, an athlete was considered injured if any of the following conditions applied [14]: 1) any circumstance that forced the Taekwondo athlete to leave the competition; 2) any circumstance for which the referee or athlete had to stop competition; 3) any circumstance for which the athlete requested medical attention. In other words, the definition included so-called time-loss injuries (stoppage of a bout) as used in the NCAA Injury Surveillance System [15]. Injury rates were calculated from matches fought using the basic rate formula: (# injuries / # athlete-exposures) × 1,000 = # injuries per 1,000 athlete-exposures (A-E). The Colorado concussion classification was utilized in management of the concussions [16,17]. According to this classification, a first degree concussion is identified by confusion, no loss of memory and no loss of consciousness (LOC). A second degree involves confusion, loss of memory but no LOC and the third degree is when there is LOC [16,17]. Results The age range for the males was 17–34 years with a mean of 24.2 years and for the females, 16–26 years with a mean of 21 years. The age was not recorded for 3 males and 1 female. Table 1 displays the injury data and rates for the Canadian Taekwondo athletes. The lower extremities were the most commonly injured body region in the men (32.0 /1,000 A-E), followed by the face (eyes, nose, cheek, lips, jaw; 18.3/1,000 A-E), and the spine (neck, upper back, low back and coccyx) (13.8/1,000 A-E). If the head and neck (which includes the face area) are combined, as was done in other studies [4,7], this body region incurred the second highest injury rate: 24.9/1,000 A-E. All injuries to the women were sustained to the lower extremities with the foot incurring most of the injuries (15.2/1,000 A-E; Table 2). The top five injuries in the males include the sprain (22.8/1,000 A-E), followed by the joint dysfunction (13.7/1,000 A-E), contusion and laceration (11.4/1,000 A-E each), and strain (9.1/1,000 A-E). The cerebral concussion is ranked sixth (6.9/1,000 A-E). There were one third degree and two first degree concussions. In the women, the contusion was the most often occurring injury (15.2/1,000 A-E), followed by the sprain and strain (5.1/1,000 A-E each; Table 3). Table 4 displays the rates of the injury mechanisms by gender. Receiving a kick by the men included those connecting with the head/face (18.3/1,000 A-E), trunk (6.9/1,000 A-E), and thigh (2.3/1,000 A-E). Delivering a kick as an injury mechanism in the men included, among others, kicking to the elbow (6.9/1,000 A-E), kicking with the toes, to the trunk and with the knee (2.3/1,000 A-E each). In the women, delivering a kick (10.1/1,000 A-E) was the main injury mechanism and comprised kicks to the elbow, while the kick that was received involved a knee kick. Discussion The injuries incurred by the Canadian Taekwondo athletes compare favourably to those found by others. As mentioned above, American elite athletes recorded injury rates of 127.4/1,000 A-E (men) and 90.1/1,000 A-E (women) [2], while European colleagues had rates of 139.5/1,000 A-E (men) and 96.5/1,000 A-E (women) [3]. At one Greek national championship, the men (20.6/1,000 A-E) sustained statistically significantly fewer injuries than the women (36.4/1,000 A-E) [13]. The total injury rate of the Canadian male and female Taekwondo athletes combined, was also lower than that of their African counterparts (86.6/1,000 A-E) [7]. At an Open British tournament, injury rates of 51.3/1,000 A-E (men) and 47.6/1,000 A-E (women) were reported [4]. However, the athletes competing at this particular tournament were of sub-elite level. It is hypothesised that injuries may be related to level of skill and experience, although confirmatory research still needs to be carried out [18]. All competitors were black belts, but no information is available on their experience in Taekwondo and in competition. Future research should include general Taekwondo as well as competition-specific experience in addition to belt level. Comparative data gleaned from prospective studies on other martial arts injuries incurred at single tournaments are depicted in table 5. In view of the nature of the sport, as alluded to above, it is not surprising to find the lower extremities to sustain most of the injuries as was found in previous studies as well [2,3,13]. Within the lower extremities, the foot (i.e., instep) was the most often injured body part, as was the case with the females in the present study, which led to the suggestion for the Taekwondo governing bodies to recommend padding to help decrease injuries to this site [22]. In karate, on the other hand, the head and neck incur most of the injuries [8,10], while in judo, the upper extremities are more at risk [6,11]. As expected, the contusion was found to be the most frequently occurring injury type in other studies on Taekwondo injuries [e.g., [2,3,13]]. The sprain ranked in the top three of most frequently occurring injuries across several tournaments [5]. The contusion was also the most often occurring injury in karate [9,10], while the epistaxis ranked second in Dutch men and women [10]. In Finnish elite male karate athletes the laceration was ranked second and the epistaxis in women [9]. In judo, the strain in men and the abrasion in women were sustained most often [11,12]. Since the sample sizes in the current investigation as well as in the aforementioned karate and judo studies are rather small, more research is needed to arrive at more definitive conclusions. However, differences between the martial arts in terms of techniques used and competition rules undoubtedly play a major role. Of more concern, however, is the occurrence of cerebral concussions. The Canadian males recorded a higher rate than found in American (4.7/1,000 A-E) [2] and Greek (1.0/1,000 A-E) [13] elite Taekwondo athletes, but lower than those competing in the 1993 European Cup (15.5/1,000 A-E) [3] and the 1991 World Championships (15.3/1,000 A-E) [23]. The Canadians also recorded lower rates than elite Dutch karate athletes (13.2/1,000 A-E) competing under semi-contact rules [10]. Given the serious implications of these injuries, preventive measures, testing of equipment and follow-up research are urgently needed [e.g., [18]]. In accordance with what was found previously, the injury mechanisms included both receiving and delivering kicks for men and women alike [2,5]. The men, more than the women, tended to get injured as a result of receiving a kick [2,3]. It is suggested that the technique most likely implicated is the roundhouse kick [3,4,13]. Kicking the elbow typically leads to injury, especially if the kick is executed with the instep of the foot, such as when using the roundhouse kick to attack or counter-attack. Yet another reason to implement foot padding, as already mentioned above. In karate, punching is the main injury mechanism for both men and women [8,10], which may be related to the head and neck region being most frequently injured. More research on Canadian Taekwondo athletes of different age groups and skill levels is needed. Age in the present study is not believed to have played a role in the injuries sustained. The injury profile of the Canadians is quite similar to those found in other studies with Taekwondo athletes in their early twenties [2,3,5]. Children and juniors in Taekwondo were reported as incurring higher injury rates than adults [4,13]. Future studies should also include time lost due to injury. Joint dysfunction was identified as the second most common injury sustained by male athletes (13.7/1,000 A-E). Haldeman [24] defines joint dysfunction quoting Drum (1973) as,"Joint mechanics showing area disturbances of function without structural change; subtle joint dysfunctions affecting quality and range of joint motion. They are diagnosed with the aid of motion palpation, as well as stress and motion radiography investigation" [p. 623]. Greenman [25] states: "Joint dysfunction is characterized by findings of misalignment, relative fixation, loss of normal range-of-motion and end-play, tenderness, and tissue texture abnormality" [p. 13–14]. Although controversial, the term has been used widely in the literature, mostly by chiropractors, physical therapists and occasionally by biomechanists and medical doctors [24-33]. Further studies are required to validate the current finding. Conclusion The total injury rates for the Canadian Taekwondo athletes compare favourably to those reported in the literature, which is contrary to what was expected based on such a small sample size. It is hypothesized that recent rule changes may have contributed to these relatively low rates when compared to those found for other single tournaments, although more research is indicated before a definitive conclusion may be drawn. Interestingly, joint dysfunction was identified for the first time, which warrants more study. The injury data collection form should also include the technique used as a specification of the injury mechanism. General Taekwondo and competition-specific experience in addition to belt rank should also be recorded. Competing interest None declared. Authors' contributions MK collected the data, designed the Injury Report form, and wrote the initial draft of the manuscript. WP did the result part, revised and proof read the manuscript. Pre-publication history The pre-publication history for this paper can be accessed here: Acknowledgements We would like to thank Canadian Memorial Chiropractic College for funding this study. Figures and Tables Figure 1 Injury data collection form. Table 1 Injury rates (95%CI) in adult Canadian Taekwondo athletes. Men Women Total Number of athletes 219 99 318 Number of reported injuries 35 5 40 Number of athlete-exposures (AE) 438 198 636 Injury rates -- per 100 athletes 16.0 (10.7–21.3) 5.1 (0.7–9.5) 12.6 (8.7–16.5) -- per 1,000 AE 79.9 (53.4–106.4) 25.3 (3.2–47.4) 62.9 (43.4–82.4) Table 2 Distribution of injuries by body part per 1,000 athlete-exposures. Men Women Body part Number Rate Body part Number Rate Head 3 6.9 Hamstrings 1 5.1 Eyes 2 4.6 Ankle 1 5.1 Nose 3 6.9 Foot 3 15.2 Cheek 1 2.3 Lip 1 2.3 Jaw 1 2.3 Neck 1 2.3 Hands 3 6.9 Upper back 1 2.3 Low back 2 4.6 Pelvis 1 2.3 Coccyx 2 4.6 Hamstrings 3 6.9 Leg 2 4.6 Ankle 5 11.4 Foot 2 4.6 Toes 2 4.6 Total 35 79.9 Total 5 25.3 Table 3 Distribution of injuries by injury type per 1,000 athlete-exposures. Men Women Injury type Number Rate Injury type Number Rate Sprain 10 22.8 Contusion 3 15.2 Joint dysfunction 6 13.7 Sprain 1 5.1 Contusion 5 11.4 Strain 1 5.1 Laceration 5 11.4 Strain 4 9.1 Concussion 3 6.9 Abrasion 1 2.3 Epistaxis 1 2.3 Total 35 79.9 Total 5 25.3 Table 4 Distribution of injuries by mechanism per 1,000 athlete-exposures. Men Women Injury mechanism No Rate Injury mechanism No Rate Receiving a kick 12 27.4 Delivering a kick 2 10.1 Delivering a kick 7 16.0 Receiving a kick 1 5.1 Simultaneous kicks 1 2.3 Not recorded 2 10.1 Other 3 6.9 Not recorded 12 27.4 Total 35 79.9 Total 5 25.3 Table 5 Comparative injury rates per 1,000 athlete-exposures (95%CI) in adult martial arts athletes*. Sport/Study Men Women Taekwondo (this study) 79.9 (53.4–106.4) 25.3 (3.2–82.4) Judo [12] 48.5 (18.5–78.6) 34.3 (4.2–64.3) Judo [19] 115.1 (90.9–139.3) -- Judo [20] 51.3 (1.0–101.6) 125.0 (107.7–142.3) Judo [11] 25.2 (6.5–43.8) 41.3 (14.3–68.3) Karate [10] 168.9 (144.1–193.6) 158.5 (120.0–197.1) Karate [19] 65.5 (43.1–87.8) -- Karate [21] 135.6 (105.9–165.3) -- Karate [9] 157.7 (123.6–191.8) 80.4 (27.9–132.9) *Except for our own studies, injury rates are estimated based on the information provided by the authors ==== Refs Zemper ED Pieter W Injury rates during the 1988 US Olympic Team Trials for Taekwondo Br J Sports Med 1989 23 161 64 2620229 Pieter W Van Ryssegem G Lufting R Heijmans J Injury situation and injury mechanism at the 1993 European Taekwondo Cup J Hum Mov Stud 1995 28 1 24 Pieter W Bercades LT Heijmans J Injuries in young and adult Taekwondo athletes Kines 1998 30 22 30 Pieter W Zemper ED Injuries in adult American Taekwondo athletes In Proceedings of Fifth IOC World Congress on Sport Sciences, Sydney, Australia October 31-November 5, 1999 Barrault D Achou B Sorel R Accidents et incidents survenus au cours des compétitions de judo Symb 1983 15 144 152 Phillips JS Frantz JM Amosun SL Weitz W Injury surveillance in Taekwondo and judo during physiotherapy coverage of the seventh All Africa Games SA J Phys 2001 57 32 34 Hillman S Dicker G Sali A Non contact karate injuries Aus J Sci Med Sport 1993 25 73 75 Tuominen R Injuries in national karate competitions in Finland Scan J Med Sci Sports 1995 5 44 48 Pieter W Injuries and mechanisms of injury in karate competition In Proceedings of 1st World Congress on Combat Sports and Martial Arts, Université de Picardie Jules Verne, Faculté de Sciences du Sport, Amiens, France March 31-April 2, 2000 Pieter W Talbot C Pinlac V Bercades LT Injuries at the Konica Asian Judo Championships Acta Kines Univ Tartu 2001 6 102 111 James G Pieter W Injury rates in adult elite judoka Biol Sport 2003 20 25 32 Beis K Tsaklis P Pieter W Abatzides G Taekwondo competition injuries in Greek young and adult athletes Eur J Sports Traumol rel res 2001 23 130 136 Lindenfeld TN Schmitt DJ Hendy MP Mangine RE Noyes FR Incidence of injury in indoor soccer Am J Sports Med 1994 22 364 371 8037278 McKeag DB Hough DO Zemper ED Primary Care Sports Medicine Dubuque, IA: Brown & Benchmark 1993 63 73 Colorado Medical Society. Report of the Sports Medicine Committee Guidelines for the Management of Concussion in Sports (revised) 1991 Denver, Colorado Medical Society Kelly JP Rosenberg JH The development of guidelines for the management of concussion in sports J Head Trauma Rehab 1998 13 53 65 10.1108/09649429810208738 Pieter W Caine D, Caine C, Lindner K Martial arts In Epidemiology of Sports Injuries 1996 Champaign IL: Human Kinetics Books 268 283 Dah C Djessou P Accidents et incidents liés au judo et au karaté au cours d'une saison sportive [1986–1987] en Côte-d'Ivoire Cinés 1989 28 153 157 Pieter W De Crée C Competition injuries in young and adult judo athletes In Proceedings of The Second Annual Congress of the European College of Sport Science, Copenhagen, Denmark August, 20–23, 1997 McLatchie GR Analysis of karate injuries sustained in 295 contests Inj Brit J Acc Surg 1976 8 132 134 10.1016/0020-1383(76)90049-8 Pieter W Zemper ED Varnes JW, Gamble D, Horodyski MB Foot injuries in Taekwondo In Proceedings of the 38th World Congress Proceedings, Gainesville: 1995; The University of Florida College of Health and Human Performance 1995 165 166 Pieter W Lufting R Injuries at the 1991 Taekwondo world championships J Sports Traumatol rel res 1994 16 49 57 Haldeman S Principles and practice of chiropractic 1992 2 Norwalk: Appleton & Lange 623 Greenman PE Principles of manual medicine 1996 2 Baltimore: Williams & Wilkins 13 15 Taylor P Tole G Vernon H Skin rolling technique as an indicator of spinal joint dysfunction JCCA 1990 34 82 86 Suter E McMorland G Herzog W Bray R Conservative lower back treatment reduces inhibition in knee-extensor muscles: a randomized controlled trail J Manipulative Physiol Ther 2000 23 76 80 10714531 10.1067/mmt.2000.104088 Kokmeyer DJ Van der Wurff P Aufdemkampe G Fickenscher TC The reliability of multitest regimens with sacroiliac pain provocation tests J Manipulatice Physiol Ther 2002 25 42 8 10.1067/mmt.2002.120418 Knustson GA Dysafferentation: a novel tern to describe the neuropathological effects of joint complex dysfunction–a look at likely mechanisms of symptom generation J Manipulative Physiol Ther 1999 22 491 4 10519568 Suter E McMorland G Herzog W Bray R Decrease in quadriceps inhibition after sacroiliac joint manipulation in patients with anterior knee pain J Manipulative Physiol Ther 1999 22 149 53 10220713 Toussaint R Gawlik CS Rehder U Ruther W Sacroiliac dysfunction in construction workers J Manipulative Physiol Ther 1999 22 134 8 10220710 Maigne JY Chatellier G Comparison of three manual coccydynia treatments: a pilot study Spine 26 E479 83 2001 Oct 15; discussion E484 11598528 10.1097/00007632-200110150-00024 Harrison DE Harricon DD Troyanovich SJ The sacroiliac joint: a review of anatomy and biomechanics with clinical implications J Manipulative Physiol Ther 1997 20 607 17 9436146

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BMC Musculoskelet Disord. 2004 Jul 27; 5:22

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BMC Musculoskelet Disord

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==== Front BMC Health Serv ResBMC Health Services Research1472-6963BioMed Central London 1472-6963-4-191527122010.1186/1472-6963-4-19Research ArticleWorld health system performance revisited: the impact of varying the relative importance of health system goals Lauer Jeremy A 1lauerj@who.intLovell CA Knox 2knox@terry.uga.eduMurray Christopher JL 1christopher_murray@harvard.eduEvans David B 1evansd@who.int1 Evidence and Information for Policy, World Health Organization, Geneva, Switzerland2 Department of Economics, University of Georgia, Athens, GA 30602, USA2004 22 7 2004 4 19 19 12 11 2003 22 7 2004 Copyright © 2004 Lauer et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background In 2002, the World Health Organization published a health system performance ranking for 191 member countries. The ranking was based on five indicators, with fixed weights common to all countries. Methods We investigate the feasibility and desirability of using mathematical programming techniques that allow weights to vary across countries to reflect their varying circumstances and objectives. Results By global distributional measures, scores and ranks are found to be not very sensitive to changes in weights, although differences can be large for individual countries. Conclusions Building the flexibility of variable weights into calculation of the performance index is a useful way to respond to the debates and criticisms appearing since publication of the ranking. health care provisionweighting of indicators ==== Body Background The World Health Organization recently published a performance ranking of the health systems of its 191 member countries, and intends to update it at regular intervals [1-4]. It was based on a framework outlining a set of social goals to which health systems should contribute [5]. It was argued that systems should contribute to improving population health, be responsive to the people they serve and be financed fairly. Five outcome indicators were defined – the level of population health, inequalities in health, the level of responsiveness, inequalities in responsiveness and fairness in financial contributions. Estimates of attainment on these five indicators were made for the 191 countries that were members of WHO at that time, and a composite (overall) attainment indicator was constructed for each country as a weighted average of attainment on the five individual outcome indicators. Publication of the analytical framework and the resulting ranking provoked considerable comment, and a variety of issues concerning the methodology and country positions in the ranking have been raised. A central component of the methodology for measuring overall attainment was the use of fixed weights, common to all countries, to aggregate the five indicators. This feature has been controversial, with some arguing that people in different cultural and social settings value individual health system goals in different ways [6-13]. The fixed weights had the virtue of being based on expert opinion, having been derived from the valuations of 1,007 respondents – largely health system professionals – to a WHO survey [14]. However the weights were common to all countries, regardless of their development status and cultural traditions. In this paper we examine the sensitivity of the attainment scores to alternative weighting schemes that allow weights to vary across countries. These country-specific weights may reveal varying objectives of policy makers or constraints under which they operate. Melyn and Moesen [15] have referred to such weights as 'benefit of the doubt' weights. Methods WHO used fixed weights (0.25, 0.25, 0.125, 0.125, 0.25) to aggregate five health system outputs (respectively, the level of population health, inequality in the distribution of health, the level of health system responsiveness, inequality in the distribution of responsiveness, and fairness in financial contributions) into a scalar health system attainment index. Overall attainment ranged from 35.7 (Sierra Leone) to 93.4 (Japan) on a [0–100] scale. We propose here an analytical framework that reduces to the WHO fixed-weight methodology as a special case, but that allows varying degrees of freedom for weights to be defined that – in the sense of Melyn and Moesen – implicitly take into account individual country circumstances. For shorthand, we say countries "choose" such weights, which in reality are determined as solution values of a linear program. If the linear program is a fair representation of the objective function of and constraints faced by decision makers, the weights are indeed "chosen", but even if this condition is not necessarily met, the resulting weights may still be of interest. The extent of freedom to choose weights in a linear program can be set by the analyst. The analyst can enforce fixed weights common to all countries, allow countries complete freedom to choose their own weights, or adopt a middle ground in which countries are granted limited freedom to choose weights within bounds thought to be sensible by experts. A generic statement of the performance evaluation problem in primal-dual linear programming format is: In these programs y is a country's output vector, x is its input vector, Y is the sample output matrix and X is the sample input matrix. In the present context y is (5 × 1), Y is (5 × 191), x is (n × 1) and X is (n × 191), with n to be specified below. The primal program seeks the maximum radial expansion of a country's outputs, provided that it not exceed the standards established by a convex combination (λ ≥ 0, ∑λ = 1) of best-practice countries in the sample. The optimal value of φ provides a distance measure (i.e. an indication of how far a country has to go) to match best practice as observed in the sample. Since φ ≥ 1, the attainment of a country is evaluated as φ-1 ≤ 1. Best practice countries have φ-1 = 1, other countries have φ-1 < 1, so φ provides a basis for acomplete ranking of countries on their relative ability to deliver five health system outputs. The dual program seeks a set of nonnegative weights μ,υ attached to a country's outputs and inputs that maximize its attainment. Each country's output weights are normalized by μy = 1, but each is free to select its own set of nonnegative weights. In constructing the overall attainment index, WHO identified five output indicators and no inputs, preferring to treat each country's health system as a "health output management unit". Consequently each country's input vector is represented as a scalar with unit value. Under these circumstances the performance evaluation problem simplifies to: where ω = υ + υ0. The modified primal program seeks the maximum feasible radial expansion of a country's outputs consistent with best practice observed in the sample. The modified dual program seeks a set of nonnegative weights μ for a country's outputs that put it in the best light. A country can be expected to assign relatively large weights to those outputs at which it excels relative to best practice, and relatively low, possibly zero, weights to those outputs at which it lags behind best practice, subject to the normalization μy = 1. (See Annex for a graphical explanation.) By complementary slackness, μm(Ymλ - φym) = 0, m = 1, ..., M, so slack in any element of a country's projected output vector φy implies that the country assigns a zero weight to that output. Since it is unreasonable to allow a country to assign a zero weight to any output deemed sufficiently important to have been included in the WHO performance evaluation exercise, it is desirable to restrict weights in some way. This can be accomplished most easily by appending constraints to the dual side of (2) of the form: γm ≥ μmym/μy ≥ βm, m = 1, ..., M.     (3) Restrictions (3) place lower and upper bounds on the relative importance of each output (as measured by μm) in total output. Implementation of the weight-restricted linear program requires specifying the 2M = 10 parameters γm, βm. One procedure is to ignore the upper bounds γm and set the lower bounds βm > 0. This eliminates the possibility of a country assigning zero weights to those outputs at which it lags behind best practice. A less arbitrary procedure is to follow Takamura and Tone [16] by adapting Saaty's Analytical Hierarchy Process (AHP) [17]. This procedure exploits expert judgment, that could be provided for example by the above-mentioned survey of health system professionals, to set lower bounds βm > 0 and upper bounds 1 > γm. Although these bounds are common to all countries, they allow countries limited freedom to select weights appropriate to their circumstances. Results The fixed weights used by WHO)) [4] to aggregate the five health system indicators gave countries no freedom to choose weights appropriate to their circumstances. We compare the WHO attainment index with three alternative indexes allowing countries varying degrees of freedom to choose weights. The first index is based on the solution to program (2), without weight restrictions, thereby allowing complete freedom to choose. The second index is based on (2), with lower bounds in (3) of βm = 0.10 on all weights, allowing substantial freedom to choose. The third index is based on (2), with lower and upper bounds in (3) set by a modified AHP procedure. In the modified procedure, "expert opinion" was taken to mean the average values of weights arising from population-representative country surveys, each of which included a module on health system goals [9]. Respondents were queried about their individual preferences on the five stated health system goals in a total of 51 countries, in some of which multiple surveys were performed, and country means were calculated on the basis of these individual responses [18]. The survey methods, reliability, validity, representativeness, sample size and respondent characteristics are extensively described in Ustün et al. [9], and are also reported in summary form in Sadana et al. [19], Mathers et al. [20], Mathers et al. [21] and Sadana et al. [22]. The survey instruments are available at . For each output, the lower bound for calculation of the third index was taken as the minimum of the country average weights, and the upper bound the maximum [23]. Country mean weights and survey types, as well as survey wide maximum and minimum weights are shown in Table 1. The lower bounds are accordingly βm = (0.19, 0.17, 0.12, 0.11, 0.22) and the upper bounds γm = (0.29, 0.25, 0.18, 0.17, 0.30). This specification allows limited freedom to choose. We refer to the four indexes as WHO, LP1, LP2 and LP3, respectively. Summary statistics of the four attainment indexes appear in Table 2. The three LP distributions have higher means than the WHO distribution, and two of them have lower dispersion. However increasing restrictions on freedom to choose reduce the mean, and increase the dispersion, of the LP attainment indexes toward the mean and dispersion of the WHO attainment index. Rank correlations between pairs of attainment rankings appear in Table 3. Despite the distributional changes due to freedom to choose, rank correlations are positive, high and statistically significant. The lowest correlations involve LP1, the index allowing complete freedom to choose. With the exception of LP1, there is strong agreement about the identity of countries in the top and bottom quartiles of the distribution. Japan is ranked #1 and Sierra Leone is ranked #191 on all four indexes. Figure 1 shows plots of WHO attainment scores and rankings versus the three LP attainment scores and rankings. The convergence of the distributions of the LP attainment scores and rankings to the WHO scores and rankings is apparent. Results based on LP1 are unattractive. Over one-third of countries (70 of 191) assign a zero weight to four of the five indicators, and the vast majority of countries assign a weight in excess of 0.9 to either responsiveness distribution or fairness in financial contributions. This means they assign a low or zero weight to population health, the defining goal of the health system, which does not have face validity. In LP1, only Japan, Luxembourg and the United States assign positive weights to all five indicators. Consequently the attainment index is tightly distributed about a very high mean value. The ability to discriminate is sacrificed to freedom to choose, with 75% of countries receiving attainment indexes of 99 or above. Results from LP2 are somewhat more attractive. Nevertheless, when weights are bounded below by 0.1, over three-quarters (147 of 191) of countries assign the minimum weight to four of the five indicators and a 0.6 = 1 - (4 × 0.1) weight to either responsiveness distribution or fairness in financial contributions. The attainment scores are again compressed about a high mean value, and the ability to discriminate is not much improved, with 75% of countries receiving attainment scores of 93 or above. However despite this dramatic compression, the LP2 ranking is globally very similar to the WHO ranking. Eighteen of the countries ranked in the top 20 by WHO appear in the LP2 top 20, and 14 of the countries ranked in the bottom 20 by WHO appear in the LP2 bottom 20. Not surprisingly, the distribution of the attainment scores for LP3 looks even more similar to the distribution of the WHO scores, and has a similar mean and standard deviation. Rank correlation is very high, with only one country falling out of the WHO top 20 and only five countries rising out of the WHO bottom 20. Nonetheless, limited freedom to choose has an important impact on individual countries. The USA, given an ability to emphasize the importance of responsiveness level and responsiveness inequality, and to de-emphasize the importance of health level and inequality in the distribution of health, improves its ranking from #15 to #3. Australia improves from #12 to #7 for similar reasons. Italy, on the other hand, falls from #11 to #18, primarily as a result of the movement of other countries. In LP3, the largest positive changes in ranking are for Mauritius (+25) and Saint Vincent (+22), while the largest negative changes in ranking are for Kazakhstan (-39) and Albania (-36). Discussion We began by questioning the appropriateness of the fixed weight approach to aggregating indicators adopted by WHO, on the grounds that fixed weights deny countries at varying stages of development the freedom to choose. We then proposed a sequence of linear programming models that allowed countries varying freedom to choose the weights assigned to their indicators. LP1 allows complete freedom to choose, and generates weights we consider unacceptable, particularly because so many countries give a zero weight to improving health. LP2 allows considerable freedom to choose, but generates many country-specific weights falling outside the range of the within-country means used as bounds in LP3. Clearly, the validity of a procedure that routinely assigns weights out of the range of representative cross-population preferences should be questioned, even without a sophisticated theory of empirical ethics or democratic choice. LP3 applies the AHP procedure to set plausible bounds on weights, and allows limited freedom to choose. It generates a very similar distribution of the attainment index, and a very high linear rank correlation with the WHO ranking. Despite these similarities, we find the LP3 approach intuitively appealing, and are encouraged by its global concordance with the WHO index. However it is fair to ask: if LP3 and WHO generate such similar rankings, why bother? What value does LP3 add? Indeed, individual countries may come to diametrically opposed conclusions about the benefits of LP3 or WHO on the basis of their implied rank changes (e.g. Mauritius vs. Kazakhstan). Howbeit, our first response to the question "why bother" focuses on the distribution of the LP3 weights in comparison to the WHO weights. The WHO weight on responsiveness inequality was 0.125. But the LP3 upper bound of 0.17 is binding on 182 countries, which implicitly want a higher weight on this indicator. The WHO weight on fairness in financial contributions was 0.25. But the LP3 upper bound of 0.30 is binding on 167 countries that want a higher weight. At the other end, the WHO weight on health level is 0.25. But the LP3 lower bound of 0.19 is binding on 170 countries that want a lower weight. The WHO weight on responsiveness level is 0.125. But the LP3 lower bound of 0.12 is binding on 103 countries that want a lower weight. It appears that a majority of countries at all stages of development may implicitly assign greater importance to indicators of health distribution, and less importance to indicators of health level, than the experts whose judgments formed the basis of the original WHO weights. Our second response is more general. By allowing countries limited freedom to choose their weights, LP3 takes a small but nevertheless significant step toward respecting their varying circumstances. While the narrower the bounds on weights, the smaller the step, even the limited freedom embodied in LP3 makes an important difference to some countries. Conclusions Building in the flexibility of varying weights might be a useful way for WHO to respond to the debates and criticisms appearing since publication of the ranking. We conclude by speculating that a variant of LP3 incorporating information regarding which weights are binding, and in which direction, might yield even greater benefits in terms of respecting individual circumstances. Competing interests JAL, CJLM and DBE were part of the team at WHO that developed the methods for the world health system performance rankings published by the Organization in 2000. Abbreviations AHP (Analytical Hierarchy Process) DEA (Data envelopment analysis) LP (Linear program) LP1 (Linear Program 1) LP2 (Linear Program 2) LP3 (Linear Program 3) WHO (World Health Organization) Authors' contributions JAL developed methods inspired by the benefit-of-the-doubt concept and drafted an earlier version of the manuscript. CAKL adapted and applied the DEA methods described here to health system performance and drafted the initial version of the current manuscript. CJLM conceived the methods for measuring health system performance. DBE coordinated the research at WHO. All authors revised and approved the manuscript. Pre-publication history The pre-publication history for this paper can be accessed here: Supplementary Material Additional File 1 Annex.Graphical interpretation of DEA and conceptual links with value theory.doc Click here for file Figures and Tables Figure 1 Graphical array showing LP attainment scores vs WHO attainment scores (left column) and LP ranks vs WHO ranks (right column). From top to bottom, WHO vs LP1, LP2, and LP3, respectively. Table 1 Country means and survey types. Mean survey weight Survey country Health level Health distribution Responsiveness level Responsiveness distribution Fair financing Survey type Argentina 0.26 0.25 0.13 0.13 0.24 briefa Australia 0.23 0.21 0.15 0.14 0.27 postalb Austria 0.23 0.20 0.15 0.14 0.28 postal Bahrain 0.26 0.17 0.17 0.13 0.27 brief Belgium 0.24 0.25 0.13 0.14 0.25 brief Bulgaria 0.25 0.22 0.13 0.13 0.27 brief Canada 0.25 0.17 0.16 0.13 0.29 brief Chile 0.20 0.21 0.15 0.15 0.29 brief China 0.27 0.21 0.15 0.12 0.25 postal Costa Rica 0.28 0.25 0.12 0.12 0.22 brief Croatia 0.25 0.24 0.13 0.13 0.25 brief Cyprus 0.25 0.23 0.14 0.13 0.25 postal Czech Republic 0.29 0.22 0.14 0.12 0.24 brief, postal Denmark 0.26 0.21 0.15 0.12 0.25 postal Egypt 0.26 0.22 0.14 0.12 0.26 postal Estonia 0.27 0.22 0.14 0.11 0.25 brief Finland 0.25 0.21 0.14 0.12 0.27 brief, postal France 0.24 0.23 0.14 0.13 0.26 brief, postal Germany 0.24 0.22 0.13 0.14 0.28 brief Greece 0.25 0.21 0.15 0.13 0.26 postal Hungary 0.24 0.20 0.16 0.13 0.27 postal Iceland 0.26 0.20 0.14 0.13 0.26 brief Indonesia 0.26 0.22 0.15 0.13 0.24 brief Ireland 0.24 0.25 0.13 0.13 0.26 brief Italy 0.24 0.23 0.14 0.14 0.25 brief Jordan 0.26 0.18 0.16 0.12 0.27 brief Kyrgyzstan 0.25 0.22 0.13 0.13 0.26 postal Latvia 0.24 0.19 0.15 0.12 0.30 brief Lithuania 0.24 0.23 0.15 0.13 0.25 postal Luxembourg 0.25 0.23 0.13 0.13 0.26 telephonec Malta 0.25 0.23 0.13 0.14 0.24 brief Morocco 0.19 0.18 0.17 0.17 0.29 brief Netherlands 0.24 0.18 0.17 0.14 0.28 brief, postal New Zealand 0.24 0.22 0.15 0.13 0.26 brief Oman 0.25 0.18 0.18 0.14 0.25 brief Poland 0.24 0.22 0.14 0.12 0.27 brief Portugal 0.24 0.25 0.13 0.13 0.25 brief Republic of Korea 0.28 0.21 0.14 0.12 0.25 brief Romania 0.25 0.22 0.14 0.13 0.26 brief Russian Federation 0.25 0.17 0.17 0.12 0.29 brief Spain 0.26 0.24 0.13 0.13 0.24 brief Sweden 0.23 0.20 0.15 0.14 0.28 brief Switzerland 0.22 0.21 0.15 0.15 0.27 postal Thailand 0.21 0.19 0.16 0.16 0.28 brief Trinidad and Tobago 0.24 0.22 0.14 0.13 0.26 brief Turkey 0.24 0.23 0.13 0.13 0.27 postal Ukraine 0.26 0.22 0.14 0.12 0.26 brief United Arab Emirates 0.23 0.17 0.18 0.14 0.28 brief United Kingdom 0.26 0.22 0.14 0.12 0.26 postal United States of America 0.24 0.20 0.15 0.16 0.25 postal Venezuela 0.28 0.23 0.13 0.11 0.25 brief Sample minimum 0.19 0.17 0.12 0.11 0.22 Sample maximum 0.29 0.25 0.18 0.17 0.30 abrief = brief face-to-face survey (Üstün et al. 2001). bpostal = postal survey (Üstün et al. 2001). c telephone = computer-assisted telephone survey (Üstün et al. 2001). Table 2 Summary Statistics WHO LP1 LP2 LP3 Mean (%) 73.30 95.18 85.15 79.28 Standard deviation (%) 12.34 4.79 11.34 14.98 Interquartile range (%): First quartile 63.64 92.99 78.12 69.42 Second quartile 75.39 96.00 87.91 83.37 Third quartile 81.65 99.05 93.25 89.83 Fourth quartile 93.45 100.00 100.00 100.00 Table 3 Rank Correlations. WHO LP1 LP2 LP3 WHO 1.00 0.71 0.96 0.97 LP1 1.00 0.75 0.69 LP2 1.00 0.99 LP3 1.00 ==== Refs Evans DB Tandon A Murray CJL Lauer J The comparative efficiency of national health systems in producing health: an analysis of 191 countries Global Programme on Evidence for Health Policy Discussion Paper No 29 2000 Geneva, Switzerland, World Health Organization Evans DB Tandon A Murray CJL Lauer JA Comparative efficiency of national health systems: cross national econometric analysis BMJ 2001 323 307 310 11498486 10.1136/bmj.323.7308.307 Tandon A Murray CJL Lauer J Evans DE Measuring overall health system performance for 191 countries Global Programme on Evidence forHealth Policy Discussion Paper No 30 2000 Geneva, Switzerland, World Health Organization World Health Organization The World Health Report 2000: Health systems: Improving performance Geneva, World Health Organization 2000 Murray CJ Frenk J A framework for assessing the performance of health systems Bull World Health Organ 2000 78 717 731 10916909 Navarro V Assessment of the World Health Report 2000 Lancet 2000 356 1598 1601 11075789 10.1016/S0140-6736(00)03139-1 Williams A Science or marketing at WHO? 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BMC Health Serv Res. 2004 Jul 22; 4:19

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==== Front Nutr JNutrition Journal1475-2891BioMed Central London 1475-2891-3-91528202810.1186/1475-2891-3-9Review"A calorie is a calorie" violates the second law of thermodynamics Feinman Richard D 1rfeinman@downstate.eduFine Eugene J 12efine@downstate.edu1 Department of Biochemistry, State University of New York Downstate Medical Center, Brooklyn, NY 11203 USA2 Department of Nuclear Medicine, Jacobi Medical Center, Bronx, NY 10461 USA2004 28 7 2004 3 9 9 21 4 2004 28 7 2004 Copyright © 2004 Feinman and Fine; licensee BioMed Central Ltd.2004Feinman and Fine; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The principle of "a calorie is a calorie," that weight change in hypocaloric diets is independent of macronutrient composition, is widely held in the popular and technical literature, and is frequently justified by appeal to the laws of thermodynamics. We review here some aspects of thermodynamics that bear on weight loss and the effect of macronutrient composition. The focus is the so-called metabolic advantage in low-carbohydrate diets – greater weight loss compared to isocaloric diets of different composition. Two laws of thermodynamics are relevant to the systems considered in nutrition and, whereas the first law is a conservation (of energy) law, the second is a dissipation law: something (negative entropy) is lost and therefore balance is not to be expected in diet interventions. Here, we propose that a misunderstanding of the second law accounts for the controversy about the role of macronutrient effect on weight loss and we review some aspects of elementary thermodynamics. We use data in the literature to show that thermogenesis is sufficient to predict metabolic advantage. Whereas homeostasis ensures balance under many conditions, as a general principle, "a calorie is a calorie" violates the second law of thermodynamics. ==== Body Review The recent awareness of an epidemic of obesity coincides with, and may have contributed to a dramatic increase in the popularity of a variety of low carbohydrate diets. This rapid switch in dietary habits of a significant part of the population, and the virtual revolution in the food industry, is unusual in that it stands in direct opposition to long-standing recommendations of the majority of the nutritional and medical establishment (e.g. [1,2]). Despite isolated examples, such as a recent editorial by Walter Willet pointing to the need to understand low carbohydrate diets [3], there is still little real acceptance by nutrition professionals or health organizations. One aspect of these diets that has been especially controversial is the so-called metabolic advantage – the idea that more weight may be lost calorie for calorie compared with diets of higher carbohydrate content. We recently reviewed the literature on metabolic advantage [4]. We showed that there is a sufficient number of reports in the literature to establish the existence of metabolic advantage and we tabulated results from ten or so studies demonstrating that low carbohydrate diets can lead to greater weight loss than isocaloric low fat diets. The reports we cited have frequently been met with the criticism that the data could not be right because they would violate the laws of thermodynamics ([5,6]). An example is the recent demonstration of metabolic advantage in a small, pilot study [7] which, despite its preliminary status, was extremely well controlled. Three groups were studied: A low carbohydrate group (LoCHO = 1800 kcal for men; 1500 kcal for women), a low fat group (LoFat, 1800 and 1500); a third group also consumed a low carbohydrate diet but an additional 300 kcalories were provided (LoCHO+300, 2100 and 1800). The order of average amount of weight lost was LoCHO = 23 lbs, LoCHO+300 = 20 lbs LoFat = 17 lbs. This work received a good deal of attention in the popular press. Media reports, however, included comments of experts that "It doesn't make sense, does it?" "It violates the laws of thermodynamics. No one has ever found any miraculous metabolic effects." ([5]). If this is an accurate quotation, it is odd indeed. Miraculous, or otherwise, a metabolic effect was found. In the absence of an identifiable methodological error, experimental data has to be accepted and numerous investigations, in fact, serve as precedents for Greene et al.'s findings (Reviews: [4,8]). In our previous review of metabolic advantage [4] we showed that there is, in fact, no theoretical violation of the laws of thermodynamics, and we provided a plausible mechanism. In general the pathways for gluconeogenesis that are required in order to supply obligate glucose (e.g. to brain and CNS), in combination with increased protein turnover, could account for the missing energy. Here, we simplify the thermodynamic argument and review some of the relevant principles. We show, moreover, that well-established data in the traditional nutritional literature predict metabolic advantage and no one should be surprised. The ironic conclusion is that the principle that weight gain on isocaloric diets must always be independent of macronutrient composition would violate the second law of thermodynamics. What do we mean by "a calorie is a calorie?" Because it is a colloquial phrase, it is important to understand exactly what it is meant by "a calorie is a calorie." The most common meaning is that is it impossible for two isocaloric diets to lead to different weight loss. Frequently, the concept is justified by reference to the "laws of thermodynamics", but an explicit connection has never been spelled out. More recently, Buchholz & Schoeller [10] appear to identify "a calorie is a calorie" with the first law of thermodynamics. They also admit that high protein /low carbohydrate diets can lead to greater weight loss than isocaloric low fat diets in agreement with our assessment [4]. Nonetheless they maintain that "a calorie is a calorie," now justifying it by their connection of the phrase to the concept of energy conservation. It is important to point out that no study of isocaloric diets has ever claimed that the first law of thermodynamics is not true. Buchholz & Schoeller [10] have limited themselves by only including the first law and, therefore, do not understand how the differential weight loss could occur and think it "deserves further study." Our major point here is that there is more than one law of thermodynamics and that a more accurate understanding of the role of the second law shows that differential weight loss is not inconsistent with any physical principle. Thermodynamics The idea that "a calorie is a calorie" comes from a misunderstanding of the laws of thermodynamics. There are two laws of thermodynamics. (The zeroth law that establishes the concept of temperature and the third law that describes absolute zero are not relevant here). When speaking of "the laws of thermodynamics" it is important to be sure that one is including the second law. The first law is very different in character from the second law [9,11,12]. The first law is a conservation law: it says that the form of energy may change, but the total is always conserved. The second law is a dissipation law: it defines a quantity, the entropy, S, which we traditionally identify with disorder or high probability. The second law says that in any (real) irreversible process, the entropy must increase (ΔS > 0); balance is not expected. Entropy is, in fact, identifiable with irreversibility. It is important to understand that it is the second law that drives chemical reactions. The first law is a bookkeeping law and tells us that the total energy attributed to work, heat and changes in chemical composition will be constant. It does not tell us whether such a reaction will occur, or if it does, what the relative distributions of the forms of energy will be. To predict the tendency of the reaction to occur, we must employ the second law that says the entropy must increase. In a chemical reaction, at constant temperature and pressure, the entropic and energetic effects are combined into the change in the Gibbs free energy, ΔG, whose sign predicts the direction of reaction, and whose magnitude indicates the maximum amount of work realizable from the reaction. Application of ΔG' To understand the implications of "a calorie is a calorie," that energy yield could be path-independent and the same for all diets consider that it implies that carbohydrate and protein are equivalent fuels as shown in Figure 1. The diagram indicates that, because it is a state variable, the free energy (ΔG') for Path 1 must be equal to that for path 2 + 3. If the ΔG' values for path 1 and path 2 are taken to be their calorimeter values, they will be approximately equal (~4 kcal/g, path 1 corrected for ureagenesis). This means that ΔG' for path 3, the conversion of protein to carbohydrate (also corrected) must be about zero. There exists at least one condition where this is not true, the standard state; it is generally considered that gluconeogenesis from one mole of alanine requires about 6 ATP [13,14]. Of course free energies are concentration dependent, so in vivo values will differ from standard state values but they are continuous functions of the concentrations and there will be numerous conditions under which ΔG' is not zero. In other words, assuming that protein and carbohydrate are energetically equivalent leads to a contradiction. Figure 1 Pathways for oxidation of macronutrients. Inefficiency The second law was developed in the context of the industrial revolution and the attempt to understand the efficiency of machines. The law describes the theoretical limits on the efficiency of engines and applies as well to living (irreversible) systems. The second law says that no machine is completely efficient. Some of the available energy is lost as heat and in the internal rearrangement of chemical compounds and other changes in entropy. In other words, although the first law holds even in irreversible processes – energy is still conserved – the second law says that something is lost, something is unrecoverable. The efficiency of a machine is dependent on how the machine works and, for a biochemical machine, the nature of the fuel and the processes enlisted by the organism. A simple example is the inefficiency of low-test gasoline in high compression gasoline engines. If a "calorie is a calorie" were true, nobody would pay extra for high test gasoline. (The calorimeter values of a gasoline will be the same whether or not it contains an antiknock compound). In weight loss diets, of course, inefficiency is desirable and is tied to hormonal levels and enzyme activities Efficiency and thermogenesis In nutrition, one component of inefficiency is measured in thermogenesis (thermic effect of feeding), or the heat generated in processing food. There is a large literature on this subject and the general conclusion, as summarized in a recent review by Jéquier [15], is that thermic effects of nutrients is approximately 2–3 % for lipids, 6–8 % for carbohydrates, and 25–30% for proteins. It is interesting that this data itself might be enough to explain metabolic advantage. Here we took the average of Jéquier's values (2.5, 7 and 27.5 % for fat, CHO and protein) and calculated the effective energy yield for a 2000 kcal diet. If we assume a diet composition of CHO:fat: protein of 55:30:15, within the range of commonly recommended diets, the calculated effective yield is 1848 kcal. We now consider the effect of reducing carbohydrate progressively and substituting the calories removed equally between fat and protein. Figure 2 shows that the wasted calories due to thermogenesis increase as carbohydrate is reduced and reach 100 kcal at 21 % carbohydrate. This value of 100 kcal is recommended by several professionals as the goal for daily weight reduction (e.g. [16]). Notably, at 8 % CHO, the value for the early phase of the Atkins [17], South Beach [18] or Protein Power diets [19], 140 kcalories are lost as heat. Now, there will be metabolic accommodations and one can't predict that the ratios will stay the same over a long term diet, but the calculations show that the possibility of metabolic advantage should not come as a surprise. Figure 2 The dependence of effective calories on % carbohydrate in a 2000 kcal diet. Effective calories were determined by subtracting the losses due to thermogenesis as described in the text. Recommendations for fighting obesity frequently call for small reductions in calories [16]. In fact, given the resistance of steady state systems to small perturbations it is doubtful that this is a promising strategy. Nonetheless, taking the goal at face value, if it could be achieved by a simple change in macronutrient composition, such a method would seem worthy of serious consideration. The arguments above show that such a phenomenon is possible. There are plausible arguments for how it could take place and substantial experimental evidence for its occurrence [4]. Conclusions A review of simple thermodynamic principles shows that weight change on isocaloric diets is not expected to be independent of path (metabolism of macronutrients) and indeed such a general principle would be a violation of the second law. Homeostatic mechanisms are able to insure that, a good deal of the time, weight does not fluctuate much with changes in diet – this might be said to be the true "miraculous metabolic effect" – but it is subject to many exceptions. The idea that this is theoretically required in all cases is mistakenly based on equilibrium, reversible conditions that do not hold for living organisms and an insufficient appreciation of the second law. The second law of thermodynamics says that variation of efficiency for different metabolic pathways is to be expected. Thus, ironically the dictum that a "calorie is a calorie" violates the second law of thermodynamics, as a matter of principle. The analysis above might be said to be over-kill although it is important, intellectually, not to invoke the laws of thermodynamics inappropriately. There are also, however, practical consequences. The seriousness of the obesity epidemic suggests that we attack it with all the means at our disposal. Metabolic advantage with low carbohydrate diets is well established in the literature. It does not always occur but the important point is that it can occur. To ignore its possibilities and to not investigate the precise conditions under which it appears would be cutting ourselves off from potential benefit. The extent to which metabolic advantage will have significant impact in treating obesity is unknown and it is widely said in studies of low carbohydrate diets that "more work needs to be done." However, if the misconception is perpetuated that there is a violation of physical laws, that work will not be done, and if done, will go unpublished due to editorial resistance. Attacking the obesity epidemic will involve giving up many old ideas that have not been productive. "A calorie is a calorie" might be a good place to start. Competing interests None declared. ==== Refs Saltos E The Food Pyramid-Food Label Connection American Heart Association guidelines for weight management programs for healthy adults. AHA Nutrition Committee Heart Dis Stroke 1994 3 221 228 7921668 Willett WC Reduced-carbohydrate diets: no roll in weight management? Ann Intern Med 2004 140 836 837 15148073 Feinman RD Fine EJ Thermodynamics and Metabolic Advantage of Weight Loss Diets. Metabolic Syndrome and Related Disorders 2003 1 209 219 10.1089/154041903322716688 Rolls BJ quoted in October 13, 2003 CBS News [http://www.cbsnews.com/stories/2003/02/15/health/main540776shtml] Bray GA Low-Carbohydrate Diets and Realities of Weight Loss JAMA 2003 289 1853 1855 12684366 10.1001/jama.289.14.1853 Greene P Willett W Devecis J A. Skaf Pilot 12-week feeding weight-loss comparison: Low-fat vs. low-carbohydrate (ketogenic) diets. Obesity Research 2003 11 A23 Westman EC Mavropoulos J Yancy WS Volek JS A Review of Low-carbohydrate Ketogenic Diets Curr Atheroscler Rep 2003 5 476 483 14525681 Kondepudi D Prigogine I Modern Thermodynamics. From Heat Engines to Dissipative Structures 1998 Chichester, John Wiley & Sons Buchholz AC Schoeller DA Is a calorie a calorie? 2004 79 Am J Clin Nutr 8995 9065 Caplan S. Roy Essig A Bioenergetics and linear nonequilibrium thermodynamics. The steady state. 1983 Cambridge, MA, Harvard University Press Carter W. Craig About Thermodynamics [http://pruffle.mit.edu/300/Syllabus_web/node5html] 2002 Voet D Voet JG Fundamentals of Biochemistry 2004 3rd New York, John Wiley & Sons Devlin TM Textbook of Biochemistry with Clinical Correlations 2002 Fifth New York, John Wiley Sons, Inc. Jequier E Pathways to obesity Int J Obes Relat Metab Disord 2002 26 Suppl 2 S12 7 12174324 10.1038/sj.ijo.0802123 Hill JO Wyatt HR Reed GW Peters JC Obesity and the environment: where do we go from here? Science 2003 299 853 855 12574618 10.1126/science.1079857 Atkins RC Dr. Atkins' New Diet Revolution 2002 New York, Avon Books Agatston A The South Beach Diet 2003 New York, Random House Eades MR Eades MD Protein Power 1996 New York, Bantam Books

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==== Front Int J Health GeogrInternational Journal of Health Geographics1476-072XBioMed Central London 1476-072X-3-141527293010.1186/1476-072X-3-14MethodologyAccounting for regional background and population size in the detection of spatial clusters and outliers using geostatistical filtering and spatial neutral models: the case of lung cancer in Long Island, New York Goovaerts Pierre 1goovaerts@biomedware.comJacquez Geoffrey M 1jacquez@biomedware.com1 Biomedware, Inc., Ann Arbor, MI, USA2004 23 7 2004 3 14 14 14 6 2004 23 7 2004 Copyright © 2004 Goovaerts and Jacquez; licensee BioMed Central Ltd.2004Goovaerts and Jacquez; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background Complete Spatial Randomness (CSR) is the null hypothesis employed by many statistical tests for spatial pattern, such as local cluster or boundary analysis. CSR is however not a relevant null hypothesis for highly complex and organized systems such as those encountered in the environmental and health sciences in which underlying spatial pattern is present. This paper presents a geostatistical approach to filter the noise caused by spatially varying population size and to generate spatially correlated neutral models that account for regional background obtained by geostatistical smoothing of observed mortality rates. These neutral models were used in conjunction with the local Moran statistics to identify spatial clusters and outliers in the geographical distribution of male and female lung cancer in Nassau, Queens, and Suffolk counties, New York, USA. Results We developed a typology of neutral models that progressively relaxes the assumptions of null hypotheses, allowing for the presence of spatial autocorrelation, non-uniform risk, and incorporation of spatially heterogeneous population sizes. Incorporation of spatial autocorrelation led to fewer significant ZIP codes than found in previous studies, confirming earlier claims that CSR can lead to over-identification of the number of significant spatial clusters or outliers. Accounting for population size through geostatistical filtering increased the size of clusters while removing most of the spatial outliers. Integration of regional background into the neutral models yielded substantially different spatial clusters and outliers, leading to the identification of ZIP codes where SMR values significantly depart from their regional background. Conclusion The approach presented in this paper enables researchers to assess geographic relationships using appropriate null hypotheses that account for the background variation extant in real-world systems. In particular, this new methodology allows one to identify geographic pattern above and beyond background variation. The implementation of this approach in spatial statistical software will facilitate the detection of spatial disparities in mortality rates, establishing the rationale for targeted cancer control interventions, including consideration of health services needs, and resource allocation for screening and diagnostic testing. It will allow researchers to systematically evaluate how sensitive their results are to assumptions implicit under alternative null hypotheses. ==== Body Background Cancer mortality maps are important tools in health research, allowing the identification of spatial patterns, clusters and disease 'hot spots' that often stimulate research to elucidate causative relationships [1,2]. In most spatial analysis software a statistical pattern recognition approach has been implemented whereby a statistic (e.g. spatial cluster statistic, autocorrelation statistic, etc.) quantifying a relevant aspect of spatial pattern is calculated. The value of this statistic is then compared to the distribution of that statistic's value under a null spatial model. This provides a probabilistic assessment of how unlikely an observed spatial pattern is under the null hypothesis [3]. Waller and Jacquez [4] formalized this approach by identifying five components of a test for spatial pattern. 1. The test statistic quantifies a relevant aspect of spatial pattern (e.g. Moran's I, Geary's c, LISA, a spatial clustering metric, etc.) 2. The alternative hypothesis describes the spatial pattern that the test is designed to detect. This may be a specific alternative, such as clustering near a focus, or it may be the omnibus "not the null hypothesis". 3. The null hypothesis describes the spatial pattern expected when the alternative hypothesis is false (e.g. Complete Spatial Randomness, often called CSR). 4. The null spatial model is a mechanism for generating the reference distribution. This may be based on distribution theory, or it may use randomization (e.g. Monte Carlo) techniques. 5. The reference distribution is the distribution of the test statistic when the null hypothesis is true. CSR is the null hypothesis employed by most, if not all, statistical tests for spatial pattern, and is the workhorse of almost all spatial statistical software. Examples of statistics used in these tests include spatial autocorrelation (e.g. Moran's I and Geary's c); its local counterpart (e.g. LISA); geographic boundary statistics (e.g. boundary count and mean length), and a host of techniques for identifying hot spots, cold spots and foci. While CSR is useful in some situations, it often is not a relevant null hypothesis for highly complex and organized systems such as those encountered in the environmental and health sciences [5,6]. For such fields CSR may be not relevant because spatial randomness rarely, if ever, occurs – some spatial pattern is almost always present. Hence in many situations rejecting CSR has little scientific value because CSR does not describe any plausible state of the system. As emphasized by Ord and Getis [7], Type I errors may abound when statistical tests are applied without regard to the global autocorrelation structure. For example, locations would be identified as hot spots simply because they lie in areas of generally high (or low) values, which would lead one to blend together local peaks and clusters of high (low) values. Even when health professionals are interested in identifying areas with generally high (or low) disease rates, it is still important to account for spatial autocorrelation to avoid an over-identification of the number of significant spatial clusters or outliers. In summary what are needed are realistic models that incorporate background pattern – the spatial and multivariate structure found when the null hypothesis is true. The term "Neutral Model" captures the notion of a plausible system state that can be used as a reasonable null hypothesis (e.g. "background variation"). The problem then is to identify spatial patterns above and beyond that incorporated into the neutral model, enabling, for example, the detection of cancer clusters beyond background or regional variation in the risk of developing cancer. Neutral models can be generated using simulation techniques developed in the field of geostatistics [8] which provides a set of statistical tools for analyzing and mapping data distributed in space and time. In particular, sequential Gaussian simulation (SGS) allows one to generate realizations of the spatial distribution of rates that reproduce the sample histogram and spatial patterns displayed by the data, and also account for any auxiliary data or information on the local trend [9]. The objective of this paper is to present geostatistical approaches to generating neutral models that account for the spatial dependence of cancer rates, their regional background and spatially heterogeneous population sizes. These models are then used for the detection of local clusters and anomalies in cancer rates. The new methodology is applied to the analysis of the geographical distribution of lung cancer in three counties of Long Island, New York, which have been investigated under the CSR hypothesis in a previous issue of this journal [10,11] Methods Data The use of neutral models in cluster analysis will be illustrated using the lung cancer data analysed in [10,11]. This section briefly summarizes the salient features of this dataset, and readers are referred to the above papers for a detailed description. The New York State Department of Health (NYSDOH) published the cancer incidence data online as part of their Cancer Surveillance Improvement Initiative, . Data have been released on the following four cancers: breast (female only), colorectal (female and male), lung (female and male), and prostate. These data represent newly diagnosed cancer cases in the period 1993–7 assigned to the patient's residence at diagnosis, and they are calculated as the number of cancers for each 100,000 people in the population. To protect patient privacy, the NYSDOH data provided case counts referenced to ZIP codes rather than individual residences. While ZIP codes are somewhat arbitrary spatial units of analysis with respect to potential health and environmental factors, they provide a convenient way to group the population and preserve confidentiality. The methods presented here do not depend on the spatial unit of aggregation and the reader may use census geography if that is their preference. As in the earlier analysis [10,11], the focus of this study is on the 214 ZIP codes within Nassau, Queens and Suffolk County on Long Island. Because cancer incidence is related to age, NYSDOH calculated the expected cancer incidence for each ZIP code using the ZIP code's age structure and the average incidence by age class for New York State (direct adjustment). We thus are using an external standard (the state average) rather than an internal standard (the average for Long Island), to calculate the expected incidence. A standardized morbidity ratio (SMR) has been calculated by dividing the observed value by the age-adjusted expected incidence. An SMR value of 1.0 indicates that the observed incidence is the same as expected, lower than 1.0 indicates that fewer than expected cases of cancer occurred, and greater than 1.0 indicates that more than expected occurred. Local cluster analysis under CSR Jacquez and Greiling [10] identified significant clustering and spatial outliers in SMR using Anselin's local Moran test [12] in the ClusterSeer™ Software . The local Moran test evaluates local clustering or spatial autocorrelation by computing the contribution of each location to the Moran's I statistics for the whole study area. Its null hypothesis is that there is no association between SMR values in neighboring ZIP codes. The working (alternative) hypothesis is that spatial clustering exists. For each ZIP code, referenced geographically by its centroid with the vector of spatial coordinates u = (x, y), the LISA (Local Indicator of Spatial Autocorrelation) statistic is computed as: where z(u) is the SMR for the ZIP code being tested, which is referred to as the "kernel" hereafter. z(uj) are the values for the J(u) neighboring ZIP codes that are here defined as units sharing a common border or vertex with the kernel u (1-st order queen adjacencies). All values are standardized using the mean m and standard deviation s of the SMR data (here 214 values). Since the standardized values have zero mean, a negative value for the LISA statistics indicates a spatial outlier where the kernel value is much lower or much higher than the surrounding values (e.g. SMR is below the global zero mean while the neighborhood average is above the global zero mean, or conversely). Cluster of low or high values will lead to positive values of the LISA statistics (e.g. both kernel and neighborhood averages are jointly above zero or below zero). In addition to the sign of the LISA statistics, its magnitude informs on the extent to which kernel and neighborhood values differ. To test whether this difference is significant or not, a Monte Carlo simulation is conducted, which traditionally consists of sampling randomly and without replacement the global distribution of observed rates (i.e. sample histogram), then computing the corresponding simulated neighborhood averages. This operation is repeated many times (e.g. L = 999 draws) and these simulated values are multiplied by the kernel value to produce a set of L simulated values of the LISA statistics at location u: with z(l)(uj) = F-1[p(l)(uj)], F[.] is the sample cumulative distribution function (cdf), and p(l)(uj) is a random number uniformly distributed within 0 and 1. This set represents a numerical approximation of the probability distribution of the LISA statistics at u, under the assumption of spatial independence. The observed LISA statistics, LISA(u), can then be compared to the probability distribution, allowing the computation of the probability of not rejecting the null hypothesis (so-called p-value). Following Jacquez and Greiling [10], we used an adjusted significance level α = 0.01101 to account for the fact that the multiple tests (i.e. 214 in this study) are not independent since near ZIP codes share similar neighbors. This significance level was obtained using the Bonferroni adjustment which amounts at dividing the significance level α = 0.05 by the average number of neighbors in each test. Thus, every ZIP code where the p-value is lower than 0.01101 will be classified as a significant spatial outlier (HL: high value surrounded by low values, and LH: low value surrounded by high values) or cluster (HH: high value surrounded by high values, and LL: low value surrounded by low values). A typology of neutral models The use of CSR as the null hypothesis means that the distribution of cancer rates is assumed to be spatially random (no autocorrelation) with uniform risk over the study area. In most cases, however, mortality rates are spatially correlated while the risk of developing cancer varies regionally as a result of changes in environmental exposure or other demographic, social, and economic factors. Another weakness of the above test is that it does not consider whether ratio data are based on many or a few cases, thereby ignoring the instability of rates computed from small population sizes. The basic idea of the proposed approach is to generate neutral models that are more realistic in the sense that they incorporate presence of spatial autocorrelation, non-uniform risk, and account for spatially heterogeneous population sizes. Table 1 provides a typology of neutral models that could be used for inference regarding numerator and denominator, including incidence and prevalence, as well as mortality rates. Model I corresponds to the CSR case, while model II reproduces the spatial correlation of the cancer rates. Model III reflects the situation where environmental exposures or other factors make the risk non-uniform. Models IV through VI allow one to account for the impact of population size on the stability of observed rates. Unlike Model I these more complex neutral models can not be generated simply by shuffling randomly the SMR data across the 214 ZIP codes, and geostatistical simulation techniques to generate each type of model are described below. Table 1 Typology of neutral models. Models differ according to the reproduction of spatial correlation, the incorporation of non-uniform risk, and the filtering of noise caused by spatially varying population sizes. Risk Accounting for Population size No Yes Uniform, spatially random I IV Uniform, spatially correlated II V Heterogeneous, spatially correlated III VI Normal score transform of SMR data The simulation techniques used in this paper assume a multiGaussian distribution for the variable under study, which requires a prior normal score transform of SMR data to ensure that at least their univariate distribution (histogram) is normal. Normal score transform is a graphical transform that allows one to normalize any distribution, regardless of its shape. It can be seen as a correspondence table between equal p-quantiles zp and yp of the z-cdf F(z) (cumulative histogram) and the standard Gaussian cdf G(y). In practice, the normal score transform proceeds in three steps: 1. The N original data z(uα) (i.e. SMR data) are first ranked in ascending order. Since the normal score transform must be monotonic, ties in z-values must be broken, which has been done randomly as implemented in GSLIB software [13]. 2. The sample cumulative frequency of the datum z(uα) with rank k is then computed as = k/N - 0.5/N. 3. The normal score transform of the z-datum with rank k is matched to the -quantile of the standard normal cdf: y(uα) = φ(z(uα)) = G-1[F(z(uα))] = G-1[] Local cluster analysis under spatial neutral model (Model II) Model II aims to reproduce the pattern of spatial correlation displayed by the data that is here quantified using the normal score semivariogram [8,14] which plots the average squared difference between normal score transformed SMR data as a function of the separation distance and direction between ZIP codes: Here |h| corresponds to the Euclidian distance between two ZIP codes. Note the following discussion can be readily generalized to other distance measures that could be more appropriate to capture contiguity of entities of complex shape: our methodology is general and does not depend on a particular formulation of the distance measures. Following previous simulation studies [9] and in order to account for the noise induced by small population sizes, each pair has been assigned a weight proportional to the square root of the population size, , where n(uα) is the size of the population at risk in the ZIP code with centroid uα. Following an earlier analysis of the data [10], the population in ZIP codes was estimated using 2000 US census numbers. Spatial neutral models are generated using Sequential Gaussian Simulation (SGS) which proceeds as follows (see [8] p. 380 for more details): 1. Fit a permissible function [9] to the experimental semivariogram (Equation 3). The modeling was here performed using least-square regression [15]. All semivariogram models were bounded, that is a sill is reached for a given distance referred to as the range of influence. The covariance models were then derived by subtracting the semivariogram model from the sill value. 2. Define a random path (i.e. using a random number generator) visiting each ZIP code location uα only once. 3. At each location uα determine the mean and variance of the Gaussian probability distribution of y-values as: where y(l)(ui) are normal scores simulated at locations previously visited along the random path and located within a search radius from uα, mY is the stationary mean of the variable Y (which is zero following the normal score transform), and C(ui-uα) is the covariance function of the normal score variable Y for the separation vector hiα = ui-uα. λi are kriging weights obtained by solving the following system of linear equations (simple kriging, SK): 4. Draw a simulated value from the conditional cumulative distribution function (ccdf) of probability and add it to the data set. In other words, the simulated value at uα is , where p(l) is a random number between 0 and 1. 5. Proceed to the next location along the random path, and repeat the two previous steps. 6. Loop until all N locations (i.e. N = 214 here) are simulated. 7. Transform the simulated normal scores {y(l)(uα); α = 1,..., N} so that the target histogram (in this case the global distribution of observed rates, F[.]) is reproduced: z(l)(uα) = F-1[p(l)(uα)] with p(l)(uα) = G[y(l)(uα)] The procedure is repeated using a different random path and set of random numbers to generate another realization. Note that these realizations account for only the histogram and semivariogram model of the SMR data (global conditioning), but they are non-conditional to the SMR data themselves (e.g. location of zones of high or low SMR values). Once the L sets of N simulated SMR values, {z(l)(uα); α = 1,..., N} have been generated, Equation (2) is applied to each member of this set to compute the simulated values of the LISA statistics at each location u. The simulated LISA values form the empirical distribution of the LISA statistics, allowing the calculation of the p-value for the test of hypothesis. Local cluster analysis under a locally constrained spatial neutral model (Model III) The simulation of neutral model II is conducted using a stationary mean for SMR values, which is unrealistic for situations where environmental exposure or other factors make the risk non-uniform. In this instance the researcher wishes to detect spatial pattern above and beyond this non-uniform risk. For example, one might want to detect clusters of melanoma beyond those that are explained by the north-south gradient in solar radiation. Non-uniform risk can easily be accounted for in the simulation procedure by replacing the stationary mean mY in Equation 4 by locally varying means mY(uα), that is using the following estimate for the mean and variance of the Gaussian ccdf: where CR(ui-uα) is the covariance function of the residual normal score variable [Y(uα) - mY(uα)] for the separation vector hiα = ui-uα, and the kriging weights are obtained by solving the following system of linear equations (simple kriging with local means, SKlm): The first step in the generation of model III is the computation of the local means mY(uα), which define the reference background risk the user wants to consider for the null hypothesis. In this paper a smooth model of background risk values was obtained by using the following kriging estimator of the local means of observed SMR data: The kriging weights are calculated in two-steps. First, the following "kriging of the local mean" system [8] is solved: Then, to incorporate data reliability due to spatially varying population size directly into the geostatistical filter the kriging weights are rescaled, following [9], as: This rescaling is applied separately to the negative and positive kriging weights, keeping constant the overall contribution of these two sets of weights; that is the sum of positive (negative) kriging weights is the same before and after rescaling, which ensures that the unbiasedness constraint in system (11) is still satisfied. Note that although the population size is incorporated in the estimation of the local means, it is not accounted for directly into the test of hypothesis, which will be achieved using Models IV through VI introduced below. Once the local means of the normal score transformed SMR data have been estimated, they are subtracted from the SMR values and the semivariogram of residuals is estimated and modelled. Then, the simulation is performed using SGS and SKlm. Last, the L realizations are used to derive the empirical probability distribution of the LISA statistics and the p-value of the test is computed. Accounting for population size in local cluster analysis (Models IV to VI) The neutral models introduced so far ignore the fact that cancer rates estimated over small areas, such as United States ZIP code areas or census tracts, tend to be less reliable [16,17], hence larger fluctuations among simulated rates are expected at these locations. If ignored, large differences in population size decrease the ability of Moran's I to detect true clustering. There are essentially three approaches to incorporate population sizes in cluster detection: 1) randomly shuffle the cases rather than the rates (i.e. under a heterogeneous Poisson model the cases are allocated to each area using hypergeometric sampling [18]), 2) use a modified version of the test statistics (i.e. Oden's I pop [19] or Waldhör's I [20]), and 3) transform or standardize the rates first, then compute the LISA statistics on the results (i.e. Empirical Bayes Index [21], Cressie's transform [14 p.385–402], or any other smoothing algorithm [17,22]). In this paper, the third approach has been adopted and the noise caused by small population sizes was filtered using a variant of the estimator introduced in equation 10: The kriging weights are calculated in two-steps. First, the following system is solved: with g0 = b0 × (1-δ(ui-uα)) where b0 is the nugget variance in the weighted semivariogram model of SMR data, and δ(ui-uα) = 0 if ui = uα and 1 otherwise. Then, to incorporate data reliability (i.e. population size) directly into the geostatistical filter the kriging weights are rescaled according to Equation 12. The ability of the proposed approach to reconstruct the underlying disease risk from observed mortality rates has been tested in extensive simulation studies [9]. Results and discussion Generating spatial neutral models Figures 1 and 2 (top graphs) show the geographic distribution of lung cancer in males and females (aggregated to the ZIP code level), in Long Island, New-York. Middle graphs show the experimental weighted semivariograms computed in four directions from the normal score transforms of SMR data. For both males and females SMR normal scores exhibit a range of autocorrelation of about 15 km, with smaller variability (i.e. lower semivariogram values) observed along the NW-SE direction. The spatial anisotropy is less pronounced for female lung cancer and an isotropic model was fitted (solid black line). Regional background is further revealed once the noise and short-range variability of SMR data has been removed using factorial kriging (Equation 10) and the semivariogram model fitted to sampled values (solid line in middle graphs), see Figures 1 and 2 (bottom graph). High SMR values are recorded mainly along the Southern shore of the Island for both genders, while differences between males and females are more striking for low value: the lowest SMR values are observed in the westernmost part of Long Island for females and slightly more to the east for the males. These maps of regional background were subtracted from the original SMR maps, and the spatial autocorrelation of the corresponding residuals was quantified using the experimental semivariograms displayed in Figure 3. Since some of the spatially correlated variability is captured by the regional background, the residual semivariograms show lower sills and shorter ranges relatively to the SMR semivariograms of Figures 1 and 2. Figure 1 Geographic distribution and spatial variability of male lung cancer. The fill color in each ZIP code represents the SMR, with green indicating relatively low SMR and purple representing relatively high SMR (categories correspond to deciles of the histogram of rates). From these rates, a population-weighted semivariogram is computed in four directions. The semivariogram model (solid line) is used to filter the noise and short-range variability of observed SMR, yielding a smooth map of SMR local means (regional background). Figure 2 Geographic distribution and spatial variability of female lung cancer. The fill color in each ZIP code represents the SMR, with green indicating relatively low SMR and purple representing relatively high SMR (categories correspond to deciles of the histogram of rates). From these rates, a population-weighted semivariogram is computed in four directions. The semivariogram model (solid line) is used to filter the noise and short-range variability of observed SMR, yielding a smooth map of SMR local means (regional background) Figure 3 Residual semivariograms for male and female lung cancer. The regional background displayed at the bottom of Figures 1 and 2 is subtracted from the maps of SMR data, and the spatial variability of these residuals is characterized by population-weighted semivariograms computed in four directions. One hundred realizations of neutral Models I through III were generated using Sequential Gaussian simulation and the information displayed in Figures 1 to 3. The first two realizations of each model for male lung cancer are displayed in Figure 4. The two top maps (model I), which were obtained by shuffling randomly the 214 ZIP code SMR data in Figure 1 (top map), illustrate the simplistic nature of CSR as null hypothesis in cluster detection. Spatial patterns are reproduced by the middle maps (Model II) where one notices groups of low and high simulated SMR values the position of which changes from one realization to the next since the simulation is not conditioned locally to the observed rates. The regional background displayed in Figure 1 (bottom graph) is incorporated in Model III, which reduces fluctuations among realizations and led, for example, to high SMR values being consistently simulated in the central part of Long Island. Figure 4 Different neutral models for male lung cancer. The fill color in each ZIP code represents the simulated SMR, with green indicating relatively low SMR and purple representing relatively high SMR (categories correspond to deciles of the histogram of simulated rates). Simulated maps (realizations) of the spatial distribution of lung cancer SMR data are generated under the assumption of complete spatial randomness (Model I), or created using geostatistical simulation in order to reproduce the spatial autocorrelation displayed by observed rates (Model II) as well as the regional background, i.e. SMR local means (Model III). Accounting for population size in spatial neutral models Population in Long Island ZIP codes can vary substantially, ranging from 445 to 105,723, with a mean of 23,298, see Figure 5 (top graph). Population sizes also display a strong spatial pattern, with a gradient from highly populated ZIP codes in the western part of Long Island to the sparsely populated eastern part. The scattergrams in Figure 5 illustrate how the population size impacts the magnitude of fluctuations among SMR data. As the ZIP codes become less populated the variability among SMR values increases, which reflects the smaller reliability of the rates inferred from small populations at risk and makes problematic the later detection of clusters or spatial outliers. Figure 5 Geographic distribution of population size (male + female) and its impact on stability of SMR values. The fill color in each ZIP code represents the 2000 population size, with green indicating sparsely populated ZIP codes and purple representing larger population sizes (categories correspond to deciles of the histogram of sizes). The scatterplots illustrate the larger spread of measured SMR for ZIP codes with low population and how the extreme rates recorded in these ZIP codes are smoothed by geostatistical filtering. Using factorial kriging and the SMR semivariogram models displayed in Figures 1 and 2, the noise caused by small population sizes was geostatistically filtered from SMR maps: compare filtered maps in Figure 6 with original maps shown at the top of Figures 1 and 2. While the noise filtering does not change the mean of the SMR data, their standard deviation decreases: 0.290 to 0.238 for males and 0.355 to 0.329 for females. The larger decrease observed for male SMR values is caused by the higher amount of noise (i.e. relative nugget effect) reflected as the discontinuity at the origin of the semivariogram. The scattergrams at the bottom of Figure 5 indicate that the geostatistical filtering changes mainly the extreme rates recorded for sparsely populated ZIP codes. Then, one hundred realizations of neutral Model IV through VI were generated using Sequential Gaussian simulation and the filtered SMR maps statistics. Figure 6 Geostatistical filtering of male and female lung cancer data. The fill color in each ZIP code represents the noise-filtered SMR, with green indicating relatively low SMR and purple representing relatively high SMR (categories correspond to deciles of the histogram of filtered rates). Local cluster analysis under various neutral models Female Figures 7 and 8 show the results of the cluster analysis for female SMR values under the neutral models I through VI, while Table 2 lists the exact number of ZIP codes classified as significant clusters of high values (HH) or low values (LL), and outliers (LH and HL). Table 2 also indicates how the p-value varies among neutral models, highlighting the fact that depending on the assumption being made, the size and locations of clusters/outliers can change. Figure 7 Results of the local cluster analysis conducted for female lung cancer using neutral models I to III. The fill color in each ZIP code represents the classification into significant low-low or high-high clusters, as well as high-low or low-high outliers. Yellow indicates ZIP codes that have not been found significant using an adjusted significance level α = 0.01101. Figure 8 Results of the local cluster analysis conducted for female lung cancer using neutral models IV to VI. The fill color in each ZIP code represents the classification into significant low-low or high-high clusters, as well as high-low or low-high outliers. Yellow indicates ZIP codes that have not been found significant using an adjusted significance level α = 0.01101. Table 2 Number of significant zip codes for the different types of cluster/outliers and neutral models. Results are reported for female lung cancer. Numbers between parentheses indicate zip codes that have similar classification under the reference Model I (CSR). Summary statistics for the p-values are also provided. Neutral Model Type Model I Model II Model III Model IV Model V Model VI High-High 7 0(0) 4(2) 10(5) 0(0) 3(2) High-Low 1 0(0) 2(0) 0(0) 0(0) 1(0) Low-High 2 0(0) 4(0) 2(2) 0(0) 1(0) Low-Low 18 1(0) 2(2) 31(18) 4(4) 6(4) P-value Mean 0.178 0.230 0.405 0.166 0.237 0.394 CV 85.9% 62.5% 71.3% 95.3% 62.2% 76.9% Under the CSR model (Model I), results similar to the ones reported in [11] were found. First, the local Moran test identified a single, large cluster of low SMR extending through portions of Flushing in the north and Jamaica in the south. Next to this cluster is the only high-low outlier: Oakland Gardens (11364) with a SMR of 1.116. Sayville (11782) is a significant spatial outlier with low SMR (72% of the New York average), though its SMR has a wide confidence interval resulting from the small number of observed cases there (15,896 habitants). Thus, while statistically distinct from its neighbors, it does not have significantly reduced risk. This is also the case for the second low-high outlier, Manorville (11949, 11,384 habitants), which has a SMR close to one but is located in the western part of Long Island where background rates are higher. Several local clusters of high SMR values occurred in the more central portions of Long Island. There is a cluster in north-mid Long Island, made up of two significant local clusters centered on Bayville (11709) and Mill Neck (11765). This cluster has about 60–70% higher SMR than the New York state average. A large cluster in south central Long Island is composed of four local clusters centered on Ronkonkama (11779), Central Islip (11722), Islip Terrace (11752), and East Islip (11730). This cluster has an SMR about 40% higher than the New York state average. Further east is a third cluster of high female lung cancer incidence centered on Mastic (11950) and including several adjacent ZIP codes. Its SMR is about 60% higher than the New York state average. Accounting for spatial autocorrelation (i.e. Model II) leads to a substantial reduction in the size of significant clusters compared to the CSR assumption. In fact only one ZIP code is a significant low-low cluster under Model II: Saint Albans (11412) which was the center of the Southern low-low cluster detected under CSR. The scattergram in Figure 9 (left graph) shows that the use of spatially correlated neutral models leads to larger p-values on average (0.23 vs. 0.18), and those are highly correlated with the ones obtained under CSR (Model I). These larger p-values cause a substantial reduction in the size of significant ZIP codes, since fewer units exceed the adjusted significance level α of 0.01101. The reason for that increase in p-values is illustrated for the ZIP code #11364 (Oakland Gardens) which was the only unit classified as high-low outlier under neutral model I. Figure 10 (left top graph) shows the distribution of simulated values of the LISA statistics for that ZIP code. Clearly, the variance of the distribution is much larger than the results obtained under CSR, while both means are equal to zero. The spatial autocorrelation of simulated rates increases the likelihood that the J neighboring values are jointly small or high, causing the neighborhood average, hence the LISA value, to exhibit much larger fluctuations among realizations. Consequently, the probability that the observed LISA statistics falls in the tails of the simulated distribution decreases, leading to a larger p-value (0.061 versus 0.003) and a ZIP code that is no longer a significant outlier. Figure 9 Scatterplots of the p-values obtained when conducting the local cluster analysis under CSR assumption (Model I) or more complex neutral models. Model III reproduces the pattern of spatial correlation as well as the regional background of SMR values, while Model II accounts only for the spatial correlation. Figure 10 Histograms of the values of the LISA statistics simulated for ZIP code #11364 (Oakland Gardens) under different neutral models. The black dot denotes the observed LISA statistics which lies inside the 0.95 probability interval for all models except Models I and IV developed under the CSR assumption. The map of significant ZIP codes at the bottom of Figure 7 bears little resemblance with the maps obtained under the neutral models I and II. This is expected since Model III addresses a different question, namely the detection of local departures from the regional background. Thus, in general, one would expect HL and LH outliers to be more frequent than spatial clusters HH or LL. Also the local constraining of the neutral models to the regional background causes less variation among realizations, leading to the J neighboring values being consistently either small or large across the realizations. Thus the distribution of 999 simulated LISA values is expected to be narrower than for the two previous models with a shift in the mean. This is illustrated for the ZIP code #11364 in Figure 10 (left bottom graph). Because this unit is located in a low-valued area, the use of neutral models reproducing the regional background yields smaller simulated LISA values (average = -0.14 instead of 0.0). In high-valued areas, the shift is expected to be in the opposite way, leading to a larger range of p-values observed across the area, see the scattergram in Figure 9 (right graph). Table 2 and Figure 9 indicate that the p-values are of larger magnitude (average: 0.405 versus 0.23 for Model II) and weakly correlated with the ones obtained under CSR. For female lung cancer, the same numbers of ZIP codes (6) were classified as significant outliers or clusters under neutral model III. The two low-low clusters are Springfield Gardens (11413) and Saint Albans, which was the only significant unit under neutral model II. These ZIP codes are both located in the western part of Long Island with low background SMR values, and in the same area the following three low-high outliers are found: Bellerose (11426), Little Neck (11362), and New Hyde Park (11040) surrounding the high-high cluster Glen Oaks (11004). The last low-high outlier is found in Shelter Island Heights (11965) in the eastern part of Long Island, though its SMR (72% of the New York average) has a wide confidence interval resulting from the small number of observed cases there (1,080 habitants). The two high-low outliers are found in central Long Island characterized by a low SMR background level: Ridge (11961) and Bayport (11705) with SMR values 20 to 40% higher than the New York state average. Three more clusters of high SMR (1.15 to 1.20) are found in the North western part of Long Island, next to the large group of low SMR recorded in Flushing and Jamaica: Bayville (11709), Mill Neck (11765), and Glen Cove (11542). For all three types of model, accounting for population size through geostatistical filtering leads to a larger number of ZIP codes classified as clusters and fewer outliers, see Figure 8 and Table 2. This result can be explained by the smoothing of local fluctuations, in particular the ones recorded in sparsely populated ZIP codes, yielding larger and more compact clusters, such as for Model IV. Figure 10 (right column) also shows that this smoothing halves the standard deviation of the distributions of simulated LISA statistics. Major differences between Models I and IV include bigger and more compacts clusters of low and high SMR values, the disappearance of two sparsely populated high-high clusters (Bayville and Mill Neck, with 7,134 and 732 habitants, respectively), and the classification of a former high-low cluster into a low-low cluster (Oakland Gardens) since the filtered rate becomes slightly lower than the global mean. A similar trend is observed for spatially correlated neutral models where the filtering increases the number of significant low-low clusters from one to four, all located in the eastern part of Long Island. The comparison of Models III and IV indicates the disappearance of a few sparsely populated ZIP codes which were classified as spatial outliers prior to filtering: HL (Bayport, 8,006 habitants), LH (Shelter Island Heights, Bellerose and Little Neck, with 1,080, 18,726 and 17,502 habitants). The only remaining LH cluster is New Hyde Park which has 39,156 habitants. The HH cluster (Glen Oaks, 14,682 habitants) also disappeared. Conversely, three other ZIP codes with populations ranging from 776 to 21,282 became significant LL clusters under Model IV: East Marion (11939), Woodbury (11797), and Cambria Heights (11411). Across all six types of neutral models, only one out of 214 ZIP codes is consistently classified into the same category: the low-low cluster at Saint Albans (11412) which has a SMR = 0.82 and a population of 37,452. The stability of this cluster under alternative specifications of the statistical null hypothesis can be used by cancer surveillance and control efforts to quantify the degree of confidence associated with this cancer cluster. Male Results of the cluster analysis for male lung cancer are displayed in Figures 11 and 12 and reported in Table 3. Model I (CSR assumption) yields the same results as the one reported in [11]. Three local clusters of low SMR values were identified, centred on Great Neck (ZIP 11024), Roslyn (11576), and Huntington (11743), all in the northwest portion of Long Island. These clusters are typified by lung cancer SMR values that are 50–75% of the New York State average. A large cluster of lung cancer SMR 20–60% higher than the New York average was identified in central Long Island. Cutchogue (11935) was found a significant high-low outlier although its small population (3,444) impacts the reliability of the morbidity ratio. The two low-high outliers are Moriches (11955) and Rockaway Park (11694). Figure 11 Results of the local cluster analysis conducted for male lung cancer using neutral models I to III. The fill color in each ZIP code represents the classification into significant low-low or high-high clusters, as well as high-low or low-high outliers. Yellow indicates ZIP codes that have not been found significant using an adjusted significance level α = 0.01101. Figure 12 Results of the local cluster analysis conducted for male lung cancer using neutral models IV to VI. The fill color in each ZIP code represents the classification into significant low-low or high-high clusters, as well as high-low or low-high outliers. Yellow indicates ZIP codes that have not been found significant using an adjusted significance level α = 0.01101. As for female lung cancer, accounting for spatial autocorrelation (i.e. Model II) leads to fewer significant ZIP codes compared to the common CSR assumption. Only two units are now significant: high-high cluster at Shirley (11967) and a low-high outlier at Rockaway Park (11694). Changes are also substantial when looking at results obtained under neutral model III. We found two high-high clusters: Shirley (11967) and Queens Village (11429), one low-low cluster: Corona (11368), and one low-high outlier: Elmont (11003). Accounting for population size in the cluster analysis (Model IV) enhances the size and compactness of the two major clusters of low and high SMR values, while the classification of three sparsely sampled ZIP codes (Cutchogue, Moriches and Rockaway Park with 3,444, 2,652 and 19,278 habitants respectively) changed from spatial outliers to clusters. A new cluster of high SMR values (SMR = 1.29) is also found in Lindenhurst (11757). Using spatially correlated neutral models the geostatistical filtering (Model V) reveals a new cluster of low SMR values in Port Washington (11050) and Great Neck (11024) with lung cancer SMR values that are 70% of the New York State average. Comparison of Models III and VI indicates that besides increasing the size of clusters identified under Model II geostatistical filtering leads to the identification of a new low-low cluster: Cold Spring Harbor (11724, with a SMR 63% below the New York state average) and one low-high outlier: Springfield Gardens (11413, SMR = 0.80). Across all six types of neutral models, only one out of 214 ZIP codes is consistently classified into the same category: the high-high cluster at Shirley (11967) which has a SMR = 1.157 and a population of 24,942. How many realizations are needed? The use of randomization in test of hypothesis relies on the assumption that the space of solution is sampled fairly exhaustively and uniformly (equally-probable realizations [23]). It is thus necessary to investigate how conclusions change as a function of the number of neutral models generated. For example, Figure 13 shows the influence of increasing the sample size from 99 to 999 on the average difference in terms of p-value and classification of ZIP codes into significant outliers and clusters (the reference is the results obtained using 99 realizations). All curves exhibit a plateau within this range of sampling intensity, although the asymptotic behavior depends on the type of neutral models. This result indicates that for this case study enough realizations of neutral models were generated to yield stable classifications of ZIP codes. Figure 13 Impact of the number of realizations and type of neutral models on the stability of local cluster analysis results. The left graph displays the absolute value of the average change in p-value as the number of realizations increases from 99 to 999. The right graph shows the number of ZIP codes that are classified differently as the number of realizations increases from 99 to 999. Conclusions Cancer mortality maps are used by public health officials to identify areas of excess and to guide surveillance and control activities. Maps of incidence as well as mortality are used as input to disease clustering procedures whose purpose is to identify local areas of excess and deficit. While some controversy revolves around the utility of these techniques, it is indisputable that the finding of a confirmed cancer cluster is often of considerable concern. The accurate quantification of local excesses and deficits, as well as regional trends and differences in cancer incidence and mortality, is therefore a problem of considerable practical importance. Arguably one of the biggest problems facing spatial epidemiology and exposure assessment is that of identifying geographic pattern (e.g. hotspots, coldspots, clusters, etc) above and beyond background variation. Most, if not all, environmental contaminants and diseases with potential environmental causes occur at a background level in the absence of a pollution- or disease-generating process. Nonetheless, this background pattern is typically ignored in spatial analyses that employ null hypotheses of complete spatial randomness. Because some spatial dependency is expected at background levels, CSR often is an inappropriate null hypothesis. When should the different types of neutral models be employed? The 6 types of neutral models presented here represent permutations of whether or not population size is accounted for, and 3 types of underlying risk models. As a rule of thumb one should employ that neutral model or those neutral models that most closely correspond to the spatial pattern expected in the absence of the alternative spatial process. So, for a cluster study one would select those neutral models that specify the risk function deemed most likely in the absence of spatial clustering. When working with rates spatial heterogeneity in the size of the at-risk population should always be accounted for, and selections from neutral models of types IV through VI are appropriate. When in doubt about which neutral model to employ, it makes sense to use several in order to determine how sensitive the results are to specification (and misspecification) of the null hypothesis. To the authors' collective knowledge, CSR is rarely if ever encountered in real-world biological systems. It is an apt descriptor of the "snow" that used to appear on late-night television when the programming day was over. It thus seems that neutral model types I and IV will seldom be appropriate. They perhaps will prove most useful for evaluating the extent of bias in past studies that employed CSR. The approach presented in this paper enables researchers to assess geographic relationships using appropriate null hypotheses that account for the spatial correlation and background variation modeled from the observed rates and any ancillary information (i.e. exposure model). An immediate consequence of using more realistic (i.e. spatially correlated) neutral models are larger p-values, leading to a substantial reduction in the number of ZIP codes declared significant outliers or clusters across Long Island. This result confirms earlier findings that CSR often leads to an over-identification of the number of significant spatial clusters or outliers. These false positives have potentially serious consequences in that it can lead to public alarm and demands for investigation by already stretched state health departments. The drop in the number of significant units is however accentuated by the use of an adjusted significance level (Bonferroni adjustment) to account for the correlation between the tests conducted at neighboring ZIP codes. Further research should investigate the redundancy between the use of spatially correlated neutral models and adjusted significance level, which might lead to an "under-identification" of the number of significant spatial clusters or outliers. When the constraint of local conditioning of neutral models is superimposed to the reproduction of spatial autocorrelation (i.e. model III), the approach allows one to detect local departures from the conditioning background specified by the user. In this paper, this background was identified to the regional variability of SMR data which was estimated geostatistically. Future research will investigate the use of exposure models for local conditioning of neutral models, leading to the detection of clustered or isolated geographical units that depart significantly from the cancer rates expected from exposure data. A similar approach has recently been implemented whereby the regional background observed in the past has been incorporated into the geostatistical simulation of neutral models [24]. This new methodology allowed one to identify geographic pattern above and beyond background variation displayed in prior time intervals for cervix cancer mortality rates. Another issue, which often impacts the results of cluster analysis, is the lack of reliability of rates inferred from small populations. If ignored, large differences in population size decrease the ability of Moran's I to detect true clustering/departures from spatial randomness. A geostatistical smoother, which accounts for the spatial pattern of SMR data (i.e. anisotropic variability, range of autocorrelation), has been applied to eliminate the random variability that appeared as a nugget effect on the experimental semivariograms. The smoothing of local fluctuations, in particular the ones recorded in sparsely populated ZIP codes, resulted in the detection of larger and more compact clusters of low or high SMR values as well as the disappearance of some unreliable spatial outliers. Geostatistical filters are very flexible and could be used to filter short-range variability in addition to the noise created by small population sizes. In this case, the focus of the analysis would be on the regional background of the data, allowing the detection of regional clusters. The neutral models and methods in this paper make possible, for the first time ever, evaluation of the sensitivity of the results of cluster or boundary analyses to specification of the null hypothesis. Within a study, this will provide detailed quantification of the reliability of the results, and will identify those areas that are stable (i.e. always classified as a member of a cluster or not) or whose classification is highly sensitive to specification of the null hypothesis. This end result will be a spatially explicit analysis of potential false positives and false negatives. Authors' contributions Authors PG and GMJ collaborated intensely on all aspects of the manuscript, from research design to data preparation. PG carried out most of the geostatistical and local cluster analysis and drafted the manuscript. Both authors read and approved the final manuscript. Table 3 Number of significant zip codes for the different types of cluster/outliers and neutral models. Results are reported for male lung cancer. Numbers between parentheses indicate zip codes that have similar classification under the reference Model I (CSR). Summary statistics for the p-values are also provided. Neutral Model Type Model I Model II Model III Model IV Model V Model VI High-High 8 1(1) 2(1) 15(8) 2(1) 4(1) High-Low 1 0(0) 0(0) 0(0) 0(0) 0(0) Low-High 2 1(1) 1(0) 1(1) 0(0) 2(0) Low-Low 14 0(0) 1(1) 24(14) 2(1) 4(2) P-value Mean 0.185 0.259 0.368 0.166 0.251 0.371 CV 83.4% 54.8% 71.8% 92.9% 58.9% 80.5% Acknowledgements This research was funded in part by grants R01 CA92669 and 1R43CA105819-01 from the National Cancer Institute and R43CA92807 under the Innovation in Biomedical Information Science and Technology Initiative at the National Institute of Health. The views stated in this publication are those of the authors and do not necessarily represent the official views of the NCI. ==== Refs Jacquez GM Gatrell A, Loytonen M GIS as an enabling technology GIS and Health 1998 London, Taylor and Francis 17 28 Rushton G Elmes G McMaster R Considerations for improving geographic information system research in public health Journal of the Urban and Regional Information Systems Association 2000 12 31 49 Gustafson EJ Quantifying landscape spatial pattern: What is the state of the art? Ecosystems 1998 1 143 156 10.1007/s100219900011 Waller LA Jacquez GM Disease models implicit in statistical tests of disease clustering Epidemiology 1995 6 584 590 8589088 Sokal RR Oden NL Thomson BA Local spatial autocorrelation in a biological model Geographical Analysis 1998 30 331 354 Fortin MJ Jacquez GM Randomization tests and spatially auto-correlated data Bulletin of the Ecological Society of America 2000 81 201 205 Ord JK Getis A Testing for local spatial autocorrelation in the presence of global autocorrelation Journal of Regional Science 2001 41 411 432 10.1111/0022-4146.00224 Goovaerts P Geostatistics for Natural Resources Evaluation 1997 New York: Oxford University Press Goovaerts P Jacquez GM Greiling D Exploring scale-dependent correlations between cancer mortality rates using factorial kriging and population-weighted semivariograms: a simulation study Geographical Analysis 2004 Jacquez GM Greiling DA Local clustering in breast, lung and colorectal cancer in Long Island, New York Int J Health Geogr 2003 2 3 12633503 10.1186/1476-072X-2-3 Jacquez GM Greiling DA Geographic boundaries in breast, lung and colorectal cancer in relation to exposure to air toxics in Long Island, New York Int J Health Geogr 2003 2 4 12633502 10.1186/1476-072X-2-4 Anselin L Local indicators of spatial association – LISA Geographical Analysis 1995 27 93 115 Deutsch CV Journel AG GSLIB: Geostatistical Software Library and User's Guide 1998 2 New York: Oxford Univ Press Cressie N Statistics for Spatial Data 1993 New York: Wiley Pardo-Iguzquiza E VARFIT: a Fortran-77 program for fitting variogram models by weighted least squares Computers and Geosciences 1999 25 251 261 10.1016/S0098-3004(98)00128-9 MacNab YC Dean CB Spatio-temporal modelling of rates for the construction of disease maps Statistics in Medicine 2002 21 347 358 11813222 10.1002/sim.1021 Mungiole M Pickle LW Hansen Simonson K Application of a weighted head-banging algorithm to mortality data maps Statistics in Medicine 1999 18 3201 3209 10602145 10.1002/(SICI)1097-0258(19991215)18:23<3201::AID-SIM310>3.3.CO;2-L Besag J Newell J The detection of clusters in rare diseases Journal of the Royal Statistical Society Series A 1991 154 143 155 Oden N Adjusting Moran's I for population density Statistics in Medicine 1995 14 17 26 7701154 Waldhor T The spatial autocorrelation coefficient Moran's I under heteroscedasticity Stat Med 1996 15 887 892 8861157 10.1002/(SICI)1097-0258(19960415)15:7/9<887::AID-SIM257>3.3.CO;2-5 Assuncao RM Reis EA A new proposal to adjust Moran's I for population density Stat Med 1999 18 2147 2162 10441770 10.1002/(SICI)1097-0258(19990830)18:16<2147::AID-SIM179>3.0.CO;2-I Kafadar K Choosing among two-dimensional smoothers in practice Computational Statistics and Data Analysis 1994 18 419 439 10.1016/0167-9473(94)90160-0 Goovaerts P Impact of the simulation algorithm, magnitude of ergodic fluctuations and number of realizations on the spaces of uncertainty of flow properties Stochastic Environmental Research and Risk Assessment 1999 13 161 182 10.1007/s004770050037 Goovaerts P Jacquez GM Detection of temporal changes in the spatial distribution of cancer rates using LISA statistics and geostatistically simulated spatial neutral models Journal of Geographical Systems 2004 accepted

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Int J Health Geogr. 2004 Jul 23; 3:14

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10.1186/1476-072X-3-14

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==== Front Int J Health GeogrInternational Journal of Health Geographics1476-072XBioMed Central London 1476-072X-3-151527294210.1186/1476-072X-3-15ResearchUsing a Geographical Information System to investigate the relationship between reported cryptosporidiosis and water supply Hughes Sara 1sarakhughes@hotmail.comSyed Qutub 1qutub.syed@hpa.org.ukWoodhouse Sarah 1swoodhouse@doctors.org.ukLake Iain 2i.lake@uea.ac.ukOsborn Keith 3Keith.Osborn@uuplc.co.ukChalmers Rachel M 4Rachel.Chalmers@nphs.wales.nhs.ukHunter Paul R 5Paul.Hunter@uea.ac.uk1 Health Protection Agency Northwest, Chester, UK2 School of Environmental Sciences, University of East Anglia, Norwich, UK3 United Utilities, Warrington, UK4 HPA Cryptosporidium Reference Unit, Swansea, UK5 School of Medicine, Health Policy and Practice, University of East Anglia, Norwich, UK2004 23 7 2004 3 15 15 30 6 2004 23 7 2004 Copyright © 2004 Hughes et al; licensee BioMed Central Ltd.2004Hughes et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background This paper reports on a study investigating the epidemiology of sporadic cryptosporidiosis in the North West of England and Wales using a Geographical Information System (GIS) to map location of residence of cases. Some 747 reports of cases were made to CDSC North West of which 649 reports were suitable for analysis. Cases were plotted on the maps of water supply zone and water quality area boundaries, provided by the two main water utilities. Results It was notable that there were major spatial variations in attack rate across the North West and Wales. The most dramatic example was the large difference between the Greater Manchester conurbation with many reports and Liverpool with none. Given the distribution of previously detected waterborne outbreaks in the region it was initially thought that drinking water source may be an explanation. However, an analysis of the distribution of cases in the Greater Manchester area showed no correlation with any of five water supplies that serve the conurbation. Conclusions Our study has shown a dramatic variation in the incidence of laboratory confirmed cryptosporidiosis within two regions of the United Kingdom. Further analysis has not been able to prove drinking water as a likely explanation of this variation which so far remains unexplained. ==== Body Background Cryptosporidiosis is infection with species of the genus Cryptosporidium. Most infections in the UK are due either to C. parvum (previously known as C. parvum genotype 2 or bovine strain) or C. hominis (previously known as C. parvum genotype 1 or human strain) [1]. Cryptosporidium spp. are protozoan parasites. In otherwise healthy individuals they tend to cause a self-limiting form of gastroenteritis which can last for several days and, sometimes, weeks. In patients with certain forms of immune deficiency, most notable the Acquired Immune Deficiency Syndrome (AIDS), the infection can cause a severe and prolonged diarrhoeal illness which, prior to the widespread use of at highly effective antiretroviral therapy was often fatal [2] Cryptosporidiosis has now become the most commonly identified protozoal cause of gastroenteritis in the United Kingdom. Most of the epidemiological data to-date has been related to reports of outbreaks. Between the years 1983 to 1997 there were 80 outbreaks cryptosporidiosis in England and Wales affecting 4649 individuals [3]. Of these 80 outbreaks, 25 affecting 3455 cases were associated with drinking water. Indeed large outbreaks of cryptosporidiois have often been associated with drinking water [4,5]. Outbreaks of cryptosporidiosis were a particular problem in the North West Region of England during the 1990s where a single unfiltered surface water source was responsible for several outbreaks [2]. However, outbreak-related cases represent only a small proportion (<10%) of the total cases reported to national surveillance. The epidemiology of sporadic (non-outbreak-related) cases is largely unknown. Of three large case-control studies reported in the past few years only one found an association with drinking mains water [7-9]. The study that did find an association with drinking water was undertaken in a largely rural area that when the study was undertaken received some of its water from systems that did not have modern filtration plants. The other two studies identified contact with another case, contact with cattle and overseas travel as being the main risk factors for sporadic infection. The question remains what proportion of sporadic cryptosporidiosis infections may be due to the consumption of mains drinking water. This paper reports a study using GIS to investigate the epidemiology of sporadic cryptosporidiosis and particularly address the issues of whether sporadic cases are also associated with consumption of drinking water. Results Table 1 shows the number of records from each health authority and the number of exclusions, including reasons for exclusion. Figures 1 and 2 show the geographical distribution of individual cases by indicating a dot on the map of the water supply zones (water quality area for Wales). Figure 3 indicates the attack rates for each zone in the North West where the shading indicates a range of attack rates. Care should be taken in interpreting the zone rates as the populations covered by each zone/area varied substantially. In some zones high attack rates were seen despite only a single case being identified because of a low denominator population. The area specific attack rates are not shown for Wales as numbers of cases was smaller. Table 1 Health authority of reported cases, including reasons for exclusion from analysis Reasons for excluding post codes Health Authority Total records Included in analysis Excluded Incorrect Duplicate Incomplete Missing % excluded Bro Taf 2 2 2 100 Bury and Rochdale 51 43 8 4 2 1 1 15.7 Dyfed Powys 49 44 5 5 10.2 East Lancashire 47 45 2 2 4.3 Gwent 12 12 0 0 Iechyd Morgannwg 6 6 6 100 Morecambe Bay 13 10 3 3 23.1 Manchester 69 48 21 3 10 8 30.4 N Cheshire 6 6 0 0 North Wales 121 111 10 9 1 8.3 North West Lancashire 74 59 15 3 2 10 20.3 South Cheshire 63 63 0 0 South Lancashire 20 20 0 0 Salford 34 28 6 4 2 17.6 St Helens & Knowsley 8 8 0 0 Stockport 66 60 6 1 1 4 9.1 West Pennine 32 29 3 1 1 1 9.4 Wigan and Bolton 46 35 11 2 4 4 1 23.9 Wirral 28 28 0 0 TOTAL 747 649 98 37 10 24 27 13.1 Figure 1 Cryptosporidiosis cases in the North West, January 2001 to February 2002 Figure 2 Cryptosporidiosis cases in the Welsh Water Area, February 2001 to February 2002 Figure 3 Cryptosporidium attack rates in the North West. Attack rates calculated for each Water Supply Zone in the North West, January 2001 to February 2002 (per 1000 population). It can be seen that there is substantial spatial variation in the distribution of reported cases. In part, this variation can be explained by variation in population density. However, much of the variation is unexplained. For example, reports from Liverpool are very uncommon, whilst reports from Greater Manchester are very common. It was decided to investigate the excess case reporting from Greater Manchester in further detail to look for any possible association with water supplies. Water to the Greater Manchester area comes from five main water treatment works; Lostock (derived from Thirlmere in the Lake District and chlorinated but not filtered), Woodgate Hill (derived from Haweswater and Windermere via the Watchgate Treatment Works near Kendal where the water is treated by rapid gravity sand filtration, though not chemically coagulated before spring 2003), Arnfield-Godley (chemical coagulation, clarification and rapid gravity sand filtration), Buckton Castle (chemical coagulation, dissolved air flotation and rapid gravity sand filtration) and Wybersley (chemical coagulation, dissolved air flotation and rapid gravity sand filtration). In order to determine whether there was any relationship between attack rate and water supply, all water supply zones in the North West that received any water from one or more of these five supplies were identified (Figure 4). For each of these water supply zones, the proportion of the supply from each treatment works were was obtained from United Utilities. The correlation between the attack rate and proportion of water from each treatment works was tested using Kendall's rank correlation (Table 2) [10]. The figure adjusted for ties was used. There was no significant correlation between water source and attack rate. Figure 4 Dominant water treatment works in Greater Manchester during 2001. Each water supply zone in the Greater Manchester area is identified and colour coded to illustrate which of the five water treatment works supply most of the drinking water. Where there is no single dominant source the zone is left uncoloured Table 2 Water supply and cases of Cryptosporidiosis Correlation between water supply zone specific attack rate and proportion of water received from each of the five main water treatment works supplying Greater Manchester. Water treatment works Z P value Lostock -1.084 0.2782 Woodgate Hill 1.713 0.0867 Arnfield – Godley -1.186 0.2353 Buckton Castle -0.628 0.5294 Wybersley 0.451 0.6517 Discussion As already mentioned, care should be taken in the interpretation of this analysis. It is notable that the proportion of reports that could not be allocated a correct postcode varied from one health authority to another to some extent. Also variation in attack rate between water supply zones or water quality areas was as likely to be due to differences in population size as to differences in reported cases. This was most obvious in zones/areas with relatively small population sizes where random effects could have a particularly important affect. However, there are a number of obvious features. The most obvious is the large number of cases from the Greater Manchester conurbation. This covered the Bury and Rochdale, Manchester, Salford, Stockport, West Pennine, and Wigan and Bolton Health Authorities. This excess of cases in Manchester is even more remarkable when compared with the virtual absence of cases from the Liverpool conurbation (Liverpool, Sefton and St Helen's & Knowsley Health Authorities). The reason for the excess of cases in Greater Manchester is unclear. Although different reporting habits could play a part, we doubt that it could explain more than a small part of the difference. Reporting practices are not that greatly different across the North West [10]. A sero-epidemiological study, currently underway, may be able to determine whether the low reporting rate from Liverpool is real or not. An alternate explanation could be that the increase represents different water supplies. Salford, and Wigan and Bolton Health Authorities get much of their water supply from Thirlmere, a supply known to be prone to contamination by Cryptosporidium [6], none of the others have been implicated in outbreaks of disease. However, it would appear that the attack rates did not vary in any consistent way in relation to water source and so a waterborne hypothesis for this excess could not be proven. Analysis was restricted to Greater Manchester as analysis of all reports in the North West could be subject to confounding as a result of geographical variation in reporting behaviour, whereas the Health Authorities in Greater Manchester share a very similar notification system. The lack of an association with drinking water source was consistent with the conclusions of the case control study undertaken at the same time which also did not find an association with drinking water [9]. Nevertheless, it will be interesting to see whether the completion of an adequate water filtration plant for the Thirlmere supply which is scheduled for spring 2004 has much, if any, impact on the number of reports from Manchester. A further explanation could be that the Manchester population experience other risk factors more commonly than the Liverpool population. Possible explanations include contact with contact with animals, visiting swimming pools and overseas travel. We do not have access to data to show whether or not people from Manchester are more exposed to these factors than people from Liverpool. However, Manchester is closer to a major National Park, The Peak District. If people from Manchester use their proximity to the Peak District to spend more time in the countryside and so are more likely to come into contact with farm animals, this could explain the difference. This would be an interesting hypothesis to test in a further study. In addition to Greater Manchester, there are also areas of increased reporting from North Wales and from North West Lancashire. These hotspots also remain unexplained. North West Lancashire, however, receives much of its water from Thirlmere and a water source cannot be excluded. However, many cases were reported from the Fylde peninsula which only receives a small proportion of its water from Thirlmere. Conclusions The use of GIS to study the spatial distribution of cases has been useful in identifying geographical variation, but not necessarily for identifying the reasons for this variation. However, initial analysis does not support the hypothesis that differences in drinking water source is the major reason for this variation. We agree with Dangendorf et al. [12] that GIS will contribute substantially to our understanding of the contribution of drinking water to human disease as it aids the identification of possible associations between disease and particular water supplies, provided sufficient information is collected to enable accurate location of cases. Methods Consultants in Communicable Disease Control in the North West Region of England and in Wales were asked to forward details of cryptosporidium cases upon notification from the laboratory. A data collection form was completed for each case, giving the following details: name, address, postcode, date of birth, GP name, GP address and date of notification. The form was faxed or e-mailed to Communicable Disease Surveillance Centre (CDSC) – North West as soon as possible. Enhanced surveillance for the North West of England and Wales were set up separately, North West England in mid December 2000 and Wales in February 2001. Both ran until February 2002. To check for accuracy, the data were audited every 2 months. Each CCDC was sent a list of the cases they had notified to CDSC North West in the preceding 2 months. Any cases that had not been notified were forwarded to CDSC. The first stage in the geographical analysis was to check the 747 records for possible duplicate records. These were selected on the criteria of 2 individuals with identical names, dates of birth and postcodes being present in the database. Given that a postcode contains on average only 15 addresses the chances of these being legitimate is highly unlikely. Through this procedure 10 records were deleted from the database. Consequently 737 cases of cryptosporidiosis were identified during the period of enhanced surveillance. The next step was to assign a grid reference to each postcode and this was achieved using the Royal Mail Postcode Address File. Eighty eight records were excluded as either, an incomplete postcode was entered into the cryptosporidiosis database or a match could not be found in the postcode address file. Therefore, in total the database was reduced to 649 cryptosporidiosis cases. These were plotted as points against a backdrop of the water supply zones for the two main water utilities. The water supply zone and water quality area boundaries were provided by the two main water utilities (United Utilities and Welsh Water). A "water supply zone" is an area designated by a water undertaker providing water to the residences of not more than 50,000 people. In general the source is consistent across a particular zone. Using the GIS each case was also assigned its corresponding water supply zone and the number of cases in each WSZ was divided by the population, based upon data supplied by the two water utilities, to produce the attack rate maps. The analysis was undertaken in ArcGIS 8.1 using point in polygon techniques [13]. Authors' contributions PRH was lead on study design, did the statistical analyses and co-wrote the paper. SH co-designed the study and co-wrote the paper and undertook most of the data collection. QS co-designed the study and co-wrote the paper. SW co-designed the study and co-wrote the paper. IL undertook the geographical analyses and co-wrote the paper. KO co-designed the study, co-wrote the paper and obtained data on the water distribution. RC co-designed the study and co-wrote the paper. ==== Refs Morgan-Ryan UM Fall A Ward L Hijjawi N Sulaiman I Fayer F Thompson RCA Olson M Lala L Xiao L Cryptosporidium hominis n. sp. (Apicomplexa: Cryptosporidiidae) from Homo sapiens J Eukaryot Microbiol 2002 49 433 440 12503676 Hunter PR Nichols G The epidemiology and clinical features of cryptosporidium infection in immune-compromised patients Clin Microbiol Rev 2002 15 145 154 11781272 10.1128/CMR.15.1.145-154.2002 Nichols G Hunter PR, Waite M, Ronchi E Using existing surveillance systems In Drinking Water and Infectious Disease: Establishing the Links 2002 Boca Raton: CRC Press 131 141 Hunter PR Waterborne disease: epidemiology and ecology 1997 Chichester: Wiley Department of the Environment, Transport and the Regions, and Department of Health Cryptosporidium in water supplies: Third Report of the Group of Experts 1998 London: Her Majesty's Stationery Office Hunter P Syed Q Naumova EN Possible undetected outbreaks of cryptosporidiosis in areas of the North West of England supplied by an unfiltered surface water source Commun Dis Public Health 2001 4 136 138 11525003 Robertson B Sinclair MI Forbes AB Veitch M Kirk M Cunliffe D Willis J Fairley CK Case-control studies of sporadic cryptosporidiosis in Melbourne and Adelaide, Australia Epidemiol Infect 2002 128 419 431 12113486 10.1017/S0950268802006933 Goh S Reacher M Casemore DP Verlander NQ Chalmers R Knowles M Williams J Osborn K Richards S Sporadic Cryptosporidiosis, North Cumbria, England, 1996–2000 Emerg Infect Dis 2004 10 1007 1015 15207050 Hunter PR Hughes S Woodhouse S Syed Q Verlander NQ Chalmers RM Morgan K Nichols G Beeching N Osborn K Case-Control Study Sporadic Cryptosporidiosis with genotyping Emerg Infect Dis 2004 10 1241 1249 15324544 Buchan IE StatsDirect statistical software, version 1605 2000 Chalmers RM Hughes S Thomas A Woodhouse S Thomas PD Hunter P Laboratory ascertainment of Cryptosporidium and local authority public health policies for the investigation of sporadic cases of cryptosporidiosis in two regions of the United Kingdom Comm Dis Public Health 2002 5 114 118 Dangendorf F Herbst S Exner M Kistemann T Hunter PR, Waite M, Ronchi E Geographical Information Systems In Drinking Water and Infectious Disease: Establishing the Links 2002 Boca Raton: CRC Press 143 153 Burrough PA McDonnell RA Principles of Geographical Information Systems 1998 Oxford: Oxford University Press

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Int J Health Geogr. 2004 Jul 23; 3:15

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Int J Health Geogr

10.1186/1476-072X-3-15

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==== Front Int J Health GeogrInternational Journal of Health Geographics1476-072XBioMed Central London 1476-072X-3-161528202710.1186/1476-072X-3-16EditorialWeb GIS in practice: an interactive geographical interface to English Primary Care Trust performance ratings for 2003 and 2004 Kamel Boulos Maged N 1M.N.K.Boulos@bath.ac.uk1 School for Health, University of Bath, Claverton Down, Bath BA2 7AY, UK2004 28 7 2004 3 16 16 25 7 2004 28 7 2004 Copyright © 2004 Kamel Boulos; licensee BioMed Central Ltd.2004Kamel Boulos; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background On 21 July 2004, the Healthcare Commission released its annual star ratings of the performance of NHS Primary Care Trusts (PCTs) in England for the year ending March 2004. The Healthcare Commission started work on 1 April 2004, taking over all the functions of the former Commission for Health Improvement , which had released the corresponding PCT ratings for 2002/2003 in July 2003. Results We produced two Web-based interactive maps of PCT star ratings, one for 2003 and the other for 2004 , with handy functions like map search (by PCT name or part of it). The maps feature a colour-blind friendly quadri-colour scheme to represent PCT star ratings. Clicking a PCT on any of the maps will display the detailed performance report of that PCT for the corresponding year. Conclusion Using our Web-based interactive maps, users can visually appreciate at a glance the distribution of PCT performance across England. They can visually compare the performance of different PCTs in the same year and also between 2003 and 2004 (by switching between the synchronised 'PCT Ratings 2003' and 'PCT Ratings 2004' themes). The performance of many PCTs has improved in 2004, whereas some PCTs achieved lower ratings in 2004 compared to 2003. Web-based interactive geographical interfaces offer an intuitive way of indexing, accessing, mining, and understanding large healthcare information sets describing geographically differentiated phenomena. By acting as an enhanced alternative or supplement to purely textual online interfaces, interactive Web maps can further empower organisations and decision makers. ==== Body Background On Wednesday 21 July 2004, the Healthcare Commission released its annual star ratings of the performance of NHS Primary Care Trusts (PCTs) in England for the year ending March 2004. The Healthcare Commission started work on 1 April 2004, taking over all the functions of the former Commission for Health Improvement , which had released the corresponding PCT ratings for 2002/2003 in July 2003 [1]. A star rating scheme is adopted. PCTs with the highest levels of performance in the measured areas are awarded a rating of three stars. PCTs with mostly high levels of performance, but which are not consistent across all measured areas, are awarded a rating of two stars. PCTs where there is some cause for concern about particular areas of measured performance are awarded a rating of one star. PCTs that have shown the poorest levels of measured performance or little progress in implementing clinical governance receive a rating of zero stars [2]. The performance ratings Web pages of the Healthcare Commission and the former Commission for Health Improvement offer a very limited "geographic search" restricted to browsing results by Strategic Health Authority (SHA) and . This "geographic search" does not allow any visual appreciation of PCT performance levels, or any visual comparisons to be made between PCTs or between 2003 and 2004 result sets. Results We produced two Web-based interactive map sets of PCT star ratings, one for 2003 and the other for 2004 . The maps use a yellow-green-blue quadri-colour scheme to represent PCT star ratings. Users can switch between the two map sets or themes, 'PCT Ratings 2003' and 'PCT Ratings 2004', within the same pane (the two themes are synchronised, so that when users switch themes the corresponding tile from the other theme is always displayed – Figure 1). Map zooming (100% to 800%), panning, MapTips (displaying PCT names), and legends are available. Dynamic overview maps are offered as navigational help (at zoom levels 200%-800%). Map search is also possible (by PCT name or part of it – Figure 2). Clicking a PCT on any of the maps will display the detailed performance report of that PCT for the corresponding year. Printer-friendly versions of the maps can be generated for direct printing from the Web browser. Figure 1 Screenshots from our Web-based interactive maps of PCT star ratings for 2003 and 2004. Screenshots from our Web-based interactive maps of PCT star ratings for 2003 and 2004 . When users switch between 'PCT Ratings 2003' and 'PCT Ratings 2004', the corresponding tile from the other theme is always displayed within the same pane, allowing instant 2003–2004 visual comparisons to be made. In this Figure, Northumberland Care Trust can be seen achieving lower ratings in 2004 (1 star–light green) compared to 2003 (3 stars–dark blue). The detailed 2004 performance report of Northumberland Care Trust (from the Web site of the Healthcare Commission) has been displayed by clicking the Trust shape on the 'PCT Ratings 2004' map. Note the overview maps displaying the position of the current map tile on a miniature complete map of England. Figure 2 Screenshot of the map search box. Screenshot of the map search box, which allows users to locate a Trust on the maps by typing the Trust name or part of it. Selecting a PCT from the 'Result' list and clicking 'show' will zoom into and display the corresponding map tile for that PCT. The maps were successfully tested in both Microsoft Internet Explorer and Mozilla Firefox Web browsers. Discussion Many people are more visually oriented and find that spending long hours browsing the flat textual indices of the Internet leaves a lot to be desired, especially when it comes to navigating large online datasets and understanding the relationships, patterns and trends buried in them. Information resources and large textual datasets (like the detailed PCT performance reports in our case–more than 600 PCT reports for 2003 and 2004 combined) can be organised and navigated based on their geographical attributes [3]. These geographical aspects of textual information are sometimes very useful as an index to information, providing an intuitive way of accessing, mining, and understanding it. Some information types like PCT performance ratings lend themselves very well and naturally to geographical indexing and visualisation. In fact, PCT performance ratings describe a geographically differentiated phenomenon, which is the variation in the performance and quality of primary healthcare services between different areas across England. Using our Web-based interactive maps, users can quickly and intuitively locate any PCT and retrieve detailed performance information about it. They can also visually appreciate at a glance the distribution of PCT performance across England; for example, one can instantly note that there were no three star (dark blue) PCTs in the London region in 2002/2003 and that this has remained unchanged in 2003/2004. Users can visually compare the performance of different PCTs in the same year and also between 2003 and 2004 (by switching between 'PCT Ratings 2003' and 'PCT Ratings 2004' themes). The performance of many PCTs has improved in 2004, whereas some PCTs, e.g., Northumberland Care Trust – Figure 1, achieved lower ratings in 2004 compared to 2003. Conclusions Web-based interactive geographical interfaces offer an intuitive way of indexing, accessing, mining, and understanding large healthcare information sets describing geographically differentiated phenomena, and can act as an enhanced alternative or supplement to purely textual online interfaces. Geographical interfaces enable instant visual comparisons to be made between different geographical areas and over time (when information sets and maps for successive periods of time are available), thus empowering organisations and decision makers. Methods Star ratings of English PCTs for the years 2002/2003 and 2003/2004 were obtained from the Web sites of the former Commission for Health Improvement and the Healthcare Commission respectively. The Internet addresses (URLs) of the corresponding detailed reports of PCT performance were also harvested from the same sources. The maps were created in ESRI ArcView GIS Version 3.1 . We used the 2001 Census PCT (post April 2002 change) boundary dataset, which is the copyright of the Crown/Ordnance Survey , and is freely available to the UK academic community from EDINA UKBORDERS service with the support of the ESRC and JISC . The names/boundaries and labels (codes) of few PCTs changed between 2003 and 2004, but this was properly cared for in our exercise. We inserted four new fields in the original PCT boundary dataset table to store the 2003 and 2004 star ratings and corresponding detailed report URLs for all English PCTs. The PCTs in the output maps are coloured according to the values in their star rating fields (0, 1, 2, or 3 corresponding to the number of stars awarded), with light colours for low ratings to dark colours for high ratings. We used ColorBrewer and [4]) to select a suitable colour scheme for our maps. Our chosen scheme is colour blind friendly, black and white photocopy friendly (for printed output), LCD projector friendly, laptop (LCD) friendly, CRT screen friendly, and colour printing friendly–all at the same time (Figure 3). Figure 3 Screenshot of ColorBrewer online tool. Screenshot of ColorBrewer online tool showing the colour scheme we have chosen for our maps. This yellow-green-blue quadri-colour scheme is colour blind friendly, black and white photocopy friendly (for printed output), LCD projector friendly, laptop (LCD) friendly, CRT screen friendly, and colour printing friendly–all at the same time. The corresponding Hue-Saturation-Value numerical triplets for the four colours in our scheme are also shown, ready for using in ArcView 3.x. The online interactive maps were then produced using the Demo version of alta4 HTML ImageMapper 3.5 extension for ESRI ArcView GIS 3.x and Figure 4), and its companion tool alta4 ThemeBrowser 1.0. ThemeBrowser is used to combine separate HTML ImageMapper projects (in our case 'PCT Ratings 2003' and 'PCT Ratings 2004' map sets) into a single ThemeBrowser Web page (see ). Figure 4 Screenshot of the Demo version of HTML ImageMapper 3.5 extension within ArcView GIS 3.1. Screenshot of the evaluation version of alta4 HTML ImageMapper 3.5 extension within ESRI ArcView GIS 3.1, showing the main settings we have used to generate our Web-based 'PCT Ratings 2004' interactive map set. The dialogue box on the right shows the 'MapTip Field' and 'Click Action/URL Field' settings associated with features (PCTs) on the output map. It is noteworthy that HTML ImageMapper does not require any server side software installation, and as such is much simpler to use than some other Internet GIS solutions like the client/server version of ALOV Map/TimeMap . The standalone versions of ALOV Map/TimeMap and JShape Java applets, which don't require any server side setup, are limited by the fact that they need to download the whole map shapefile from the Web server before they can start on the client side, and so are not suitable for large datasets (our PCT boundary dataset in ESRI shapefile format is about 50 MB in size). Other options for generating interactive Web maps from a desktop GIS are discussed in [5]. ==== Refs Rating the performance of the NHS in 2003/2004 (Healthcare Commission press release–July 2004) Commission for Healthcare Audit and Inspection NHS performance ratings 2003/2004 London 2004 Dodge M Indexing the Web with Geography MappaMundi Magazine – Map of the Month 2000 Nov 1 Harrower M Brewer CA Colorbrewer.org: an online tool for selecting colour schemes for maps Cartographic Journal 2003 40 27 37 10.1179/000870403235002042 Boulos MNK Roudsari AV Carson ER A simple method for serving Web hypermaps with dynamic database drill-down Int J Health Geogr 2002 1

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Int J Health Geogr. 2004 Jul 28; 3:16

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10.1186/1476-072X-3-16

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==== Front World J Surg OncolWorld Journal of Surgical Oncology1477-7819BioMed Central London 1477-7819-2-241526876010.1186/1477-7819-2-24ReviewCancer of the endometrium: current aspects of diagnostics and treatment Münstedt Karsten 1karsten.muenstedt@gyn.med.uni-giessen.deGrant Phillip 2Phillip.Grant@psychol.uni-giessen.deWoenckhaus Joachim 3joachim.woenckhaus@patho.med.uni-giessen.deRoth Gabriele 1gabriele.roth@gyn.med.uni-giessen.deTinneberg Hans-Rudolf 1hans-rudolf.tinneberg@gyn.med.uni-giessen.de1 Department of Obstetrics and Gynecology, Justus-Liebig-University Giessen, Klinikstrasse 32, D 35385 Giessen, Germany2 Department of Psychology, Justus-Liebig-University Giessen, Otto-Behagel-Str. 10F, D 35394 Giessen, Germany3 Institute of Pathology, Justus-Liebig-University Giessen, Langhansstrasse 10, D 35385 Giessen, Germany2004 21 7 2004 2 24 24 4 7 2004 21 7 2004 Copyright © 2004 Münstedt et al; licensee BioMed Central Ltd.2004Münstedt et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background Endometrial cancer represents a tumor entity with a great variation in its incidence throughout the world (range 1 to 25). This suggests enormous possibilities of cancer prevention due to the fact that the incidence is very much endocrine-related, chiefly with obesity, and thus most frequent in the developed world. As far as treatment is concerned, it is generally accepted that surgery represents the first choice of treatment. However, several recommendations seem reasonable especially with lymphadenectomy, even though they are not based on evidence. All high-risk cases are generally recommended for radiotherapy. Methods A literature search of the Medline was carried out for all articles on endometrial carcinoma related to diagnosis and treatment. The articles were systematically reviewed and were categorized into incidence, etiology, precancerosis, early diagnosis, classification, staging, prevention, and treatment. The article is organized into several similar subheadings. Conclusions In spite of the overall good prognosis during the early stages of the disease, the survival is poor in advanced stages or recurrences. Diagnostic measures are very well able to detect asymptomatic recurrences. These only seem justified if patients' chances are likely to improve, otherwise such measures increases costs as well as decrease the patients' quality of life. To date neither current nor improved concepts of endocrine treatment or chemotherapy have been able to substantially increase patients' chances of survival. Therefore, newer concepts into the use of antibodies e.g. trastuzumab in HER2-overexpressing tumors and the newer endocrine compounds will need to be investigated. Furthermore, it would seem highly desirable if future studies were to identify valid criteria for an individualized management, thereby maximizing the benefits and minimizing the risks. ==== Body Incidence and mortality Nearly 170,000 new cases of endometrial carcinomas were estimated worldwide in 1997 [1]. However, incidences throughout different regions of the world vary considerably. Compared to Africa and Asia having the lowest rates of incidence, Western Europe, USA and Canada are shown to have the highest incidence worldwide (Figure 1). As shown in figure 2, even within Europe the incidence rates are very heterogeneous. In some of these countries, e.g. Germany, endometrial carcinoma is the most common among genital carcinoma [2]. Figure 1 Estimated endometrial cancer incidences throughout different regions of the world [1]. Figure 2 Estimated endometrial cancer incidences throughout different countries in Europe [1]. Endometrial carcinomas occur in advanced age (postmenopausal). The age-related incidence for Germany is shown in Figure 3. The overall increase in the incidence of this disease during the last decades is mainly related to higher life expectancy within the developed world. Figure 3 Age dependent incidence of endometrial cancer in Germany. Robert-Koch-Institute at: Etiology and risk factors The etiology of the endometrial carcinoma is not fully understood. Most cases appear sporadically whereas about 10% are hereditary. Chief among the latter is the autosomal dominantly inherited hereditary non-polyposis colorectal cancer (HNPCC) [3-5]. The risk of developing endometrial cancer is believed to be ten times higher for women carrying the gene compared to the general population [6]. The likelihood of a synchronous or metachronous development of endometrial carcinomas is, however, higher for patients with breast, ovarian, and non-hereditary colorectal cancer [7]. Within the current concept of multi-step progression of normal cells to malignancy, recent molecular work has identified several gene alterations important for tumor development. In summary, mutations and amplifications of oncogenes K-ras and HER2/neu, mutations or deletions of tumor suppressor genes p53, p21, p16, and pTEN/MMAC1 as well as impaired DNA repair functions through mutations of hMLH1, hMSH2, and hMSH6 have been connected with the development of endometrial carcinomas [8]. Environmental, dietary and hormonal factors as well as an aging female population have been attributed to an observed increase of endometrial carcinomas over the past few years. Epidemiologic studies have observed correlations between the incidence of endometrial cancer and the usage of estrogens, especially when applied to alleviate perimenopausal and postmenopausal symptoms. Therefore, it appears that estrogen plays a key role in the development and progression of endometrial carcinomas. There is also convincing evidence that high body mass increases the risk of endometrial carcinomas. Current estimations figure that about 40% of these relate to excess body weight [9]. A plausible biological explanation for obesity influencing the risk of endometrial cancer is found in increased aromatization of androstendione to estrone in adipose tissue [10]. Hyperadrenocorticism, which is more common in obese individuals, also disturbs the estrogen metabolism. The correlation between obesity and hyperadrenocorticism is possibly increased by hyperinsulinism. This also explains the higher frequency of endometrial carcinomas in combination with diabetes mellitus. A high intake of saturated fat may also increase the risk, whereas high consumption of vegetables and fruits may do the opposite [1,11]. Due to the fact that most factors relate to prolonged or intensive exposure to estrogen (hyperestrogenism), this may likely be identified as the underlying concept leading to the development of endometrial cancer. In this process estrogens are believed not to act as carcinogenic agents, but as promoters of carcinogenesis. A state of hyperestrogenism may be caused by exogenous or endogenous factors and may relate to reproductive factors, estrogen exposure or menopausal years [9,12,13]. Several endogenous risk factors are also associated with the increase of endometrial cancer risk e.g. early menarche, late menopause (2.4-fold), nulliparity (2-fold), the polycystic ovarian syndrome, diabetes mellitus (2.8-fold), high blood pressure (1.5-fold), obesity (up to 10-fold), other tumors with estrogen production, atypical endometrial hyperplasia (see Table 1) and the aforementioned inherited forms of colorectal cancer (10-fold). Basically two hypotheses endeavor to explain the protective effect of high parity: The first one assuming the mechanical removal of premalignant and malignant cells with each delivery, the second describing a protective effect of high progesterone values during pregnancy. It is most likely for both hypotheses to be correct to some extent, whereas a large population based study from Finland favors the second hypothesis [14]. An additional factor may be anovulatory ovarian insufficiency, especially in patients with polycystic ovaries (PCO syndrome). As these patients have a persistent progesterone deficiency due to non-formation of a corpus luteum, they lack this important protective mechanism. Endocrine risk factors also include hormone producing ovarian tumors. This goes for estrogen as well as androgen producing tumors since androgens may be converted to estrone in adipose tissue. Table 1 Type of endometrial hyperplasia and rate of progression to cancer [20]. Type of hyperplasia Rate of progression Simple (cystic without atypia) 1 Complex (adenomatous without atypia) 3 Atypical  Simple (cystic with atypia) 8  Complex (adenomatous with atypia) 29 Previous irradiation of the pelvis, estrogen replacement therapy (HRT) (especially unopposed HRT) and tamoxifen therapy represent exogenous risk factors. Prolonged and exclusive intake of synthetic estrogens is associated with an up to 15-fold higher incidence of endometrial carcinomas [15]. Similarly, some selective estrogen receptor modulators (SERMs) and especially tamoxifen may have an estrogenic, proliferative effect on the endometrium. Thus tamoxifen therapy is frequently associated with polyps, hyperplasia and carcinomas of the endometrium [16,17]. Tamoxifen seems to induce a 6.4-fold increase in the risk for endometrial cancer [18]. On the other hand, cyclic application of estrogens combined with progestins does not increase endometrial cancer incidence, e.g. hormonal contraception (combined preparations) and may even reduces the risk of endometrial carcinomas by up to 50% (see prevention). In essence, hyperestrogenism will lead to stronger proliferation, thereby causing hyperplasia which may gradually acquire more and more cellular atypia (atypical hyperplasia) and later transform into an endometrioid adenocarcinoma. Recently a case-control study identified antipsychotic drugs as being a great risk factor for endometrial cancer [19]. These findings may also be explained to some extent by the side effects of the drugs (obesity, insulin resistance, amenorrhea, low gonadal steroids leading to hyperprolactinemia). Precancerosis In some cases endometrial cancer develops from atypical endometrial hyperplasia. The likelihood of this happening correlates with the degree of hyperplasia (Table 1) [20]. According to the World Health Organization (WHO) classification, endometrioid carcinomas are divided into simple and complex forms, each with and without atypia [21]. This classification has also been accepted by the International Society of Gynecological Pathologists. Endometrial hyperplasia is regarded as a preliminary stage of endometrioid carcinomas. Serous and clear cell carcinomas are on the other hand frequently associated with an atrophic endometrium [22]. A precursor of the serous carcinoma and possibly of some clear cell carcinomas is the endometrial intraepithelial carcinoma (EIC) [22,23]. Prevention To prevent an outbreak of the disease in menopausal and postmenopausal women long-term estrogen replacement therapy (treatment of menopausal symptoms, osteoporosis etc.) should be supplemented by intermittent application of gestagens. A recent study suggested the use of intrauterine devices (IUD) also possibly reducing the risk for endometrial cancer due to improved elimination or decrease of hyperplastic endometrial cells [24]. Numerous studies have shown that cigarette smoke reduces the risk of an endometrial carcinoma for women after the menopause, although it may increase the risk for premenopausal women [25]. The greatest reduction of risk was found in obese, multiparous women who did not receive hormone treatment [26]. Women in advanced stages of disease (stages II – IV), however, were found more likely to smoke than women in early stages (0 – I). This may reflect a smoking-related decrease in the incidence of early-stage tumors as well as an increase in tumor invasiveness and metastases [27]. The risk of endometrial carcinomas may be reduced significantly by prolonged progestin therapy every month (for 10 days) alone or in combination with estrogen [28]. Since progestins are known to act as cofactors of cancerization in breast and cervical cancer such concepts are better interpreted cautiously [29]. Therefore hormonal preventive concepts need to undergo a general assessment of benefits and risks. To sum up, apart from excess body fat reduction and omission of unnecessary estrogen therapy, there appears to be no reasonable way of preventing endometrial carcinomas. Early detection To date there is no procedure that seems appropriate as a screening method for early detection of endometrial carcinomas. Current guidelines of the American Cancer Society suggest informing patients of risks and symptoms involved with endometrial cancer and furthermore firmly emphasize the importance of reporting unexpected bleeding or spots to their physician [30]. The fact of most endometrial carcinomas (with the exception of the rare serous and clear cell types) showing these kinds of preliminary symptoms leads to the diagnosis of over 75% of cases while still in stage I [7]. A recent case-report on the usage of the Mirena® intrauterine system maintains that irregular menstrual bleeding should not be treated simply with this system without prior diagnostic [31]. The necessity of finding a screening method is discussed controversially in this context. So far, most epidemiological studies have failed to show significant effects of screening on mortality. In some cases the Pap smear may lead to the diagnosis of endometrial cancer. However, in many cases cells from inside the uterus are not assessed by the sampling procedure. Positive cervical cytology was found to correlate with nodal spread in 91% of cases, whereas the risk of lymph node spread in patients with normal cervical cytology was estimated at around 2% [32]. It would seem too early to suggest that this could help to reach a decision on the necessity of lymphadenectomy. Maybe the ThinPrep Pap tests will be able to allow further conclusions in the future [33]. Transvaginal ultrasound has also been suggested as a potential means of early detection of endometrial carcinomas. A recent meta-analysis involving 9,031 patients and covering 57 separate studies on the diagnostic accuracy and positive predictive power of endometrial thickness measurement by pelvic ultrasound in patients with postmenopausal bleeding concluded that these measurements cannot solely be used to accurately rule out endometrial pathology. Measurement of both endometrial layers of ≤ 5 mm coincides with endometrial pathology in only 2.5% [34]. Other studies have used saline infusion sonography and color Doppler sonography to differentiate between endometrial cancer, endometrial hyperplasia, fibroids, endometriosis, myoma or tamoxifen induced endometrial thickness [35-42]. A recent comparison of saline infusion sonography and office hysteroscopy revealed similar ratings of patients' pelvic pain during the procedures. Sensitivity and specificity coefficients as well as negative and positive predictive values were higher for the office hysteroscopy [43]. It seems that biopsy remains the only accurate way of diagnosing endometrial cancer [44]. Under optimal circumstances the gynecologist will remove a tissue sample from the uterine lining under hysteroscopic control [44-47]. If hysteroscopic control is neglected, the false negative rates for dilatation and curettage (D&C) will range between two and six percent, thereby emphasizing the limitations of D&C alone [45,48-50]. Newer methods, like magnetic resonance imaging (MRI), positron emission tomography (PET), intraoperative ultrasound or three dimensional sonography are not likely to gain importance with respect to the diagnosis or early diagnosis of the disease [51-56]. It is, however, reasonable to believe that they are likely to deliver more information about the invasion depth of the myometrium or lymphatic metastases [52,55,57]. Classification of endometrial carcinoma The term endometrial carcinoma describes a variety of different tumor types originating from the inner ling of the uterus. Many authors differentiate between two basic types, which may be divided into estrogen-dependent and estrogen-independent types or tumors with favorable or unfavorable prognosis [58]. Although there are no cross-sectional studies comparing tumors from various ethnic groups and significant differences in tumor biology the frequency of tumors of a certain category in various geographical areas have been assumed. This may explain why mortality in the USA is higher in black women than in white women (5.8 deaths per 100,000 persons in black women vs. 3.1 deaths per 100,000 persons in white women) [59]. The different categories may be summarized as follows: 1. It comprises of estrogen related tumors occurring in younger, perimenopausal women. These tumors are often said to be highly differentiated, mainly adenocarcinomas with positive steroid hormone receptor status (ER, PR), the known risk factors (estrogen etc.) originating from atypical endometrial hyperplasia. The patients in this group have a longer history, lower grade tumors, less myometrial invasion and low potential for lymphatic spread. They may be associated with concomitant carcinomas of the ovary, breast and colon and respond to progestin therapy. The overall prognosis is generally favorable. 2. This category is comprised of tumors of patients with shorter history, higher grade tumors, deeper myometrial invasion and high risk of lymphatic spread. The tumors will not respond to progestin therapy and there are no associated tumors. Histologically these tumors are identified as serous carcinomas or clear cell adenocarcinomas. The prognosis of patients with this type of tumor is poor. 3. Findings of carcinomas in atrophic endometrium being associated with an intermediate prognosis lead to the suggestion of a third category. In these cases the endometrioid carcinomas are not likely to be estrogen-related [21]. 4. It was furthermore suggested to incorporate endometrial neoplasia originating from an inherited predisposition into a fourth category. These types of tumors tend to develop about 15 years earlier and are associated with a favorable prognosis. Most patients in this category have a hereditary non-polyposis colorectal carcinoma syndrome (HNPCC). Histological types according to the WHO classification The following section will briefly describe the most important characteristics of endometrial carcinomas. Detailed descriptions may be found in specialized pathological textbooks e.g. Anderson et al. [21]. • Endometrioid adenocarcinoma: The endometrioid adenocarcinoma, whose glands resemble those of the normal endometrium, is the most common type (60 – 80%). This type is considered part of the 1st category • Endometrioid adenocarcinoma with squamous cell differentiation (adenoacanthoma, adenosquamous carcinoma): Approximately 25% of endometrioid adenocarcinomas display partial squamous differentiation. The squamous elements are interpreted as terminally differentiated indicating that the tumor is incapable of independent growth. Prognosis depends on the glandular components of the lesion. Highly differentiated tumors (adenoacanthomata) have a favorable prognosis, whereas poorly differentiated tumors (adenosquamous carcinomas) have an unfavorable course. • Serous adenocarcinoma: This tumor type is similar to the serous ovarian carcinoma. It is characterized by aggressive growth and poor prognosis. Lymphogenic and hematogenic metastases are usually already present at the time of diagnosis. Nearly all tumors are poorly differentiated. Serous adenocarcinomas belong to the 2nd category of endometrial cancer. • Clear cell adenocarcinoma: This type comprises 3 to 6% of all endometrial carcinomas. Like the serous adenocarcinoma, clear cell adenocarcinomas tend to progress rapidly. They share the 2nd category. • Mucinous adenocarcinoma: Diagnosis is based on the presence of mucus within the tumor cells. Purely mucinous carcinomas are rare, although a mucinous component within endometrioid carcinomas is more common. The tumors are usually highly differentiated and have a good prognosis. It is important to exclude a primary mucinous adenocarcinoma originating from the endocervix, spreading into the uterine body. Mucinous adenocarcinomas are part of the 1st category. • Squamous cell carcinoma (2nd category): A very rare entity associated with very poor survival. Primary squamous cell carcinomas of the uterine cervix should be ruled out. Adjuvant platinum-based radiochemotherapy may result in improved survival. • Mixed carcinoma: A carcinoma composed of two or more different non-squamocellular components with each component occupying at least 10% of the tumor. Prognosis varies, e.g. in case of a serous component, the prognosis is poor. • Undifferentiated carcinoma: A rare carcinoma without glandular, squamous or sarcomatous differentiation. Prognosis is unfavorable. • Rare types of endometrial carcinomas: small cell carcinomas, microglandular adenocarcinomas, signet-ring cell carcinomas, transitional cell carcinomas, glassy cell carcinomas, mucinous adenocarcinomas of the intestinal type, lymphoepithelioma-like carcinomas, and endometrial adenocarcinomas with trophoblastic differentiation have been reported. Grading The tumor grading is a highly significant prognostic parameter although it is subjective with a considerable inter-observer and intra-observer variability. It is determined by the percentage of non-squamocellular, solid portions as follows: G1: 5% and less, G2: 5–50%, G3: more than 50%. A significant nuclear atypia increases the grade of differentiation by one grade. Preoperative diagnostic procedures After histological confirmation of an endometrial carcinoma clinical palpation and vaginal sonography should be performed. Several additional examinations have been suggested: Rectoscopy, cystoscopy, computed tomography and/or MRI. They may be omitted in clearly diagnosed early cases but are strongly recommended in advanced stages. Recent studies indicate some value of tumor marker diagnostics. At a cut-off level of 40 U/ml elevated CA125 serum levels indicate nodal metastases with a sensitivity of 77.8% and a specificity of 81.1% [60,61]. Surgical therapy In all stages of endometrial carcinomas, surgery is the primary treatment of choice. Preoperative intracavitary radiation treatment, often recommended in earlier times, is not considered advisable any more since the information about the depth of myometrial invasion and thus information on an important prognostic factors is lost [62]. A study indicates that the Maylard-type incision is superior to transverse (Pfannenstiel-type) or longitudinal incision [63]. If possible, an abdominal hysterectomy with removal of the adnexa and a peritoneal lavage should be performed. After removal of the uterus, the depth of tumor invasion into the myometrium has to be determined to estimate the probability of extrauterine spread. If the myometrium is infiltrated to more than 50%, a pelvic and paraaortic lymphadenectomy should be performed. For appropriate staging, more than 20 lymph nodes should be dissected [64]. But also in cases of additional adverse prognostic factors (poor grading, lymphangiosis, see below), pelvic and paraaortic lymphadenectomy are recommended by many [65]. A decision tree on primary therapy is given in figure 4. Unfortunately, studies found no correlation between depth of invasion, histological grade, cervical invasion, peritoneal cytology, menopausal status, preoperative serum CA125 level or primary tumor diameter. Only lymphvascular space involvement (P < 0.0001) was significantly correlated to pelvic lymph node metastases, which lead the authors to the conclusion that all patients should undergo extended surgical staging, except when clinical or operative factors increase patients' morbidity [66]. Lymphadenectomy may be omitted in cases of more favorable prognosis. Figure 4 Decision tree concerning the primary treatment of endometrial carcinoma.Legend: RT = radiotherapy; HT = endocrine treatment; CHT = chemotherapy; D&C = dilatation and curettage There is some controversy on the value of radical hysterectomy in stage II carcinomas. While several earlier studies advocated this procedure [67-70] a recent study reported no prognostic advantage [71]. Maybe only the patients with stage IIb tumors and clinically evident tumor infiltration profit from radical hysterectomy. This requires further investigation. Complications after pelvic lymphadenectomy may be reduced by omentoplasty and omentopexy [72]. In advanced stages of the disease complete removal of all tumor sites is warranted. In case of serous histology and peritoneal spread, some authors also advocate omentectomy. A recent study indicates that optimal cytoreduction results in a significant survival benefit for stage IVB endometrial cancer patients with a reasonable surgical morbidity rate [73]. Vaginal hysterectomy as primary treatment of endometrial cancer has also been investigated especially in medically compromised women [72,73]. Such approaches may be combined successfully with laparoscopically assisted radical vaginal hysterectomy [74-77]. The aforementioned basic goals of surgery (hysterectomy, removal of the adnexa and lymphadenectomy in stages Ic and higher) should be reached especially in medically fit patients, because treatment along the recognized guidelines has been found to be prognostically favorable. Some studies, however, have reported the standards mentioned in many cases as not having been realized [78-80]. As shown in Italy there seems to be certain reluctance towards bringing current topics discussed in literature into practice [81]. The problem mentioned may partly be due to the fact that the current guidelines are insufficiently supported by randomized surgical trials. Interestingly the COSA-NZ-UK Endometrial Cancer Study Group trial showed that lymphadenectomy showed no advantage for endometrial cancer if primary surgery was followed by adjuvant radiotherapy [82]. Therefore studies on all surgical aspects are warranted. This also includes newer surgical approaches which await further evaluation in prospective studies. Staging Endometrial carcinomas are staged surgically. Procedures previously used for determination of stages, such as fractional dilatation and curettage to differentiate between stage I and II, are no longer applicable unless the patient is to be treated by primary radiation therapy. The old (1971) and new (1988) staging system of the International Federation of Gynecology and Obstetrics (FIGO) are shown in table 2. The prognostic importance of adequate surgical staging was recently demonstrated [83]. Table 2 Tumor classification of the international Federation of Obstetrics and Gynecology (FIGO). The surgical staging system is obligatory unless patients are to undergo primary radiotherapy when the older clinical staging system may be used. Stage Stage – Clinical Staging Stage – Surgical Staging I I Carcinoma confined to corpus Ia Tumor limited to endometrium Ia Length of uterine cavity ≤ 8 cm Ib Invasion ≤ 1/2 myometrium Ib Length of uterine cavity > 8 cm Ic Invasion > 1/2 myometrium II II Carcinoma involves corpus and cervix IIa Endocervical glandular involvement only IIb Cervical stromal invasion III III Carcinoma extends outside uterus but not outside the true pelvis IIIa Tumor invades serosa or adnexa or positive peritoneal cytology IIIb Vaginal metastasis IIIc Metastases to pelvic or para-aortic lymph nodes VI IV Carcinoma extents outside true pelvis or involves bladder or rectum IVa Tumor invades bladder, bowel mucosa, or both IVb Distant metastases, including intra-abdominal and/or inguinal lymph nodes Prognostic and predictive factors Tumor stage, patient age, histologic type and grade, hormone receptors and DNA ploidy represent the traditional prognostic factors. Respective of the response to progestin therapy steroid hormone receptors may also be regarded a predictive factors in recurrent and advanced disease [8]. The strong prognostic impact of tumor stage is underlined by the cumulative 5-year survival rates (surgical/pathological staging) which are 85% for stage I, 70% for stage II, 49% for stage III and 18% for stage IV disease. Obviously both major factors which make up the staging system of endometrial carcinomas, depth of invasion into the myometrium and lymph node status, are major prognostic factors [84,85]. A recently published analysis draws the attention to lymphvascular space involvement and suggests that its presence should indicate lymphadenectomy or adjuvant therapy [86]. Lymphvascular space involvement was also closely linked with advanced stage (unpublished observation). Furthermore, several additional prognostic factors have been suggested: Nulliparity, high tumor cell proliferation (KI-67), high tumor vessel density (angiogenesis), oncogene amplification or overexpression (HER2/neu, K-ras) and alterations of tumor suppressor genes (PTEN, p53, p21, p16) are believed to be associated with adverse prognoses. Especially Ki-67 could be of greater importance seeing that this parameter proved to be independent in multifactorial analyses in a prospective study [87]. There is a divergence of opinion concerning the value of a positive peritoneal cytology as an independent prognostic factor [88]. In stage I, depth of myometrial invasion, vascular invasion, mitosis count and progesterone receptor negativity are statistically significant prognostic factors [89,90]. Overexpression of p53 is observed in approximately 20% of all endometrial carcinomas and in up to 90% of serous carcinomas [91]. The plasminogen activator inhibitor type 2 has been discussed as a possible independent prognostic marker [92]. Overexpression of the oncogene Her-2/neu is significantly more common in advanced than in early stages. Finally, ploidy status is possibly an independent prognostic factor [93], with aneuploidy being mainly associated to prognostically unfavorable serous, clear cell and poorly differentiated carcinomas. There are, unfortunately, still too many controversies to draw final conclusions or even to make suggestions on factors to be determined routinely. Radiotherapy Primary radiotherapy In medically compromised women, primary irradiation may be suitable. Analyses from Germany show that approximately 20% of all patients undergo primary radiotherapy [7,64]. There are three possible approaches: The after loading technique alone, a combination of after loading and percutaneous techniques or by percutaneous radiotherapy alone. The literature also reports on considerable variation in the number of fractions and the doses of each fraction [64]. In case of brachytherapy only 5 × 8 Gy or 8 × 5 Gy may be applied. Combined therapy usually delivers 50 Gy percutaneously with partial blocking of the bladder and intestines after 24 and 30 Gy and 2 to 5 fractions via brachytherapy. Brachytherapy may also be applied before commencement of percutaneous therapy. The selected dose may be applied by a variety of techniques e.g. by Heyman capsules, double-rod-shaped applicators, indwelling applicators etc. [64]. An appropriate applicator should ensure adequate irradiation of the entire uterus [94]. Nowadays, computer controlled treatment planning allows optimal treatment planning and an individual adaptation of the dose distribution to the uterine cavity. This may vary between patients of course. Only few clinical trials on primary radiotherapy have been performed. The results suggest that dividing doses into smaller fractions allows better tumor control and has less side effects [95]. The old question on high-dose-rate or low-dose-rate after loading still remains unsolved. There is still limited data on the efficiency of primary radiotherapy in endometrial carcinomas. An analysis of 154 patients having undergone primary radiotherapy at our department showed that local recurrences are more common in this group compared to surgery and adjuvant radiotherapy. The rates of recurrences are stage dependent: 23.3% vs. 13.2% in stage I and 39.2% vs. 25.9% in stage II [7]. As shown in figure 5 there is a significant difference in overall survival between both groups. Thus, primary radiotherapy represents an effective but suboptimal measure for this group of patients being in generally poorer physical condition. Figure 5 Decision tree concerning the treatment of recurrent endometrial carcinoma.Legend: ENCA = endometrial carcinoma; QoL = Quality of Life; RT = radiotherapy; HT = endocrine treatment; CHT = chemotherapy; Adjuvant postoperative irradiation Most studies indicate that advance age, grade 3 histology or deep myometrial invasion relate to a higher risk of disease recurrence. Therefore adjuvant radiotherapy seems important in this subset. External beam radiation should also be considered in cases of multiple infiltrated lymph nodes (> 5). But many questions remain unanswered and the value of postoperative irradiation is still under debate. Survival rates of patients with early stage disease are excellent, no matter whether they underwent extended-surgical staging with more restricted use of the adjuvant therapy or simple hysterectomy bilateral salpingoophorectomy with more frequent use of adjuvant radiotherapy [96]. Prospective-randomized trials have so far only demonstrated improved local control yet no overall survival benefit, and have higher rates of treatment related complications [97]. This accords to larger retrospective analyses, most likely due to the fact that the majority of these recurrences can be salvaged through radiation therapy [98]. With respect to the importance of the problem, trials to evaluate the therapeutic benefit of adjuvant radiotherapy in the several subsets of patients at higher risk are warranted. The American Brachytherapy Society has now issued recommendations for brachytherapy for carcinomas of the endometrium [94]. According to these, the applicator selection should be based on patient and target volume geometry, the dose prescription point should be clearly specified and the treatment plan should be optimized. For intravaginal brachytherapy selection of the largest diameter applicator is to ensure close mucosal apposition. Finally, doses should be reported both at the vaginal surface and at 0.5-cm depth irrespective of the dose prescription point. Adjuvant medical treatment The data on adjuvant medical treatment is not conclusive. Most studies have their limitations and therefore there is still no final answer to the question, who should receive what type of adjuvant treatment. Merely in cases of uterine papillary serous carcinomas, which affect 1% to 10% of patients, there is consensus that patients should receive chemotherapy (with or without adjuvant radiotherapy) with a platinum-based regimen, combined with doxorubicin and cyclophosphamide. Newer regimens consider paclitaxel, with or without platinum [99]. Adjuvant hormonal treatment A multicenter, open, controlled, prospectively randomized trial on adjuvant endocrine treatment with medroxyprogesterone acetate (MPA) or tamoxifen in stage I and II endometrial carcinomas failed to detect differences in the disease-free and overall survival rates for a tamoxifen group compared with a control or a MPA group [100]. However, the total number of patients on trial (n = 388) seems too low in relation to the favorable prognosis of early stage disease and the low total response rate of tamoxifen which ranged around 10% in this situation [101]. In the aforementioned study tamoxifen demonstrated only modest activity which lead the authors to the conclusion that tamoxifen does not warrant further investigation as a single agent but perhaps a sequential use of tamoxifen and progestational agents [101]. Adjuvant chemotherapy The generally good prognosis of endometrial carcinomas does not justify a general recommendation of chemotherapy, especially in the early stages. Even so, patients at high risk (unfavorable histological type, deep myometrial invasion and lymph-vascular space involvement) seem to profit from adjuvant chemotherapy [102,103]. Studies on the subject unfortunately often lack a control arm so the effects of chemotherapy remain unclear [104]. Well designed studies in the group of high risk patients are warranted. Preservation of fertility The development of endometrial cancer in young patients is usually related to unopposed estrogen stimulation. In patients with continuing a desire to have children, approaches have been made to preserve fertility. Primary hormonal therapy with progestins was suggested as an alternative treatment for surgery hereby offering the preservation of fertility. These must be interpreted with caution because of low case numbers and a publication bias. Treatment with megestrol acetate at 160 mg/day for 3 months or medroxyprogesterone acetate (MPA) at 200–800 mg/day for 2–14 months resulted in disease regression in 60 to 75%, however, the percentage of patients who actually delivered healthy children was much lower, ranging from 20 to 25% [105-107]. Furthermore, in several patients, persistent or recurrent disease was observed at the time of a later hysterectomy. In all these cases of unsatisfactory progestin therapy and delayed definitive surgical treatment may have adversely affected patient prognosis. In essence, the problems regarding the optimal selection of patients for conservative progestin therapy are unsolved. Only cases with good prognostic factors are to be selected: Well differentiated tumors and tumors with known favorable prognoses (e. g. endometrioid type tumors) with no or minimal myometrial invasion and early stage disease. The greatest problem lies in the difficulty of appropriate staging, resulting in a potential underestimation of the problem. Maybe positron emission tomography, magnetic resonance imaging or a combination of both may be useful in this respect in due course. Patients have to be carefully informed that this fertility preserving concept is still experimental. Moreover, these women must realize the low overall pregnancy rate which may partially be related to the origin of the disease (obesity, irregular menses, polycystic ovarian disease (PCOD) with chronic anovulation and infertility) [108]. Nowadays when treatment of infertility is frequently offered to elderly women, such conservative treatments should, however be investigated more thoroughly. Further questions concern follow-up of these patients. In the aforementioned studies, many patients were treated with maintenance therapy (oral contraceptives or cyclic progestins) to prevent recurrence, which was excluded by routine combination of sonography and D&C every 3–6 months. Palliative treatment – treatment of local recurrences Generally the prognosis for patients with recurrent disease is poor, therefore a thorough staging procedure should be performed. Analyses from other tumor entities, e.g. ovarian carcinomas, have demonstrated that a second surgical intervention may be useful in improving patients' overall survival [109,110]. Thus, even in absence of clinical studies on the subject, patients with single site recurrence should be evaluated for their suitability to surgery at relapse. In patients with isolated central recurrences, pelvic exenteration may be a potential option for cure [111]. The choice with respect to therapy of cancer recurrence strongly depends on prior treatment. In case of prior radiotherapy, a second intervention may often not be possible. If radiotherapy is possible, only nonbulky vaginal recurrences (< 0.5-cm thick) should be treated by intracavitary brachytherapy. Patients with bulky (> 0.5-cm thick) recurrences should receive interstitial techniques [94]. A general decision tree regarding the procedures in case of a recurrence is depicted in figure 6. Regarding the decision, whether or not to start with endocrine or cytotoxic treatment, the individual risk seems important. But equally important are aspects of patients' quality of life. A risk assessment scale, which was originally introduced by Possinger for breast cancer, seems helpful [108]. Similar to the adjuvant situation, treatment with tamoxifen, medroxyprogesterone acetate (MPA) alone or in combination may be used. However, there are only few, relatively old studies on the topic, all of which do not allow a final conclusion on the value of such therapies. MPA seems to be the best substance producing remission rates up to 80% in receptor positive tumors [113]. Remission rates of tamoxifen range around 25–30%. After failure of MPA, tamoxifen may be added to MPA producing remission rates in this combination of 50–60% [114]. Also aminogluthemide seems to be active in endometrial cancer [115]. Responses to all kinds of treatments unfortunately do not tend to last for long. Figure 6 Comparison of overall survival between patients undergoing surgery and radiotherapy or primary radiotherapy. Note that patients in the group undergoing primary radiotherapy were generally older Some studies also suggest a potential benefit for luteinizing hormone-releasing hormone analogues (GnRH), although studies in endometrial carcinomas have not shown any convincing activity [116-118]. To sum, up on the background of the few and old studies with often low case numbers, newer large studies on endocrine strategies are warranted. With respect to chemotherapy, several cyctostatic compounds have demonstrated efficiency. Among these are paclitaxel, carboplatinum, doxorubicin, cisplatin, etoposide, and 5 fluorouracil. Topotecan showed only limited activity [119-124]. All drugs may be used alone or in combination, perhaps even in combination with hormonal therapy [125,126]. Again, realizing that combination chemotherapy produces greater side effects, every option, endocrine treatment, single drug or combination chemotherapy should be considered. Follow-up Generally recommendation for clinical follow-up of patients advocate patients to be monitored at three-monthly intervals during the first 3 years, at 6-monthly intervals up to the 5th year and at yearly intervals thereafter. Apart from provision of general information on all aspects of the disease and its treatment including unconventional cancer therapies, the documentation of patients' history, a clinical gynecological examination including a pap smear, a vaginal sonography and even the determination of tumor markers (SCC, CA125) have been recommended. Up to 95% of all recurrences may be detected early this way [127]. Again there are no prospective studies on the subject to enforce such recommendations. On the contrary, several retrospective studies indicate that an intensive follow-up does not result in a survival advantage for patients with recurrent disease but merely increases costs [7,128-131]. Also in this area the most appropriate management of endometrial carcinomas remains to be determined. In any case an annual examination of the breast, including mammography, is recommended, due to the fact of the frequent coincidence of malignancies of the breast [7]. Estrogen replacement therapy in endometrial cancer patients Hormone replacement therapy (HRT) with estrogen with or without progestins is frequently used to alleviate menopausal symptoms but also to reduce the risk of osteoporosis and cognitive dysfunctions. In endometrial carcinomas HRT may be believed to be critical due to fear of initiating growth of occult residual tumor cells, resulting in disease recurrence and shortened survival. As summarized by the American College of Obstetricians and Gynecologists (ACOG) there is not enough data to draw any final conclusion. Any decision on the subject should thus be individualized based on potential benefit and risk to the patient [132]. Some studies which have addressed this subject covered only a small number of patients in regard to the overall excellent prognosis of endometrial cancer patients. Of all these studies, however, none produced evidence that patients should not receive estrogen [133-136]. On the contrary, some studies reported an even prolonged survival for patients (with low-risk factors for recurrence, namely, low tumor grade (grades 1 and 2), less than 1/2 myometrial invasion, and no metastases to lymph nodes or other organs,) who received estrogen [134,136]. Furthermore, the introduction of selective estrogen receptor modulators (SERM) has also offered new treatment options which will also have to be studied in the future. Final remarks Endometrial carcinomas represent a very frequent tumor entity in industrialized countries. It is hard to believe how little evidence-based data exists on even the important aspects of the disease. This may be partially due to the overall good prognosis even if surgery is reduced to hysterectomy and adnectomy. However, the high incidence in the developed world and consequently many women suffering relapses, necessitates the research of new approaches for cancer recurrence. Recent research suggests that therapy with trastuzumab (Herceptin®) could perhaps improve the outcome in HER-2/neu overexpressing tumors [137]. Further research will focus on molecules and pathways responsible for the initiation and growth of endometrial carcinomas, including tumor suppressor genes, DNA mismatch repair genes, oncogenes, molecules involved in adhesion and invasion and angiogenesis [138]. This research will hopefully allow the development of specific and selective inhibitors. Some advances may also be possible with – conventional treatment, especially radiotherapy. Recent findings of a retrospective analysis suggest that tumor oxygenation may play an important role during adjuvant radiotherapy of endometrial carcinomas. Patients with normal hemoglobin levels during therapy (according to the definition of the EORTC = 12.0 g/dl) have a substantially better overall and recurrence free survival (Figure 7) [139]. Due to this strong impact on patients' health, these aspects require further studies. Figure 7 Comparison of recurrence-free survival between in patients undergoing adjuvant radiotherapy with respect to anemia. 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==== Front J NeuroinflammationJournal of Neuroinflammation1742-2094BioMed Central London 1742-2094-1-131528580210.1186/1742-2094-1-13Short ReportTumor necrosis factor-mediated inhibition of interleukin-18 in the brain: a clinical and experimental study in head-injured patients and in a murine model of closed head injury. Schmidt Oliver I 1olischmidt@web.deMorganti-Kossmann Maria Cristina 2cristina.morganti-kossmann@med.monash.edu.auHeyde Christoph E 1ceheyde@aol.comPerez Daniel 3danielperezch@yahoo.comYatsiv Ido 4idoyat@yahoo.comShohami Esther 4esty@huji.ac.ilErtel Wolfgang 1wolfgang.ertel@charite.deStahel Philip F 1pfstahel@aol.com1 Department of Trauma and Reconstructive Surgery, Charité University Medical School, Campus Benjamin Franklin, Berlin, Germany2 Department of Trauma Surgery, The Alfred Hospital, Monash University, Melbourne, Australia3 Department of Surgery, University Hospital Zurich, Switzerland4 Department of Pharmacology, The Hebrew University, Hadassah Medical School, Jerusalem, Israel2004 28 7 2004 1 13 13 18 6 2004 28 7 2004 Copyright © 2004 Schmidt et al; licensee BioMed Central Ltd.2004Schmidt et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Tumor necrosis factor (TNF) and interleukin-(IL)-18 are important mediators of neuroinflammation after closed head injury (CHI). Both mediators have been previously found to be significantly elevated in the intracranial compartment after brain injury, both in patients as well as in experimental model systems. However, the interrelation and regulation of these crucial cytokines within the injured brain has not yet been investigated. The present study was designed to assess a potential regulation of intracranial IL-18 levels by TNF based on a clinical study in head-injured patients and an experimental model in mice. In the first part, we investigated the interrelationship between the daily TNF and IL-18 cerebrospinal fluid levels in 10 patients with severe CHI for up to 14 days after trauma. In the second part of the study, the potential TNF-dependent regulation of intracerebral IL-18 levels was further characterized in an experimental set-up in mice: (1) in a standardized model of CHI in TNF/lymphotoxin-α gene-deficient mice and wild-type (WT) littermates, and (2) by intracerebro-ventricular injection of mouse recombinant TNF in WT C57BL/6 mice. The results demonstrate an inverse correlation of intrathecal TNF and IL-18 levels in head-injured patients and a TNF-dependent inhibition of IL-18 after intracerebral injection in mice. These findings imply a potential new anti-inflammatory mechanism of TNF by attenuation of IL-18, thus confirming the proposed "dual" function of this cytokine in the pathophysiology of traumatic brain injury. Closed head injuryinflammationcytokinesTNFinterleukin-18. ==== Body Findings Closed head injury (CHI) is the leading cause of mortality and persisting neurological impairment in young people in industrialized countries [1,2]. The neuropathological sequelae of brain injury are mediated in large part by a profound host-mediated intracranial inflammatory response [3-5]. The pro-inflammatory cytokines tumor necrosis factor (TNF) and interleukin (IL)-18 have been identified as crucial mediators of neuroinflammation after brain injury [6-9]. This notion has been supported by experimental studies in rodents which demonstrated neuroprotective effects by pharmacological inhibition of either TNF or IL-18 after CHI [9-11]. In recent years, the concept of a "dual role" evolved with regard to concomitant beneficial and adverse effects of pro-inflammatory mediators, depending on the kinetic of their expression and posttraumatic regulation in the injured brain [3,12,13]. However, the TNF-dependent regulation of IL-18 in the injured brain has not yet been investigated. We sought to determine the interrelationship between intracranial TNF and IL-18 levels in a clinical study on patients with severe CHI and in an experimental model in mice. Patients with isolated severe closed head injury (n = 10, Glasgow Coma Scale score ≤ 8) and indication for intraventricular catheters for cerebrospinal fluid (CSF) drainage due to increased intracranial pressure (ICP > 15 mm Hg) were included in this study. Drained CSF was collected daily for up to 14 days after trauma or until catheters were removed. The patient characteristics are shown in Table 1. No patient was treated with steroids. The protocol for daily CSF collection is in compliance with the Helsinki Declaration and was approved by the University's Ethics Board Committee. Control CSF was collected from patients undergoing diagnostic spinal tap (n = 10) and revealed no inflammatory CNS disease, based on normal CSF protein and glucose levels and normal white cell counts. All samples were kept on ice at 4°C and immediately centrifuged after collection, aliquoted, and frozen at -70°C until analysis. Table 1 Clinical data and intrathecal cytokine levels in patients with severe closed head injury. Patient Age (years) / Gender Type of brain injury (Marshall score) Outcome (GOS) TNF in CSF (pg/mL) IL-18 in CSF (pg/mL) Correlation rS Mean Range Mean Range 1 38 / M EML 4 6.4 1.0 – 11.5 40.6 6.5 – 155.2 - 0.804 ** 2 30 / M DI II° 3 3.6 1.0 – 7.7 114.3 29.7 – 286.4 - 0.580 * 3 56 / M EML 4 6.3 1.0 – 10.0 35.1 11.2 – 100.3 - 0.530 4 57 / F DI II° 5 6.0 1.0 – 11.7 20.1 5.0 – 168.8 - 0.761 ** 5 44 / M EML 4 1.6 1.0 – 3.4 39.8 22.6 – 74.5 - 0.751 * 6 26 / M EML 4 3.2 1.0 – 10.3 108.5 5.0 – 328.6 - 0.832 ** 7 47 / M EML 1 1.1 1.0 – 1.4 268.5 78.3 – 462.0 - 0.372 8 25 / M EML 4 2.2 1.0 – 4.0 91.6 10.3 – 290.0 - 0.195 9 37 / F DI III° 3 1.6 1.0 – 2.7 183.7 21.5 – 382.2 - 0.844 ** 10 35 / M DI II° 4 2.0 1.0 – 5.8 209.4 19.9 – 391.8 - 0.772 * Controls (n = 10) 1.0 1.0 – 7.1 5.0 5.0 – 8.4 Statistical analysis for assessment of the correlation between tumor necrosis factor (TNF) and interleukin (IL)-18 levels in serial cerebrospinal fluid samples for up to 14 days after trauma was performed by Spearman's rank correlation (*P < 0.05, **P < 0.01). The patients' outcome was determined at 3 months after injury by the Glasgow Outcome Scale (GOS) score [33]: 5 = asymptomatic, 4 = moderate disability, 3 = severe disability, 2 = persisting vegetative state, 1 = death. The type of brain injury was classified by the CT-scan criteria established by Marshall et al. [34] into diffuse injury (DI) grade I-III and evacuated vs. non-evacuated mass lesions (EML, NEML). Quantification of IL-18 and TNF levels in human CSF samples and in murine brain homogenates was performed by species-specific commercially available ELISA (R&D Systems, Abingdon, UK). According to the information provided by the manufacturer, the IL-18 assay recognizes both the mature and the pro-form of IL-18. All concentrations below the detection limit of 5 pg/mL (IL-18) or 1 pg/ml (TNF) were assigned a value of 5 pg/mL, and 1 pg/ml respectively. All samples were run undiluted in duplicate wells. The concentrations were calculated from the mean OD of duplicate samples, determined by spectrophotometer (Dynatech Laboratories Inc., Chantilly, VA, U.S.A.) at an extinction wavelength of 405 nm. The experimental part of the study was set-up on two different protocols with the aim to assess the TNF-dependent regulation of IL-18 in the murine brain: (1) The first part of the experimental study was designed to investigate a potential role of TNF-dependent regulation of intracranial IL-18 expression in a standardized model of CHI, using mice double-deficient in genes for TNF and lymphotoxin-α (TNF/LT-α-/-) [14]. These knockout mice were selected in order to compensate for potential redundant functions of TNF by LT-α which binds to the identical common receptors (i.e. TNF receptors p55 and p75) [14-16]. The generation and development of the TNF/LT-α-/- mice on a mixed C57BL/6 × 129Sv/Ev (B6 × 129) genetic background has been previously described [14]. Knockout mice and wild-type (WT) littermates of the B6 × 129 strain were subjected to a CHI (n = 10 per group) using a standardized weight-drop model, as previously described [9,17]. In brief, following ether anesthesia, a midline longitudinal scalp incision was performed. Trauma was applied to the left anterior frontal area of the exposed skull by a 330 g weight with a silicon tip dropped from a height of 2 cm, resulting in a focal closed injury to the left hemisphere. Mice received supporting oxygenation with 100% O2 until they awakened and were then brought back to their cages. Control animals were subjected to anesthesia and sham operation only (n = 10 per group). In addition, mice with anesthesia alone (n = 8) were used as internal control and untreated control animals (n = 10) were analyzed for baseline evaluation of intracerebral cytokine profiles in these mice. (2) In the 2nd part of the experimental study, mice of the C57BL/6 strain (n = 10 per group) were treated by stereotactic intracerebroventricular (i.c.v.) injection of either 200 ng mouse recombinant TNF in 10 μl PBS, or vehicle solution only (10 μl PBS), into the left hemisphere using a sterile 27-gauge syringe, under ether anesthesia. According to data from previously published studies [18-20], as well as based on titration studies from our own laboratory, the i.c.v. injection of 200 ng mouse-recombinant TNF (R&D Systems) elicited an evident induction of inflammatory changes in the murine CNS, such as intracranial recruitment of leukocytes and development of brain edema in the injected hemisphere within 24 hours (data not shown). Animals from all groups (CHI and i.c.v. injection) were sacrificed at 24 h after the respective procedure, which corresponds to the time-point of maximal extent of intracerebral inflammation in the model of CHI used in this study [17]. For assessment of intracerebral IL-18 levels, the murine brains were immediately removed after decapitation. Tissue homogenization was performed using a Polytron homogenizer (Kinematica, Kriens, Switzerland) with a dilution of 1:4 in ice cold extraction buffer containing 50 mmol/L Tris buffer (pH 7.2), NaCl 150 mmol/L, Triton-X-100 1%, and protease inhibitor cocktail (Roche, Mannheim, Germany). The homogenates were shaken on ice for 90 minutes, centrifuged for 15 minutes at 3,000 g and 4°C. Thereafter, the supernatants were aliquoted and stored at -70°C until analysis. The concentrations of total protein in the brain extracts were measured by Bradford assay (Bio Rad Laboratories, Munich, Germany). The intracerebral protein concentrations were in a similar range in all mice assessed (11.7 ± 2.4 mg/mL; mean ± SD). The quantification of IL-18 levels in murine brain homogenates was performed as described above for the human samples. All mice used in this study were males, in order to avoid a bias in gender, age 12 to 16 weeks with body weights of 25 to 32 g. The animal experiments were performed in compliance with the guidelines of the Federation of European Laboratory Animal Science Association (FELASA) and approval was granted by the Institutional Animal Care Committee of the University of Zurich and of the Hebrew University of Jerusalem. In the clinical part of the study on CHI patients, the mean IL-18 concentrations in ventricular CSF collected up to 14 days after trauma were significantly higher than in control lumbar CSF from patients undergoing diagnostic spinal tap (P< 0.05, repeated measures ANOVA; Table 1). These findings are coherent with data from previously published studies which demonstrated significantly elevated intracranial IL-18 levels after brain injury, both in humans as well as in experimental model systems [8,9]. With regard to TNF, the mean levels in individual serial cerebrospinal fluid samples were significantly elevated in 50% of all head-injured patients, compared to controls (patients #1,2,3,4,6; Table 1). Elevated intracranial TNF levels after traumatic brain injury have been previously reported in various clinical and experimental studies [21-26]. In the present study, the individual daily TNF levels in CSF were up to 10- to 100-fold lower than the corresponding IL-18 levels (Table 1). Interestingly, despite the fairly low TNF levels in CSF we found an inverse correlation between the daily individual intrathecal TNF and IL-18 levels in all trauma patients, as demonstrated by a negative Spearman's rank correlation coefficient (r = -0.195 to -0.844). In 7 of 10 patients, this inverse correlation was statistically significant, with a P-value < 0.05 in three patients (# 2,5,10) and P < 0.01 in four patients (# 1,4,6,9; Table 1). Since the quality of the blood-brain barrier has not been determined in this cohort of head-injured patients, due to the lack of matching serum samples for assessment of albumin levels, the source of elevated cytokines (intrathecal compartment vs. peripheral serum) remains unclear. In the experimental study, IL-18 was found to be constitutively expressed in the brain of untreated mice (27.7 ± 5.4 ng/mL, mean ± SEM; "baseline", Fig. 1), which is in accordance with data from previous studies revealing constitutive IL-18 expression in the CNS of normal rats and mice [8,9,27,28]. Microglia may represent the cellular source of constitutive intracranial IL-18 levels in these mice, since Prinz and colleagues have previously shown that microglial cells, but not astrocytes, produce IL-18 in the murine CNS [28]. The intracerebral IL-18 levels increased significantly in the head-injured group by 24 hours after experimental CHI (56.9 ± 4.7 ng/mL, P < 0.01 vs. baseline, Fig. 1). Knockout mice lacking TNF and LT-α genes also showed significantly elevated IL-18 concentrations at 24 h after CHI (58.4 ± 7.8 ng/mL) which were in a similar range as in head-injured WT mice, as shown in Fig. 1. This lack of differences in mice deficient in the ligands for TNF receptors may be explained by alternatively expressed inflammatory mediators or modified pathways of IL-18 regulation in these genetically engineered mice which have been shown to have significantly altered immune responses [14]. Interestingly, the intracerebral injection of vehicle alone (10 μl PBS i.c.v.) induced significantly elevated IL-18 levels in brains of normal WT mice, compared to normal untreated mice, which were in a similar range as in the brain-injured groups (53.6 ± 9.6 ng/ml, Fig. 1). These data imply that a minor penetrating injury by i.c.v. injection of a small volume of buffer solution represents a procedure which is sensitive enough to induce significant IL-18 production in murine brains within 24 hours. In contrast, the intracerebral injection of murine recombinant TNF (in 10 μl PBS) reduced the elevated IL-18 levels in murine brains significantly to levels than were even lower than baseline concentrations (22.13 ± 7.1, P < 0.01 vs. vehicle-injected mice), as shown in Fig. 1. Figure 1 Intracerebral IL-18 concentrations in mice, as determined by ELISA in murine brain homogenates (n = 10 animals per group). Untreated normal mice were used for determination of baseline IL-18 levels in this study. The four treatment groups were sacrificed after 24 hours for assessment of intracerebral IL-18 levels, as described in the text. Mice deficient in genes for TNF and lymphotoxin-α (TNF/LT-α-/-) and wild-type (WT) littermates were subjected to focal closed head injury (CHI) and sacrificed after 24 hours. Two additional groups of WT mice were given an intracerebro-ventricular (i.c.v.) injection of 200 ng mouse-recombinant TNF in 10 μl PBS or by vehicle alone (10 μl PBS i.c.v.). The data are presented as means ± SEM. *P < 0.01 vs. baseline / TNF-injection (unpaired Student's t-test). The findings from these experimental investigations corroborate the data from the clinical study, where an inverse correlation of intrathecal TNF and IL-18 levels during the first 14 days after severe CHI was found, suggesting that the inhibition of IL-18 may represent a new potential anti-inflammatory mechanism after CHI. Such a "dual role" of TNF has been suggested previously in terms of concomitant pro- and anti-inflammatory effects and detrimental as well as beneficial neuroprotective properties after brain injury [12]. While the pro-inflammatory effects mediated by TNF in the CNS have been thoroughly investigated in the past two decades [15,29,30], the concept of anti-inflammatory effects mediated by cytokines which have been formerly designated as "pro-"inflammatory mediators, is still challenging and novel. Scherbel and colleagues were the first to provide evidence of beneficial effects of TNF in the later phase (i.e. 4 weeks) after traumatic brain injury, based on studies in TNF-/- mice subjected to controlled cortical impact brain injury [31]. In these experiments, the TNF-deficient mice showed a significantly attenuated neurobehavioral impairment than WT littermates in the first 48 hours post trauma, in terms of early detrimental effects mediated by TNF [31]. However, the expected neurobehavioral recovery was absent in TNF-/- mice after 4 weeks and cortical tissue loss was significantly increased at this time-point, compared to WT littermates, implying that at later time-points the lack of TNF leads to adverse outcome after brain injury [31]. Barger and colleagues have previously shown in an in vitro model of amyloid β-mediated neurotoxicity that both TNF and LT-α (formerly designated TNF-β) can significantly attenuate neuronal degeneration by induction of antioxidative pathways through activation of the transcription factor NFκb, thus strengthening the notion of neuroprotective effects mediated by these cytokines [32]. This assumption was further corroborated in the setting of experimental CHI, where mice lacking both TNF and LT-α genes were shown to have a significantly increased mortality within one week after trauma, compared to WT littermates [17]. Overall, these data support the notion that TNF exerts detrimental effects in the early phase and beneficial neuroprotective effects in the later phase after head injury [12]. However, the assumptive underlying regulatory mechanisms of TNF-mediated neuroprotection and of TNF-mediated suppression of IL-18 in the injured brain remain unclear and have to be investigated in future experimental studies. List of abbreviations Central nervous system (CNS), cerebrospinal fluid (CSF), closed head injury (CHI), intracerebroventricular (i.c.v.), interleukin (IL), lymphotoxin-α (LT-α / TNF-β), nuclear factor κB (NFκB), tumor necrosis factor (TNF), phosphate-buffered saline (PBS), intracranial pressure (ICP), wild-type (WT), enzyme-linked immunosorbent assay (ELISA). Competing interests There are no financial interests by any of the authors with regard to the present project. Authors' contributions OIS, MCMK, CEH, ES, and PFS were responsible for conception and planning of the experiments, as well as for performing the animal experiments, collection of the human cerebrospinal fluid samples and cytokine measurements in human and murine tissue samples, as well as for writing of the manuscript. DP and IY performed the experimental i.c.v. injection experiments. WE contributed to the interpretation of the results and writing of the manuscript. Acknowledgments The authors thank Dr. Hans-Pietro Eugster (Division of Clinical Immunology, University of Zurich, Switzerland) for providing the TNF/lymphotoxin-α knockout mice. Dr. Volkmar Hans (Department of Neuropathology, Gilead Clinic, Bielefeld, Germany) is acknowledged for critical review of the manuscript. ==== Refs Marshall LF Head injury: recent past, present, and future Neurosurgery 2000 47 546 561 10981741 Bayir H Clark RS Kochanek PM Promising strategies to minimize secondary brain injury after head trauma Crit Care Med 2003 31 S112 7 12544985 10.1097/00003246-200301001-00016 Morganti-Kossmann MC Rancan M Stahel PF Kossmann T Inflammatory response in acute traumatic brain injury: a double-edged sword Curr Opin Crit Care 2002 8 101 105 12386508 10.1097/00075198-200204000-00002 Ransohoff RM The chemokine system in neuroinflammation: an update J Infect Dis 2002 186 Suppl 2 S152 6 12424691 10.1086/344266 Barnum SR Complement in central nervous system inflammation Immunol Res 2002 26 7 13 12403340 10.1385/IR:26:1-3:007 Hedtjarn M Leverin AL Eriksson K Blomgren K Mallard C Hagberg H Interleukin-18 involvement in hypoxic-ischemic brain injury J Neurosci 2002 22 5910 5919 12122053 Jander S Schroeter M Stoll G Interleukin-18 expression after focal ischemia of the rat brain: association with the late-stage inflammatory response J Cereb Blood Flow Metab 2002 22 62 70 11807395 10.1097/00004647-200201000-00008 Menge T Jander S Stoll G Induction of the pro-inflammatory cytokine interleukin-18 by axonal injury J Neurosci Res 2001 65 332 339 11494369 10.1002/jnr.1158 Yatsiv I Morganti-Kossmann MC Perez D Dinarello CA Novick D Rubinstein M Otto VI Rancan M Kossmann T Redaelli CA Trentz O Shohami E Stahel PF Elevated intracranial IL-18 in humans and mice after traumatic brain injury and evidence of neuroprotective effects of IL-18-binding protein after experimental closed head injury J Cereb Blood Flow Metab 2002 22 971 978 12172382 10.1097/00004647-200208000-00008 Shohami E Bass R Wallach D Yamin A Gallily R Inhibition of tumor necrosis factor alpha (TNFalpha) activity in rat brain is associated with cerebroprotection after closed head injury J Cereb Blood Flow Metab 1996 16 378 384 8621742 10.1097/00004647-199605000-00004 Shohami E Gallily R Mechoulam R Bass R Ben-Hur T Cytokine production in the brain following closed head injury: dexanabinol (HU-211) is a novel TNF-alpha inhibitor and an effective neuroprotectant J Neuroimmunol 1997 72 169 177 9042110 10.1016/S0165-5728(96)00181-6 Shohami E Ginis I Hallenbeck JM Dual role of tumor necrosis factor alpha in brain injury Cytokine Growth Factor Rev 1999 10 119 130 10743503 10.1016/S1359-6101(99)00008-8 Lenzlinger PM Morganti-Kossmann MC Laurer HL McIntosh TK The duality of the inflammatory response to traumatic brain injury Mol Neurobiol 2001 24 169 181 11831551 10.1385/MN:24:1-3:169 Eugster HP Müller M Karrer U Car BD Schnyder B Eng VM Woerly G Le Hir M di Padova F Aguet M Zinkernagel R Bluethmann H Ryffel B Multiple immune abnormalities in tumor necrosis factor and lymphotoxin-alpha double-deficient mice Int Immunol 1996 8 23 36 8671586 Wallach D Varfolomeev EE Malinin NL Goltsev YV Kovalenko AV Boldin MP Tumor necrosis factor receptor and Fas signaling mechanisms Annu Rev Immunol 1999 17 331 367 10358762 10.1146/annurev.immunol.17.1.331 Probert L Akassoglou K Kassiotis G Pasparakis M Alexopoulou L Kollias G TNF-alpha transgenic and knockout models of CNS inflammation and degeneration J Neuroimmunol 1997 72 137 141 9042105 10.1016/S0165-5728(96)00184-1 Stahel PF Shohami E Younis FM Kariya K Otto VI Lenzlinger PM Grosjean MB Eugster HP Trentz O Kossmann T Morganti-Kossmann MC Experimental closed head injury: analysis of neurological outcome, blood-brain barrier dysfunction, intracranial neutrophil infiltration, and neuronal cell death in mice deficient in genes for pro-inflammatory cytokines J Cereb Blood Flow Metab 2000 20 369 380 10698075 10.1097/00004647-200002000-00019 Seabrook TJ Hay JB Intracerebroventricular infusions of TNF-alpha preferentially recruit blood lymphocytes and induce a perivascular leukocyte infiltrate J Neuroimmunol 2001 113 81 88 11137579 10.1016/S0165-5728(00)00429-X Ramilo O Saez-Llorens X Mertsola J Jafari H Olsen KD Hansen EJ Yoshinaga M Ohkawara S Nariuchi H McCracken Jr, G.H. Tumor necrosis factor alpha / cachectin and interleukin 1 beta initiate meningeal inflammation J Exp Med 1990 172 497 507 2373990 10.1084/jem.172.2.497 Saukkonen K Sande S Cioffe C Wolpe S Sherry B Cerami A Tuomanen E The role of cytokines in the generation of inflammation and tissue damage in experimental gram-positive meningitis J Exp Med 1990 171 439 448 2406363 10.1084/jem.171.2.439 Goodman JC Robertson CS Grossman RG Narayan RK Elevation of tumor necrosis factor in head injury J Neuroimmunol 1990 30 213 217 2229409 10.1016/0165-5728(90)90105-V Ross SA Halliday MI Campbell GC Byrnes DP Rowlands BJ The presence of tumour necrosis factor in CSF and plasma after severe head injury Br J Neurosurg 1994 8 419 425 7811406 Csuka E Morganti-Kossmann MC Lenzlinger PM Joller H Trentz O Kossmann T IL-10 levels in cerebrospinal fluid and serum of patients with severe traumatic brain injury: relationship to IL-6, TNF-alpha, TGF-beta1 and blood-brain barrier function J Neuroimmunol 1999 101 211 221 10580806 10.1016/S0165-5728(99)00148-4 Shohami E Novikov M Bass R Yamin A Gallily R Closed head injury triggers early production of TNF alpha and IL-6 by brain tissue J Cereb Blood Flow Metab 1994 14 615 619 8014208 Fan L Young PR Barone FC Feuerstein GZ Smith DH McIntosh TK Experimental brain injury induces differential expression of tumor necrosis factor-alpha mRNA in the CNS Mol Brain Res 1996 36 287 291 8965649 10.1016/0169-328X(95)00274-V Knoblach SM Fan L Faden AI Early neuronal expression of tumor necrosis factor-alpha after experimental brain injury contributes to neurological impairment J Neuroimmunol 1999 95 115 125 10229121 10.1016/S0165-5728(98)00273-2 Culhane AC Hall MD Rothwell NJ Luheshi GN Cloning of rat brain interleukin-18 cDNA Mol Psychiatry 1998 3 362 366 9702748 10.1038/sj.mp.4000389 Prinz M Hanisch UK Murine microglial cells produce and respond to interleukin-18 J Neurochem 1999 72 2215 2218 10217305 10.1046/j.1471-4159.1999.0722215.x Rothwell NJ Hopkins SJ Cytokines and the nervous system II: Actions and mechanisms of action Trends Neurosci 1995 18 130 136 7754524 10.1016/0166-2236(95)93890-A Allan SM Rothwell NJ Cytokines and acute neurodegeneration Nat Rev Neurosci 2001 2 734 744 11584311 10.1038/35094583 Scherbel U Raghupathi R Nakamura M Saatman KE Trojanowski JQ Neugebauer E Marino MW McIntosh TK Differential acute and chronic responses of tumor necrosis factor-deficient mice to experimental brain injury Proc Natl Acad Sci U S A 1999 96 8721 8726 10411942 10.1073/pnas.96.15.8721 Marshall LF Marshall SB Klauber MR Van BerkumClark M Eisenberg H Jane JA Luerssen TG Marmarou A Foulkes MA The diagnosis of head injury requires a classification based on computed axial tomography. J Neurotrauma 1992 9 Suppl 1 S287 292 1588618 Jennet B Bond M Assessment of outcome after severe brain damage. Lancet 1975 1 480 484 46957 10.1016/S0140-6736(75)92830-5 Marshall LF Marshall SB Klauber MR Van Berkum Clark M Eisenberg H Jane JA Luerssen TG Marmarou A Foulkes MA The diagnosis of head injury requires a classification based on computed axial tomography . J Neurotrauma 1992 9 Suppl 1 S287 292 1588618

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J Neuroinflammation. 2004 Jul 28; 1:13

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==== Front RetrovirologyRetrovirology1742-4690BioMed Central London 1742-4690-1-191528579010.1186/1742-4690-1-19CommentaryThe expanding role of Tax in transcription de la Fuente Cynthia 2bcmclf@gwumc.eduKashanchi Fatah 123bcmfxk@gwumc.edu1 Institute for Proteomics Technology and Application, The George Washington University, Washington, DC 20037, USA2 Department of Biochemistry and Molecular Biology, The George Washington University School of Medicine, Washington, DC 20037, USA3 The Institute for Genomic Research (TIGR), Rockville, MD 20850, USA2004 30 7 2004 1 19 19 14 7 2004 30 7 2004 Copyright © 2004 de la Fuente and Kashanchi; licensee BioMed Central Ltd.2004de la Fuente and Kashanchi; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The viral transactivator of HTLV-I, Tax, has long been shown to target the earliest steps of transcription by forming quaternary complexes with sequence specific transcription factors and histone-modifying enzymes in the LTR of HTLV-I. However, a new study suggests that Tax preferentially transactivates the 21-bp repeats through CREB1 and not other bZIP proteins. The additional transactivation of Tax-responsive promoters subsequent to initiation is also presented. This result highlights a potentially novel role of Tax following TBP recruitment (i.e. initiation) and may expand the mechanism of Tax transactivation in promoter clearance and transcriptional elongation. ==== Body Viruses have long been a source of key scientific discoveries. Historically, they have contributed to our knowledge of transcription, cell cycle, and apoptosis. To date activated transcription in higher eukaryotic cells with or without chromatin is a great area of active research and many researchers use viral activators, including herpes virus VP16, adenovirus E1A, HIV-1 Tat and HTLV-I Tax to not only understand viral, but also basic mechanisms related to host control of vital cellular machineries, including transcription. Eukaryotic transcription has five distinct phases, pre-initiation, initiation, promoter clearance, elongation and termination, and is a tightly regulated and coupled process [1]. Viral transactivators, such as Tax, have long been shown to target the earliest steps of transcription by forming quaternary complexes with sequence specific transcription factors and histone-modifying enzymes in the LTR of HTLV-I. These Tax-containing complexes allow for increased recruitment of TBP (TFIID), GTFs, and RNAP II within the core promoter region, leading to the synthesis of viral RNA. However, determination of those cellular factors important for enhanced transcriptional activity, as well as the full scope of Tax transactivation, is still not fully elucidated. In the report by Ching et al. [2] the authors directly compare which HTLV-I enhancer motif is preferred by Tax. Each enhancer element (21-bp, CRE, AP1, SP1, κB, or SRE) was placed in an identical TATAA-context to generate a minimal HTLV-I promoter. Previous studies had utilized various promoters (which contain additional DNA elements) to highlight a particular enhancer element necessary for Tax transactivation. Thus, this is the first study to directly compare these elements in an identical setting. In the presence of Tax, the 21-bp repeat (also known as the viral CRE elements or TxREs) was found to be most responsive (70-fold above basal levels). The 21-bp repeat was clearly preferred by Tax, since other enhancer elements were only stimulated 10-fold or less. Previously, several studies suggested that Tax activation of the 21-bp repeats may be mediated by ATF-4 [3-5]. It was shown that Tax was able to interact with ATF-4 bound to the 21-bp repeats, enhance the binding of ATF-4 to the enhancer, and recruit CREB binding protein (CBP) to the viral promoter [5]. Recently, CREB1 and ATF-4, in addition to ATF-1 and ATF-2, were found to be present in vivo on the 21-bp repeats (viral CRE elements) in HTLV-I infected cells through chromatin immunoprecipitation (ChIP) assays [6]. By using dominant negative mutants of CREB1, ATF-4 (CREB2/TAXREB67), Fos, and LZIP, Ching et al. demonstrated that among the various bZIP proteins, CREB1 was clearly favored for Tax transactivation of the 21-bp repeats. Additionally, CREB1 has also been found to primarily bind at the 5' LTR (rather than the 3' LTR) in vivo within HTLV-I infected cells, lending support to the idea that CREB1 is important for HTLV-I activated transcription [7]. If CREB1 is the dominant bZIP protein that is needed for Tax transactivation of the LTR, then what is the purpose of the additional bZIP proteins? Besides contributing to Tax transactivation, could these bZIP proteins help to exclude negative regulators from the LTR? A report by Basbous et al. [8] suggested that HBZ, which negatively down-regulated transcription from the HTLV-I LTR, heterodimerized with ATF-4 and subsequently this complex was no longer able to bind to the 21-bp repeats. Only over-expression of ATF-4 was found to reverse the negative effects of HBZ on Tax activity. However, additional studies are still needed to understand the respective contribution of CREB1 and other bZIP proteins, such as ATF-4, to Tax transactivation in the context of wildtype virus and stably integrated viral promoters (i.e. correctly assembled chromatinized DNA templates both in vitro and in vivo). Lastly, Ching et al. presented the intriguing possibility of Tax enhancing transcription following transcription initiation. To determine whether Tax functioned solely to target TBP to the TATAA-element or if additional events subsequent to TBP (TFIID) recruitment were promoted by Tax, the authors constructed four independent reporters. Each promoter contained the minimal TATAA-element from HTLV-I, HIV-1, SV-40, or E1b promoters, two 21-bp repeats, and five copies of the Gal4-binding site. TBP was artificially targeted to the TATAA-element thru Gal4-TBP. The authors reasoned that if Tax functioned strictly to recruit TBP to the TATAA-element, then additional enhancement of transcription would not be observed when Tax and Gal4-TBP were present. Interestingly, only the Tax-responsive promoters, i.e. HTLV-I and HIV-1, were both synergistically stimulated by the addition of Tax and Gal4-TBP. These results suggest that Tax may control downstream transcription subsequent to the initiation phase. Other viral transactivators have been shown to have a role at initiation and downstream events, such as elongation. The most notable of these has been Tat, the viral transactivator of HIV-1. Without cellular stimulation and Tat expression, RNAP II transcriptional elongation was shown to be inefficient, producing only short transcripts [9]. One major contributing factor of Tat-dependent transactivation is the elongation factor, pTEFb. pTEFb, composed of cyclin T1 and cdk9, associates with Tat leading to increased phosphorylation at specific sites on the heptad repeats of the CTD of RNAP II and promoting elongation. Elongation is highly dependent on the status of RNAP II CTD, since dissociation/association of factors have been shown to be dependent on CTD serine 5/serine 2 phosphorylation [1,10]. Hyperphosphorylation of CTD at serine 5 is associated with promoter clearance/early elongation, whereby initiation factors are released and the 5'capping machinery subsequently recruited. During processive elongation, there is a switch in CTD phosphorylation to serine 2 phosphorylation resulting in the loss of the capping machinery and the association of splicing, elongation and chromatin remodeling factors. In the case of HTLV-I, Tax has been shown not to associate with a CTD kinase [11] and a dominant negative mutant of cdk9 (the catalytic subunit of pTEFb) was found to increase Tax transactivation of the HTLV-I promoter [12]. Therefore, there is the possibility that other kinase complexes (small vs. large pTEFb complex or other cdk kinases) may aid in increased Tax transactivation. In this context, HTLV-I infected cells contain increased levels of cyclin E/cdk2 kinase activity, through sequestration of cdk inhibitor, p21/waf1, by cyclin D2/cdk4 complexes [13,14]. This kinase complex was able to phosphorylate RNAP II CTD and antibodies against cyclin E co-immunoprecipitated only the phosphorylated form of RNAP II from HTLV-I infected cells. Thus, if only indirectly, Tax may increase kinase activity resulting in enhanced CTD phosphorylation for steps following initiation, such as promoter clearance and/or elongation. Processive elongation is highly dependent on remodeling of chromatin structure [1,10]. A study by Corey et al. [15] demonstrated that disruption of SWI/SNF recruitment by an activator resulted in lack of chromatin remodeling, transcription elongation, and production of full-length hsp70 mRNA. Tax has been shown to associate with BRG1 components of the ATP-dependent chromatin remodeling complex, SWI/SNF, and increase Tax transactivation [16]. Disruption of BRG1 by siRNA led to a decrease in Tax transactivation. Therefore, Tax may target SWI/SNF complexes downstream of RNAP II in order to prevent stalling of RNAP II. This raises a number of questions such as does Tax bind to an elongating RNAP II complex? Does Tax help to recruit elongation factors, such as TFIIS or TFIIF? Finally, it should be emphasized that each stage of transcription is not an independent process; coupling of the transcriptional and RNA processing machinery is thought to increase the rate and specificity of these enzymatic reactions [1]. As shown in Figure 1A, acetylation of nucleosomes and other transcription factors/coactivators promote an open complex structure and RNAP II holoenzyme assembly. Initiation by Tax is dependent on the recruitment of CBP/p300 and p/CAF by transcription factor/Tax complex at the 21-bp repeats (viral CRE elements). Phosphorylation of RNAP II CTD is important for loading of the 5' capping machinery to allow for rapid capping of nascent pre-mRNA, ensuring protection for the transcript from degradation. During promoter clearance (early elongation), site specific phosphorylation of the CTD is modified to allow for sequestration of splicing machinery and elongation factors, and release of the capping machinery. Assembly of SWI/SNF factors with Tax downstream of the elongation phase RNAP II complex remodels chromatin structure, promoting RNAP II processivity. Thus, the presence of Tax for initiation and possibly promoter clearance and/or elongation will help to increase viral transcription and mRNA processing overall (Figure 1B). While the results by Ching et al. are preliminary at this time, Tax transactivation post-initiation is indeed a novel concept. Further detailed analysis of Tax at both the LTR of HTLV-I and downstream of this region will help to resolve many of these questions and provide important insight into the transcription field. Figure 1 Effect of Tax on transcription. A) Schematic representation of proximal promoter of HTLV-I. Tax binding to CBP/p300 with either p/CAF or bZIP transcription factors (e.g. CREB1) leads to increased acetylation and interaction with the basal transcription machinery. Tax binding to SWI/SNF downstream of start site may help to remodel restrictive chromatin structure and aid in promoter clearance and elongation. B) The possible effect of Tax on gene expression network. The sequential steps of transcription (initiation, elongation, and termination) are intricately linked together and to mRNA processing and export (adapted from ref. 1). Thus, the effect of Tax on initiation and possibly elongation (both early promoter clearance and processive elongation events) would contribute, albeit indirectly, to RNA processing and export. Abbreviations HTLV-I, human T cell leukemia virus, type I CRE, cAMP response element CREB, cAMP response element binding protein ChIP, chromatin immunoprecipitation RNAP II, RNA polymerase II CTD, C-terminal domain HIV-1, human immunodeficiency virus, type 1 LTR, long terminal repeat TBP, TATA binding protein TxREs, Tax-responsive elements GTFs, general transcription factors TAR, transactivation region Competing Interests None declared. Authors' contributions Both authors contributed equally to the structure and content of the manuscript. ==== Refs Maniatis T Reed R An extensive network of coupling among gene expression machines Nature 2002 416 499 506 11932736 10.1038/416499a Ching YP Chun AC Chin KT Zhang ZQ Jeang KT Jin DY Specific TATAA and bZIP requirements suggest that HTLV-I Tax has transcriptional activity subsequent to the assembly of an initiation complex Retrovirology 2004 1 18 15285791 Reddy TR Tang H Li X Wong-Staal F Functional interaction of the HTLV-1 transactivator Tax with activating transcription factor-4 (ATF4) Oncogene 1997 14 2785 2792 9190894 10.1038/sj.onc.1201119 Gachon F Peleraux A Thebault S Dick J Lemasson I Devaux C Mesnard JM CREB-2, a cellular CRE-dependent transcription repressor, functions in association with Tax as an activator of the human T-cell leukemia virus type 1 promoter J Virol 1998 72 8332 8337 9733879 Gachon F Thebault S Peleraux A Devaux C Mesnard JM Molecular interactions involved in the transactivation of the human T-cell leukemia virus type 1 promoter mediated by Tax and CREB-2 (ATF-4) Mol Cell Biol 2000 20 3470 3481 10779337 10.1128/MCB.20.10.3470-3481.2000 Lemasson I Polakowski NJ Laybourn PJ Nyborg JK Transcription Factor Binding and Histone Modifications on the Integrated Proviral Promoter in Human T-cell Leukemia Virus-I-infected T-cells J Biol Chem 2002 277 49459 49465 12386157 10.1074/jbc.M209566200 Lemasson I Polakowski NJ Laybourn PJ Nyborg JK Transcription regulatory complexes bind the human T-cell leukemia virus 5' and 3' long terminal repeats to control gene expression Mol Cell Biol 2004 24 6117 6126 15226416 10.1128/MCB.24.14.6117-6126.2004 Basbous J Arpin C Gaudray G Piechaczyk M Devaux C Mesnard JM The HBZ factor of human T-cell leukemia virus type I dimerizes with transcription factors JunB and c-Jun and modulates their transcriptional activity J Biol Chem 2003 278 43620 43627 12937177 10.1074/jbc.M307275200 Kao SY Calman AF Luciw PA Peterlin BM Anti-termination of transcription within the long terminal repeat of HIV-1 by tat gene product Nature 1987 330 489 493 2825027 10.1038/330489a0 Arndt KM Kane CM Running with RNA polymerase: eukaryotic transcript elongation Trends Genet 2003 19 543 550 14550628 10.1016/j.tig.2003.08.008 Chun RF Jeang KT Requirements for RNA polymerase II carboxyl-terminal domain for activated transcription of human retroviruses human T-cell lymphotropic virus I and HIV-1 J Biol Chem 1996 271 27888 27894 8910388 10.1074/jbc.271.44.27888 Gold MO Yang X Herrmann CH Rice AP PITALRE, the catalytic subunit of TAK, is required for human immunodeficiency virus Tat transactivation in vivo J Virol 1998 72 4448 4453 9557739 Wang L Deng L Wu K de la Fuente C Wang D Kehn K Maddukuri A Baylor S Santiago F Agbottah E Trigon S Morange M Mahieux R Kashanchi F Inhibition of HTLV-1 transcription by cyclin dependent kinase inhibitors Mol Cell Biochem 2002 237 137 153 12236581 10.1023/A:1016555821581 Kehn K Deng L De La Fuente C Strouss K Wu K Maddukuri A Baylor S Rufner R Pumfery A Bottazzi ME Kashanchi F The role of cyclin D2 and p21/waf1 in human T-cell leukemia virus type 1 infected cells Retrovirology 2004 1 6 15169570 10.1186/1742-4690-1-6 Corey LL Weirich CS Benjamin IJ Kingston RE Localized recruitment of a chromatin-remodeling activity by an activator in vivo drives transcriptional elongation Genes Dev 2003 17 1392 1401 12782657 10.1101/gad.1071803 Wu K Bottazzi ME de la Fuente C Deng L Gitlin SD Maddukuri A Dadgar S Li H Vertes A Pumfery A Kashanchi F Protein profile of tax-associated complexes J Biol Chem 2004 279 495 508 14530271 10.1074/jbc.M310069200

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Retrovirology. 2004 Jul 30; 1:19

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==== Front BMC BioinformaticsBMC Bioinformatics1471-2105BioMed Central London 1471-2105-5-1001527293610.1186/1471-2105-5-100Methodology ArticleGraph-based iterative Group Analysis enhances microarray interpretation Breitling Rainer 12r.breitling@bio.gla.ac.ukAmtmann Anna 1a.amtmann@bio.gla.ac.ukHerzyk Pawel 23p.herzyk@bio.gla.ac.uk1 Plant Science Group, Institute of Biomedical and Life Sciences, University of Glasgow, Glasgow G12 8QQ, United Kingdom2 Bioinformatics Research Centre, Department of Computing Science, University of Glasgow, Glasgow G12 8QQ, United Kingdom3 Sir Henry Wellcome Functional Genomics Facility, Institute of Biomedical and Life Sciences, University of Glasgow, Glasgow G12 8QQ, United Kingdom2004 23 7 2004 5 100 100 27 4 2004 23 7 2004 Copyright © 2004 Breitling et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background One of the most time-consuming tasks after performing a gene expression experiment is the biological interpretation of the results by identifying physiologically important associations between the differentially expressed genes. A large part of the relevant functional evidence can be represented in the form of graphs, e.g. metabolic and signaling pathways, protein interaction maps, shared GeneOntology annotations, or literature co-citation relations. Such graphs are easily constructed from available genome annotation data. The problem of biological interpretation can then be described as identifying the subgraphs showing the most significant patterns of gene expression. We applied a graph-based extension of our iterative Group Analysis (iGA) approach to obtain a statistically rigorous identification of the subgraphs of interest in any evidence graph. Results We validated the Graph-based iterative Group Analysis (GiGA) by applying it to the classic yeast diauxic shift experiment of DeRisi et al., using GeneOntology and metabolic network information. GiGA reliably identified and summarized all the biological processes discussed in the original publication. Visualization of the detected subgraphs allowed the convenient exploration of the results. The method also identified several processes that were not presented in the original paper but are of obvious relevance to the yeast starvation response. Conclusions GiGA provides a fast and flexible delimitation of the most interesting areas in a microarray experiment, and leads to a considerable speed-up and improvement of the interpretation process. ==== Body Background Microarray experiments can provide a comprehensive picture of gene expression levels in biological samples. In a typical application they compare expression of several thousand genes under two different conditions (e.g. healthy vs. diseased tissue, wild type vs. mutant animals, drug-treated vs. control cells), using a small number of replicate experiments. Various techniques have been developed to rank genes according to their expression changes, e.g. based on the t-statistic [1] or the strong non-parametric RankProducts [2]. The resulting list of genes can then be restricted to those genes that fulfill a certain statistical criterion, usually an arbitrarily chosen maximum accepted false discovery rate. The main challenge to the biologist is contained in the next step of the analysis. It consists in identifying the biologically relevant expression changes, the "big picture" of the experiment. As microarray experiments tend to generate unexpected observations in areas outside the specialized expertise of the experimentalist, this can be quite difficult and time-consuming. A principled mechanism to identify the significant higher-level features of the experimental results would therefore be very useful. The biological interpretation process consists to a large extent of finding evidence connecting certain genes that are differentially expressed. This evidence can consist, e.g., of joint participation in some physiological process, physical interaction at the protein level, reported co-expression in earlier microarray experiments, a shared functional annotation, etc. This kind of evidence can intuitively be represented as a graph, and this feature is regularly used to visualize biological data, in the form of metabolic or signaling pathways or protein interaction maps. The task can then be described as the identification of subgraphs that as a whole show a statistically significant expression change. This would allow the biologist to focus her analysis on the most promising areas, without prior bias, while at the same time presenting the relevant evidence underlying each association for critical evaluation. Results and Discussion The Algorithm We have recently developed an approach, iterative Group Analysis (iGA) that identifies significantly changed functional classes of genes in a microarray experiment [3]. In contrast to similar approaches such as [4-8], the iGA method does not require a previous delimitation of a set of "differentially expressed genes", but uses an iterative calculation of p-values to determine the subset of class members that is most likely to be changed. Due to this feature, the iGA method is more sensitive in identifying functional classes that are slightly but consistently regulated, and works well on noisy data with small numbers of replicates, where the delimitation of gene lists can be overly restrictive. Here we extend this approach to the analysis of "evidence graphs", which offers much larger flexibility of the annotations that can be used and allows substantially improved visualization. Evidence graphs can be represented as bigraphs with two types of nodes, one for genes and one for the associated "evidence" (Fig. 1A). For evaluation purposes we focused on two types of networks, one where the evidence consists of GeneOntology annotations (GO network) and one where the evidence comprises enzyme substrates (metabolic network). The construction of these networks from gene annotation files is fast and simple, but more unconventional networks are also straightforward (e.g. regulatory networks inferred from previous gene expression experiments, or "literature networks" based on co-occurrence of genes in publications). Before the calculation the bigraph is converted to a simple graph, eliminating the evidence nodes and introducing pairwise edges between all nodes that were connected to a common evidence node (Fig. 1B). In addition to the graph, a complete list of genes sorted by differential expression is provided. All nodes without corresponding expression data are eliminated from the network. In the first step of the analysis, each gene node is assigned its rank in the list of genes, such that the node for the most strongly changed gene is labeled "1" (Fig. 1C), the second most changed gene is labeled "2", etc. Then, local minima are identified in the graph, i.e. those nodes that have a lower rank than all their direct neighbors in the graph (Fig. 1D). In the next step, subgraphs are iteratively extended from each of those local minima by including the neighboring node with the next highest rank (m) and, if present, all adjacent nodes of ranks equal or smaller than m. Hence, at each step of the extension process the newly extended subgraph is not adjacent to any outside node with a rank lower than m (Fig. 1E,1F,1G,1H). At each extension step we thus obtain a subgraph with n members with a maximum rank m and can calculate the p-value for observing all n of n genes at rank m or better in a list of N total genes in the graph, , which follows easily from inserting these values in the cumulative hypergeometric equation, which is also used for iGA [3]. The extension process is continued until all nodes reachable from the local minimum are included or the subgraph reaches an arbitrary maximum size. After extending the subgraphs, for each local minimum the subgraph yielding the smallest p-value is selected as its "regulated neighborhood" and all local minima are sorted by increasing p-value of these regulated neighborhoods. The subgraphs at the top positions of the resulting list should contain the most relevant regions of the total evidence network. Comparison with Previous Approaches The method devised by Ideker et al. [9] for the determination of signaling and regulation circuits from a combination of protein interaction information and expression data could easily be extended to cover the more general case of microarray interpretation addressed by GiGA. This would only require the extension of "interaction" to include, e.g., participation in a shared cellular process or shared functional annotation. Their approach uses aggregate z-scores to evaluate the quality of each subgraph. This requires a relatively complex parameter estimation procedure followed by simulated annealing. In contrast, the rank-transform of the data that is the basis of GiGA allows non-parametric p-value calculations and is thus much faster (and computationally less demanding) than the method described by Ideker et al. A disadvantage of both methods is that they both do not guarantee to find the optimally scoring subgraph. The recently released commercial Pathway Analysis software from Ingenuity Systems seems to be based on a similar concept as GiGA, i.e. the determination of regulated subgraphs in annotation networks. However, it just classifies genes as changed ("focus genes") or unchanged based on an arbitrary selected significance cut-off and thus discards most of the relative-change information (gene ranks) used by GiGA . Therefore, this method is difficult to apply to very noisy or unreplicated experiments where a reliable delimitation of the "changed" genes becomes impossible. Experimental Case Study To validate the GiGA approach, we used the yeast diauxic shift experiment by DeRisi et al. [10]. In this classical study the authors examined the response of yeast cells to glucose depletion in the growth medium. As the biology of this process is extremely well understood and the functional annotation of the yeast genome is very comprehensive, we could use this dataset to test the ability (and reliability) of GiGA to identify the relevant subgraphs of interest. In their original publication, DeRisi et al. highlight the following changes during starvation: Rechanneling of metabolites into the tricarboxylic acid (TCA) and glyoxylate cycle, increase in aerobic respiration (cytochrome c oxidase and reductase), gluconeogenesis, and carbohydrate storage (glycogen and trehalose biosynthesis). In contrast, 95% of ribosomal proteins, as well as tRNA synthetases and translation elongation/initiation factors were strongly down-regulated. Twenty hours after the initial inoculation of the sample about 20% of all genes showed at least a two-fold change in expression. Table 1 and 2 show the result of an iterative Group Analysis of these expression data. Seven time points after inoculation were examined. Significant expression changes become apparent at 13.5 hours. It can be seen that all the processes identified manually by DeRisi et al. are already apparent at this level of analysis. In addition, iGA highlights the up-regulation of sugar transporters at the early stages of starvation, obviously a desperate attempt by the cells to take up the last remaining sugars from the medium. It also highlights the induction of heat shock proteins and the repression of ribosome biosynthesis processes in the nucleolus, which were not discussed in the original paper. What is missing in these lists, however, is the automatic identification of the interrelationships between the identified processes, which would be particularly informative in more realistic applications with a less well understood biology. This connectivity between genes and functional classes is provided by GiGA. Table 3 summarizes the results for the 20.5 hour time point, using two different networks, one for GeneOntology classes, and one for enzyme substrates, extracted from the SwissProt catalytic activity descriptors of yeast proteins. For both up- and down-regulated genes, the most significant subgraph is widely separated from the next best one, contains the largest number of genes, and comprises almost all the processes detected by iGA and the original authors. (We here restricted the size of subgraphs to a maximum of 40 genes to keep navigation of the results simple.) Figures 2 and 3 show the automatically generated visualization of the corresponding most significant subgraphs and the associated annotation. It is obvious how GiGA highlights the functional connections between different enzymes. In Fig. 2, the association between small and large ribosomal subunits, nucleolar rRNA processing and translational elongation is faithfully reconstructed. In Fig. 3, which uses the enzyme substrate network (which we considered to be more challenging for the algorithm), the interplay between the TCA cycle, the overlapping glyoxylate cycle, and all the relevant protein complexes of the respiratory chain are readily apparent. The agreement with the manual interpretation by DeRisi et al. extends down to the single gene level, while at the same time adding additional, obviously relevant connections, e.g. from the TCA cycle to the ATP synthase complex. Fig. 3 also shows the second best subgraph, which contains the cytochrome c oxidase subunits together with two catalase genes that may be involved in the detoxification of the hydrogen peroxide generated by the respiratory burst induced by starvation. The performance of GiGA (as well as iGA) is best appreciated when compared to the results of an extensive expert interpretation of the same data. Table 1 to 3, and Fig. 2 and 3 show how both techniques succeed in detecting and condensing exactly the genes and processes that were considered relevant by the expert biologists when first interpreting the same data [10]. GiGA effectively summarizes the original publication in three subgraph pictures (Fig. 2 and 3). This is even more astonishing when considering that these results are achieved for each single time-point separately (see, e.g., Tab. 1 and 2). This reveals the stability of the approach towards the measurement variance inherent in any unreplicated microarray experiment. It is important to be aware that each of the highlighted subgraphs has to be carefully evaluated for its biological relevance. On the one hand, the sheer number of possible subgraphs in an evidence network creates a major multiple-testing problem, which means that some of the detected associations may be due to chance. Random permutations of the expression data – which can be generated by the GiGA software – can give an idea of the expected false-discovery rate. On the other hand, functional annotations are at present notoriously unreliable and spurious edges may affect the details of the results. Also, not all genes within a detected subgraph will necessarily show a strong expression change, because sometimes less strongly affected genes may connect those genes that do change. Such a relation is for example expected for many transcription factors and their targets [9]. Nonetheless, GiGA is able to direct the user to the most interesting areas in the evidence network. The GiGA method is not restricted to use with exhaustively annotated genomes. It can work on a wide variety of "evidence" to build the necessary network, including hypothetical predicted functions or associations. It is even possible to apply GiGA to metabolomics results, which are characterized by the absence of any significant amount of annotation – usually only exact molecular masses and their differential abundance are known. In that case, an evidence network can be built from the measured masses themselves, linking compounds m1 and m2 whenever their mass difference (Δm = |m1 - m2|) can be explained by a common biochemical transformation (e.g. dehydrogenation: Δm = 2* mass(hydrogen)). The set of relevant transformations can easily be collected from any biochemistry textbook. In addition, one can introduce edges for condensation reactions between observed masses, i.e. if m1 + m2 = m3 + mass(H2O) then edges between m1 and m3, and m2 and m3 are added to the evidence network. We are currently developing the application of GiGA to this kind of data in the Sir Henry Wellcome Functional Genomics Facility at the University of Glasgow ; data not shown). Conclusions The present analysis of a biologically well-understood test case demonstrates the reliable performance of GiGA. The method automatically identifies all relevant physiological processes, puts them into context, summarizes them in an intuitive format, and associates them with the underlying evidence (Fig. 2 and 3). It can be applied to experiments with very small numbers of replicates (a single time point in the diauxic shift test case) and can be used with any available functional annotation, including protein interaction networks, co-expression data or literature mining results, as well as in areas beyond microarray analysis. For visualization, we have used the graph-layout software aiSee, but output files suitable for a variety of graphical tools can easily be generated by slight modifications in the implementation. GiGA can be used as a stand-alone tool, but we expect that it will be most useful when integrated into existing microarray analysis software, and for that reason the GiGA algorithm is freely available without restrictions. Methods Yeast gene expression data for the diauxic shift experiment were obtained from the Stanford Microarray Database . GeneOntology annotations were obtained from Affymetrix . The enzyme substrate networks were built based on information contained in the annotation of the yeast proteome in the SwissProt database . The GiGA algorithm has been implemented as a Perl script and compiled as a Windows command line executable. These files are available (together with a manual and example files) as Additional files 1 to 8. Authors' contributions RB devised and implemented the GiGA technique and drafted the manuscript. AA and PH supervised the project. All authors read and approved the final manuscript. Supplementary Material Additional File 1 GiGA program. For use from the Windows command line. Click here for file Additional File 2 GiGA source code. Click here for file Additional File 3 GiGA manual. Describes the use of GiGA applied to the example data (Additional files 4 to 6). Click here for file Additional File 4 Gene expression data. Sorted list of genes, based on expression during the yeast diauxic shift. Click here for file Additional File 5 Evidence network. List of gene pairs connecting genes whenever their gene products are enzymes that share a common substrate. Based on annotation derived from SwissProt. Click here for file Additional File 6 Genenames file. Contains descriptive names of the yeast genes contained in Additional file 4. Click here for file Additional File 7 Example output in text format. List of significantly affected subgraphs detected in the experimental data (Additional file 4) using GiGA with default settings. Click here for file Additional File 8 Example output in graph-description language format. Contains the same results as Additional file 7, but in a format that can be visualized and explored using graph-layout software, e.g. aiSee, which is freely available for academics at . Click here for file Acknowledgements We thank Dr. Mike Barrett for stimulating discussions on the application of GiGA to metabolomics data. We also thank the referees for their very constructive evaluation of the software. This work was supported by BBSRC grants 17/GG17989 and 17/P17237. Figures and Tables Figure 1 Principle of Graph-based Iterative Group Analysis. A Evidence network. Genes are associated with their annotation in the form of a bigraph (two types of nodes). B The same evidence represented as a simple network. Genes that share an annotation are connected. C-H Example of a GiGA analysis using fictitious microarray results. C Genes are assigned their ranks based on observed expression changes. D Local minima are found, i.e. genes that have no connection to genes with a better rank. E-H Iterative expansion of subgraphs from one of the local minima, gene 2 (rank 1). E The neighboring node with the smallest rank is included (gene 4, rank 4), which leads to the additional inclusion of genes 5 (rank 3) and 6 (rank 2). F Gene 3 (rank 5) is included). G Gene 7 (rank 7) is included, leading to the inclusion of gene 8 (rank 6). H The last gene reachable from this local minimum, gene 1 (rank 8), is included and the process terminates. For each of the subgraphs a p-value can be calculated (see text) and the subgraph with the smallest p-value is declared the "regulated neighborhood" of the local minimum. In the example, genes 2, 4, 5, and 6 form a regulated neighborhood (p = 0.014). The graph expansion process would then be repeated for the remaining two local minima. Figure 2 Visualization of the most significant "down-regulated neighborhood" identified by GiGA using a GeneOntology-based network. The expression data are taken from the 20.5 h timepoint of the yeast diauxic shift (DeRisi et al., 1997). The layout was generated from the output of GiGA by the free software aiSee using a force-directed algorithm with default parameters. The same software can also be used for the versatile real-time navigation of the network. Colored boxes show the regulated genes (darker shading indicates stronger regulation), white boxes show the evidence linking the genes (in this case GeneOntology numbers and terms). Several important components of this regulatory neighborhood are indicated (small and large ribosomal subunit proteins, rRNA processing/snRNP, nucleolar proteins, translation elongation factors). These components were also identified in the original publication after manual analysis. GiGA finds them automatically, and also detects the – biologically obvious – connections between them. As all the evidence is included in the same picture, the biologist can then use her expertise to assess the relevance of each link, without having to make the connections ad hoc by tedious literature studies. Figure 3 Visualization of the two most significant "up-regulated neighborhoods" identified by GiGA using a metabolic network derived from Swissprot annotations. The expression data are taken from the 20.5 h timepoint of the yeast diauxic shift (DeRisi et al., 1997). The layout was generated as in Fig 2. Colored boxes show the regulated genes (darker shading indicates stronger regulation), white boxes show the substrates that are in common between genes. Important components of this regulatory neighborhood are indicated (TCA cycle and glyoxylate cycle enzymes, and the various respiratory chain complexes). Here it can be seen that GiGA not only detects protein complexes (such as ribosomes or the respiratory chain complexes), but also "linear" metabolic pathways such as TCA cycle and glyoxylate cycle (and potentially signal transduction pathways or regulatory cascades etc.). Almost all the enzymes discussed by DeRisi et al. (1997) are included in these two subgraphs, plus the relevant enzymatic information necessary to assess the relevance of each link, without the danger of missing some genes (unless the annotation is incomplete). Table 1 Iterative Group Analysis of gene expression during the yeast diauxic shift. Up-regulated groups. 0 h 9.5 h 11.5 h 13.5 h 15.5 h 18.5 h 20.5 h 6144 – purine base metabolism 6099 – tricarboxylic acid cycle 6099 – tricarboxylic acid cycle 3773 – heat shock protein activity 6099 – tricarboxylic acid cycle 9277 – cell wall (sensu Fungi) 3773 – heat shock protein activity 5749 – respiratory chain complex II (sensu Eukarya) 6099 – tricarboxylic acid cycle 3773 – heat shock protein activity 297 – spermine transporter activity 6950 – response to stress 6121 – oxidative phosphorylation, succinate to ubiquinone 5977 – glycogen metabolism 5749 – respiratory chain complex II (sensu Eukarya) 15846 – polyamine transport 297 – spermine transporter activity 8177 – succinate dehydrogenase (ubiquinone) activity 6950 – response to stress 6121 – oxidative phosphorylation, succinate to ubiquinone 4373 – glycogen (starch) synthase activity 3773 – heat shock protein activity 4373 – glycogen (starch) synthase activity 8177 – succinate dehydrogenase (ubiquinone) activity 15846 – polyamine transport 4373 – glycogen (starch) synthase activity 4129 – cytochrome c oxidase activity 6537 – glutamate biosynthesis 5353 – fructose transporter activity 7039 – vacuolar protein catabolism 5751 – respiratory chain complex IV (sensu Eukarya) 6097 – glyoxylate cycle 15578 – mannose transporter activity 6950 – response to stress 5749 – respiratory chain complex II (sensu Eukarya) 5750 – respiratory chain complex III (sensu Eukarya) 7039 – vacuolar protein catabolism 4129 – cytochrome c oxidase activity 6121 – oxidative phosphorylation, succinate to ubiquinone 9060 – aerobic respiration 8645 – hexose transport 5751 – respiratory chain complex IV (sensu Eukarya) 8177 – succinate dehydrogenase (ubiquinone) activity 4129 – cytochrome c oxidase activity 4396 – hexokinase activity 4396 – hexokinase activity 30162 – regulation of proteolysis and peptidolysis 5751 – respiratory chain complex IV (sensu Eukarya) 5215 – transporter activity 297 – spermine transporter activity 4364 – glutathione transferase activity 16491 – oxidoreductase activity 5977 – glycogen metabolism 6101 – citrate metabolism For this analysis, genes were assigned to groups based on GeneOntology annotations obtained from Affymetrix . All groups that are changed with a minimal p-value smaller than 1/ [number of annotated genes] (1/4087 = 2.4E-4) are shown, sorted by significance. Numbers and names are the standardized GeneOntology identifiers. Groups shown in bold were also reported as changed in the original publication (DeRisi et al., 1997) Up-regulated groups Table 2 Iterative Group Analysis of gene expression during the yeast diauxic shift. 0 h 9.5 h 11.5 h 13.5 h 15.5 h 18.5 h 20.5 h 7152 – spore wall assembly (sensu Saccharomyces) 5730 – nucleolus 30490 – processing of 20S pre-rRNA 5843 – cytosolic small ribosomal subunit (sensu Eukarya) 30490 – processing of 20S pre-rRNA 5732 – small nucleolar ribonucleoprotein complex 5842 – cytosolic large ribosomal subunit (sensu Eukarya) 7046 – ribosome biogenesis 5730 – nucleolus 30490 – processing of 20S pre-rRNA 30515 – snoRNA binding 42273 – ribosomal large subunit biogenesis 5730 – nucleolus 5842 – cytosolic large ribosomal subunit (sensu Eukarya) 6414 – translational elongation 30515 – snoRNA binding 5732 – small nucleolar ribonucleoprotein complex 3938 – IMP dehydrogenase activity 27 – ribosomal large subunit assembly and maintenance 6183 – GTP biosynthesis 42273 – ribosomal large subunit biogenesis 154 – rRNA modification 30515 – snoRNA binding 3723 – RNA binding 154 – rRNA modification Down-regulated groups. See Table 1 for details. Down-regulated groups. Table 3 Graph-based iterative Group Analysis of gene expression during the yeast diauxic shift. Down-regulated genes using GeneOntology-based network anchor locus group description minimal p-value E-value N max. rank YHL015W ribosomal proteins and rRNA processing 5.87E-86 <0.01 39 48 YMR217W amino acid and nucleotide biosynthesis 3.38E-13 2.7 9 172 YDR144C cell wall biogenesis 4.06E-08 4.5 6 242 YNL065W membrane transporter 4.02E-05 9.3 3 141 YLR062C bud site selection 6.41E-05 9.9 4 367 YGL225W protein glycosylation in Golgi 1.12E-04 10.8 4 422 YPR074C pentose phosphate pathway 1.44E-04 11.2 4 449 total genes measured in network: 4087. Down-regulated genes using metabolic network anchor locus group description minimal p-value E-value N max. rank YNL141W nucleotide and amino acid biosynthesis, tRNA synthetases 4.67E-59 <0.01 39 45 YOR224C RNA polymerases 2.59E-13 1.1 23 219 total genes measured in network: 744. Up-regulated genes using GeneOntology-based network anchor locus group description minimal p-value E-value N max. rank YER065C TCA and glyoxylate cycle, respiratory chain 8.57E-77 <0.01 39 66 YKL217W membrane transporters (sugar, amino acids) 1.76E-15 2.3 8 62 YAL017W protein kinases 1.07E-07 4.8 6 284 YBL043W cell wall biogenesis 3.81E-07 5.4 4 103 YGR248W carbohydrate metabolism 5.66E-07 5.5 5 232 YEL011W glycogen metabolism 1.01E-06 5.8 3 42 YER037W protein phosphatases 1.07E-06 5.8 8 736 YJL137C glycogen biosynthesis 7.46E-06 7.3 4 215 YDL085W disulfide oxidoreductases 1.05E-05 7.6 4 234 YNL173C mating signal transduction 1.65E-05 8.2 4 262 YNL134C alcohol dehydrogenase 1.34E-04 11.1 3 210 YBL038W mitochondrial large ribosomal subunit 1.99E-04 11.9 4 487 total genes measured in network: 4087. Up-regulated genes using metabolic network anchor locus group description minimal p-value E-value N max. rank YER065C TCA and glyoxylate cycle, respiratory chain 4.96E-53 0.11 39 54 YGR088W cytochrome c oxidase 3.09E-10 1.2 11 106 YFR015C glycogen synthases 2.08E-04 3.6 3 45 YJR073C methyltransferases 3.85E-04 4.0 5 156 YDR001C trehalases 5.01E-04 4.2 3 60 YCR014C DNA and RNA polymerases 5.44E-04 4.2 17 481 YIR038C glyoxalases 8.64E-04 4.5 5 183 total genes measured in network: 744. The evidence network was constructed either from GeneOntology information (nodes are connected if they share a GeneOntology annotation) or from enzyme activity information obtained from Swissprot . In the latter case, genes are connected if their encoded proteins convert the same substrate (as product or educt, i.e. the direction of the reaction is not taken into account here). This type of network is much smaller (only 744 genes), as only genes coding for enzymes are included. All groups that are changed with a minimal p-value smaller than 1/[number of annotated genes] are shown, sorted by significance. The corresponding E-value as estimated by the analysis of 100 random permutations of the data is also shown. The employed threshold for inclusion in the table is very generous and does not guarantee that all subgraphs shown are statistically significant. The local minimum anchoring each regulated neighborhood is indicated by its genetic locus name (for overlapping neighborhoods, only the best-ranking minimum is shown). Descriptive group names were added manually. Groups that correspond to processes discussed in the original paper are highlighted in italics. It can be seen that the highest ranking group in each case is the largest and contains the central biological processes detected by DeRisi et al. (1997) and by iGA (see Table 1 and 2). N, number of genes in each subgraph. ==== Refs Dudoit S Yang YH Callow MJ Speed TP Statistical methods for identifying differentially expressed genes in replicated cDNA microarray experiments Statistica Sinica 2002 12 111 139 Breitling R Armengaud P Amtmann A Herzyk P Rank products: A simple, yet powerful, new method to detect differentially regulated genes in replicated microarray experiments FEBS Letters Breitling R Amtmann A Herzyk P Iterative Group Analysis (iGA): A simple tool to enhance sensitivity and facilitate interpretation of microarray experiments BMC Bioinformatics 2004 5 34 15050037 10.1186/1471-2105-5-34 Doniger SW Salomonis N Dahlquist KD Vranizan K Lawlor SC Conklin BR MAPPFinder: using Gene Ontology and GenMAPP to create a global gene-expression profile from microarray data Genome Biol 2003 4 R7 12540299 10.1186/gb-2003-4-1-r7 Hosack DA Dennis G., Jr. Sherman BT Lane HC Lempicki RA Identifying biological themes within lists of genes with EASE Genome Biol 2003 4 R70 14519205 10.1186/gb-2003-4-10-r70 Kim CC Falkow S Significance analysis of lexical bias in microarray data BMC Bioinformatics 2003 4 12 12697067 10.1186/1471-2105-4-12 Provart NJ Zhu T A Browser-based Functional Classification SuperViewer for Arabidopsis Genomics Currents in Computational Molecular Biology 2003 2003 271 272 Zeeberg BR Feng W Wang G Wang MD Fojo AT Sunshine M Narasimhan S Kane DW Reinhold WC Lababidi S Bussey KJ Riss J Barrett JC Weinstein JN GoMiner: a resource for biological interpretation of genomic and proteomic data Genome Biol 2003 4 R28 12702209 10.1186/gb-2003-4-4-r28 Ideker T Ozier O Schwikowski B Siegel AF Discovering regulatory and signalling circuits in molecular interaction networks Bioinformatics 2002 18 S233 S240 12169552 DeRisi JL Iyer VR Brown PO Exploring the metabolic and genetic control of gene expression on a genomic scale Science 1997 278 680 686 9381177 10.1126/science.278.5338.680

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BMC Bioinformatics. 2004 Jul 23; 5:100

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==== Front BMC BioinformaticsBMC Bioinformatics1471-2105BioMed Central London 1471-2105-5-1021527968210.1186/1471-2105-5-102Methodology ArticleA computer simulation analysis of the accuracy of partial genome sequencing and restriction fragment analysis in estimating genetic relationships: an application to papillomavirus DNA sequences Qiao Baozhen 1qbaozhen@hotmail.comWeigel Ronald M 1weigel@uiuc.edu1 Division of Epidemiology and Preventive Medicine, Department of Veterinary Pathobiology, University of Illinois, Urbana, IL 61801 USA2004 27 7 2004 5 102 102 12 3 2004 27 7 2004 Copyright © 2004 Qiao and Weigel; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background Determination of genetic relatedness among microorganisms provides information necessary for making inferences regarding phylogeny. However, there is little information available on how well the genetic relationships inferred from different genotyping methods agree with true genetic relationships. In this report, two genotyping methods – restriction fragment analysis (RFA) and partial genome DNA sequencing – were each compared to complete DNA sequencing as the definitive standard for classification. Results Using the Genbank database, 16 different types or subtypes of papillomavirus were selected as study samples, because numerous complete genome sequences were available. RFA was achieved by computer-simulated digestion. The genetic similarity of samples, based on RFA, was determined from the proportion of fragments that matched in size. DNA sequences of four specific genes (E1, E6, E7, and L1), representing partial genome sequencing, were also selected for comparison to complete genome sequencing. Laboratory error was not taken into account. Evaluation of the correlation between genetic similarity matrices (Mantel's r) and comparisons of the structure of the derived dendrograms (partition metric) indicated that partial genome sequencing (for single genes) had higher agreement with complete genome sequencing, achieving a maximum Mantel's r = 0.97 and a minimum partition metric = 10. RFA had lower agreement, with a maximum Mantel's r = 0.60 and a minimum partition metric = 18. Conclusions This simulation indicated that for smaller genomes, such as papillomavirus, partial genome sequencing is superior to restriction fragment analysis in representing genetic relatedness among isolates. The generalizability of these results to larger genomes, as well as the impact of laboratory error, remains to be demonstrated. ==== Body Background Precise estimation of genetic relatedness between isolates of a microorganism is important for determination of phylogenetic relationships, which has important applications in studies of disease transmission [1,2]. The definitive standard for assessing genetic relatedness among organisms is the complete genome sequence of nucleotide bases [3]. However, nucleotide sequencing is expensive and time-consuming, thus, generally it is impractical for use in most investigations, particularly when a large number of samples is analyzed. Currently, one genotyping technique used frequently as an alternative to complete genome sequencing is restriction fragment analysis (RFA), in which restriction endonuclease enzymes cleave the genome at specific sites, producing DNA fragments that are then separated by size using electrophoresis [4]. The percentage of fragments matching in size has been commonly used as an index to represent the genetic similarity between samples [5,6]. The accuracy of RFA in determining the true genetic relationships can be influenced by several factors, including the number of restriction enzymes used, the specific enzymes selected for DNA digestion, and laboratory conditions [7-9]. Another common alternative to complete genome sequencing is partial genome sequencing, i.e., the nucleotide sequencing of a particular gene or segment of the genome [8,10]. The gene or genome segment is often targeted by polymerase chain reaction (PCR). Selection of an appropriate gene or region for analysis is critical for accurately representing phylogenetic relationships [11,12]. In a comparison of RFA and partial genome sequencing with respect to their similarity in interpreting a disease outbreak caused by pseudorbabies virus in a swine producing region in Illinois, USA, both genotyping methods generated similar conclusions about patterns of spread of the virus [13]. However, the accuracy of each genotyping method in representing the complete genome was not evaluated. Restriction fragment analysis detects genetic variation by surveying specific endonuclease restriction sites over the entire genome; in contrast, partial genome sequencing detects genetic variation by comparing nucleotide bases from a specific region of the genome. Each method detects a different dimension of genetic variation, and each can detect only a proportion of the genetic variation present in the entire genome. Therefore, it is important to determine which method, using partial information, provides a more accurate estimation of genetic relatedness. The primary purpose of this study was to compare both restriction fragment analysis and partial genome sequencing to complete genome sequencing, with regard to their agreement in estimating genetic relationships and in reconstructing phylogenies under the ideal conditions of absence of laboratory error. Computer simulation of the genotyping analysis was conducted, using completely sequenced papillomavirus isolates obtained from Genbank. Results Table 1 provides descriptive statistics on fragment size distributions for RFA (using the MaeI enzyme as an example) showing that a moderate number of fragments (mean > 20) were produced by simulated digestion. Fragment sizes were large (median ≈ 280 bps for example enzyme), with only 4 samples having one fragment each ≤ 20 bps. Table 2 shows that with an increase in the number of restriction enzymes, the correlation between the RFA and the complete genome sequencing genetic distance matrices increased slightly and the partition metric measuring dendrogram topological dissimilarity decreased slightly. The highest agreement with complete genome sequencing obtained for RFA was for a 4-enzyme combination, which achieved a maximum Mantel's r = 0.60 and minimum partition metric = 18. Table 3 shows that the similarity with complete genome sequencing in estimating genetic relatedness was much higher for partial genome sequencing, particularly for the E1 and L1 genes, which had the relatively longer sequences (averaging 24.2% and 19.6% of genome, respectively), although all genes selected had Mantel's r ≥ 0.88. The minimum value of the partition metric was 10, and the maximum value was 14, compared to a minimum of 18 for RFA. Phylogenetic trees are presented for complete genome sequencing (Fig. 1), RFA (the 4-enzyme condition with the highest agreement with complete genome sequencing) (Fig. 2), and sequencing of the E1 gene (the longest gene) (Fig. 3). Tree stability, as indicated by bootstrap values, was higher for complete genome sequencing (Fig. 1: all bootstrap values > 0.90) than for partial genome sequencing of the E1 gene (highest Mantel's r). However, the E1 gene tree structure for the most closely related samples was stable and nearly identical to complete genome sequencing. In contrast to the RFA example given (Fig. 2), which did not clearly differentiate the papillomavirus samples into subgroups, partial genome sequencing of the E1 gene identified 2 subgroups with the same composition (and BPV2 as an outlier) as did complete genome sequencing. Discussion Sequencing entire genomes is impractical in most investigations of genetic relationships. The computer simulation conducted here determined that compared to restriction fragment analysis, partial genome sequencing had higher agreement with complete genome sequencing in estimating genetic relatedness and greater similarity in the topology of the dendrograms of phylogenetic relationships derived from these estimates. These results using papallomavirus sequences with a genome length averaging less than 8 kb, indicate that for microorganisms with small genomes, partial genome sequencing targeting genes comprising approximately 20–25% of the total genome length can provide a very good estimate of genetic relatedness. The topological structure of phylogenetic trees was also stable for partial genome sequencing, particularly for the most closely related samples. The degree to which these results generalize to larger genomes is unknown, in part because microorganisms with large genomes are rarely, if ever, sequenced in their entirety. There are also other considerations in selecting partial genome sequencing as a genotyping method, such as presence of the gene in all isolates, and sufficient variability to differentiate isolates [12]. In addition, whether genetic variation is random or due to natural selection needs to be taken into account [14], because in the latter case genetic dissimilarity may not reflect time since divergence, thus making it more difficult to infer evolutionary relationships, which are important for making inferences about pathogen transmission. These limitations should be considered as well for restriction fragment analysis. One might expect that increasing genome size would diminish the advantage of partial genome sequencing compared to restriction fragment analysis. As total genome size increases, the number of restriction sites cut by restriction enzymes is expected to increase, providing more fragments and more genetic information for estimating genetic relatedness at no increased cost. This also needs to be taken into account in the selection of a genotyping method. However, it has been argued that if a gene is selectively neutral (i.e., variations are not subject to natural selection), it is only the length of the gene sequenced, not the ratio of sequenced gene length to genome size, that is important for determining the degree of divergence from a common ancestor [14]. To the extent that these conditions are satisfied, the results of this study indicate that specific gene sequencing is likely to provide a better estimate of genetic relationships than restriction fragment analysis of the complete genome under a wider variety of genome sizes. The general conditions under which partial genome sequencing is more accurate than restriction fragment analysis in representing true genetic relatedness have not been addressed in the analysis conducted here. However, another study from our laboratory [15], using simulated genomes of various size with different nucleotide substitution rates, and varying degrees of genetic diversity among samples, found that only under conditions of both short partial genome sequence length and low rates of nucleotide substitution did RFA provide a more accurate topological reconstruction of phylogenetic relationships than did partial genome sequencing; the degree of genetic diversity among samples did not affect the advantage partial genome sequencing had in accurately depicting phylogenetic relationships. Thus, whether one is investigating the genetic relatedness among samples collected from a single disease outbreak or a diverse collection of samples from different times and geographic regions, under most conditions partial genome sequencing will represent genetic relationships more accurately than does RFA. Genotyping using partial genome sequencing and phylogenetic reconstruction (using the neighbor-joining algorithm) have become standard for several virus species, including not only papillomavirus [16,17], but also human immunodeficiency virus [18], classical swine fever virus [19], porcine reproductive and respiratory syndrome virus [20], and foot-and-mouth disease virus [21]. The simulated genotyping conducted here assumed no error of measurement. The sources of error in restriction fragment analysis are well known [22-24]. Fragments of similar size in the same lane of a gel may be indistinguishable, thus appearing to form one fragment. Fragments of small size may be undetectable. The relationship between migration distances and fragment size may be affected by variation in gel density both between and within gels. There are also differences in measurement error between laboratories [25,26]. These deficiencies are accounted for by use of marker DNA fragments of known nucleotide base pair length to assist in estimating cleaved DNA fragment sizes; however, acknowledgement of remaining error of measurement of the size of detectable fragments is inherent in the application of a tolerance range for considering fragments of similar but different sizes as a "match" [27]. Laboratory error is also inherent in partial genome sequencing [28]. With the commonly used polymerase chain reaction (PCR) methodology for detection and amplification of genes for sequencing, there can be error in primer development because primer sites may not be specific to the gene sequences or too specific to demarcate all occurrences of the gene. Heterogeneity of amplified DNA, due to replication error, recombination, low primer specificity, or impurity of the template can result in a failure to produce consistent sequencing results. In the comparison of the degree of similarity of DNA sequences between samples, alignment of sequences with unequal sequence lengths due to deletion or duplication, or the management of inverted sequences presents additional challenges for estimating genetic similarity and phylogenetic affinity [14]. The relative magnitude of sources of error in RFA versus partial genome sequencing is unknown and, thus, the conclusions presented here are those based upon the assumption of the absence or minimization of laboratory error. In practical terms, laboratory error and cost need to be taken into account in the selection of a genotyping method. However, when the impact of these factors is minimized, the computer simulation analysis conducted here indicates that partial genome sequence becomes the preferred alternative for representing genetic relationships. Conclusions For small genomes, partial genome sequencing of target genes comprising 20–25% of the total genome provides a more accurate estimate of genetic relatedness and more accurate representation of evolutionary and transmission histories than does restriction fragment analysis and thus is indicated to be the preferred genotyping method for phylogenetic reconstruction under these conditions. The degree to which these results are generalizable to larger genomes and conditions of laboratory error remains to be determined. Methods Sample DNA sequences The source of information on nucleotide sequences was the Genbank database [29]. The organism selected for analysis was papallomavirus, for which a moderately large number of isolates with complete genome sequences was available. Human, bovine, canine, and chimpanzee papillomaviruses were considered. Among human papillomavirus (HPV) with complete genome sequencing available, 12 samples were selected at random: HPV 4, 6a, 6b, 20, 24, 49, 63, 13, 29, 32, 54, and 26. For bovine papillomavirus (BPV), complete genome sequences were available for BPV1, BPV2, and BPV4. Because the E1 gene of BPV1 (of interest for partial genome sequencing) could not be located, only BPV2 and BPV4 were chosen and included in the study. One type of canine oral papillomavirus (caninePV) and one type of common chimpanzee papillomavirus (chimPV) were available in the database, and these were chosen. Thus, a total of 16 types or subtypes of papillomaviruses that have been completely sequenced and stored in Genbank were used (Table 1). The complete DNA sequences of the 16 papillomavirus samples were aligned using ClustalW software [30]. The genetic distances among these sequences were then calculated using the Kimura correction [31,32]. Computer simulated restriction fragment analysis Restriction endonuclease enzymes Commonly used restriction endonuclease enzymes were selected [33], based on the following criteria: (1) Only enzymes with 4-base pair recognition sites were selected, in order to produce a sufficient number of fragments for analysis. (2) Among enzymes having the same recognition site, only one was selected. (3) For simplicity, enzymes with multiple recognition sites were excluded. Using these criteria, 15 restriction enzymes were included (AccII, AciI, AluI, BsuRI, CviRI, HapII, HhaI, MaeI, MaeI, MboI, MseI, NlaIII, RsaI, TaqI, TspEI). Digestion Simulated digestion of each papillomavirus DNA sample by each restriction enzyme was conducted using the DIGEST program [34]. The resulting restriction fragments for each sample were sorted by size (number of nucleotide base pairs). Calculation of genetic distances Based on the distribution of restriction fragment sizes, the genetic similarity between any two papillomavirus samples was calculated for each restriction enzyme using the Dice coefficient [5,6]: Sxy = 2nxy/(nx+ny), where nxy is the number of fragments matching in size for samples x and y, and nx and ny are the number of fragments in samples x and y, respectively. Then, Dxy = 1-Sxy was calculated as a distance measure. Pairwise distances between samples were computed for each individual enzyme. Also, pairwise distances were obtained for up to 4 enzymes, by using for each condition (2, 3, and 4 enzymes) the fragment size distributions for 30 randomly selected combinations of enzymes, and calculating the composite distance [35]. Partial genome sequence analysis The E1, E6, E7, and L1 genes, which have been of interest in studies of papillomavirus, were used for estimating genetic relatedness. The ClustalW program [30] was used for sequence alignment, and the genetic distances (with the Kimura correction) were calculated for each gene. Agreement between genotyping methods Correlation between distance matrices The matrix of genetic distances based on complete DNA sequences was considered the definitive standard. The genetic distance matrices based on RFA and partial genome sequencing were compared to complete genome sequencing by calculating Mantel's coefficient of correlation between matrices (Mantel's r) [36]. Comparison of phylogenetic trees The genetic distance matrices for RFA, partial genome sequencing, and complete genome sequencing were used to construct phylogenetic trees, using the Neighboring-joining algorithm [37], as implemented by MEGA software [38]. Trees were rooted at the midpoint between the most distantly related samples [39]. Bootstrap values indicating stability of tree topology were added to trees based on partial and complete genome sequencing [14]. The trees based on RFA and specific gene sequences were compared to the tree for complete genome sequencing, by using the COMPONENT software [40] to calculate the partition metric, which measures the difference in tree topology [41,42]. A lower value of partition metric indicates greater topological similarity. List of abbreviations bps: base pairs BPV: bovine papillomavirus caninePV: canine papillomavirus chimpPV: chimpanzee papillomavirus HPV: human papillomavirus kb: kilobase Mantel's r: Mantel's coefficient of correlation between matrices PCR: polymerase chain reaction RFA: restriction fragment analysis Authors's contributions BQ designed the investigation, collected the data, conducted the data analysis, and wrote the manuscript. RW identified the problem to be investigated, provided statistical guidance, assisted in interpretation of results, and edited the final drafts of the manuscript. Both authors read and approved the final manuscript. Figures and Tables Figure 1 Tree of phylogenetic relationships among Papillomavirus samples, based on complete genome sequences. Classification achieved using the Neighbor-joining algorithm. The tree was rooted at the midpoint between the most disparate samples. Numbers on branches indicate bootstrap values. Figure 2 Tree of phylogenetic relationships among Papillomavirus samples, based on restriction fragment analysis with four restriction enzymes. Classification achieved using the Neighbor-joining method. The tree was rooted at the midpoint between the most disparate samples. Figure 3 Tree of phylogenetic relationships among Papillomavirus samples, based on DNA sequencing of the E1 gene. Classification achieved using the Neighbor-joining method. The tree was rooted at the midpoint between the most disparate samples. Numbers on branches indicate bootstrap values. Table 1 Sequence lengths and fragment size distribution for papillomavirus samples obtained from Genbank Type of Papillomavirus Genbank Accession Number Length of Complete Genome (bps) Length of Genes (bps) Fragment Size Distribution (digested by MaeI enzyme1) E1 Gene E6 Gene E7 Gene L1 Gene Number of Fragments Median Fragment Size (bps) 5% Percentile (bps) 95% Percentile (bps) HPV4 X70827 7353 1800 422 303 1550 24 215 54 817 HPV6a L41216 8010 1886 452 297 1502 18 249 43 1151 HPV6b X00203 7902 1930 452 297 1502 17 207 47 1241 HPV20 U31778 7757 1818 497 309 1550 24 294 9 781 HPV24 U31782 7452 1824 422 291 1538 13 501 55 1354 HPV49 X74480 7560 1830 416 312 1529 18 232 24 1210 HPV63 X70828 7348 1857 425 267 1523 23 221 29 968 HPV13 X62843 7880 1941 452 306 1499 21 352 9 765 HPV29 U31784 7916 1983 446 273 1511 16 435 33 1003 HPV32 X74475 7961 1929 428 315 1511 21 276 36 881 HPV54 U37488 7759 1902 434 288 1493 28 158 20 815 HPV26 X74472 7855 1917 452 315 1511 20 341 47 877 BPV2 M20219 7937 1815 413 384 1493 27 204 17 809 BPV4 X05817 7265 1932 300 363 1562 19 323 31 750 CaninePV D55633 8607 1794 434 294 1511 24 303 24 715 ChimPV AF020905 7889 1947 458 300 1505 18 236 35 1504 Mean 7778.1 1881.6 431.4 307.1 1518.1 20.7 284.1 32.2 977.5 1: Data reported for MaeI as an example. Table 2 Similarity of restriction fragment analysis to complete genome sequencing in estimating genetic relatedness between papillomavirus samples Number of Enzymes Mantel's r Partition Metric Mean Standard Deviation Maximum Mean Standard Deviation Minimum 1 0.37 0.13 0.54 23.33 1.23 20 2 0.42 0.09 0.55 22.60 1.19 20 3 0.46 0.08 0.58 22.07 1.44 20 4 0.49 0.08 0.60 21.40 1.44 18 Mantel's r is the correlation between matrices of genetic similarity. The partition metric indicates topological similarity of dendrograms, with lower values indicating greater similarity. Table 3 Similarity of partial genome sequencing to complete genome sequencing in estimating genetic relatedness between papillomavirus samples Gene Mantel's Correlation Coefficient Partition Metric E1 0.97 12 E6 0.92 10 E7 0.88 14 L1 0.96 12 Mantel's r is the correlation between matrices of genetic similarity. The partition metric indicates topological similarity of dendrograms, with lower values indicating greater similarity. ==== Refs Tenover FC Arbeit RD Goering RV Mickelsen PA Murray BE Persing DH Swaminathan B Interpreting chromosomal DNA restriction patterns produced by pulse-field gel electrophoresis: criteria for bacterial strain typing J Clin Microbiol 1995 33 2233 2239 7494007 Salamon H Behr MA Rhee JT Small PM Genetic distances for the study of infectious disease epidemiology Am J Epidemiol 2000 151 324 334 10670558 Upholt WB Estimation of DNA sequence divergence from comparison of restriction endonuclease digests Nucleic Acids Res 1977 4 1257 1265 896461 Dowling TE Moritz C Palmer JD Riesenberg LH Hillis DM, Moritz C, Mable BK Nucleic acids III: analysis of fragments and restriction sites In Molecular Systematics 1996 Sunderland, Massachusetts: Sinauer 249 320 Lynch M The similarity index and DNA fingerprinting Mol Biol Evol 1990 7 478 484 2263197 Call DR Hallett JG Mech SG Evans M Considerations for measuring genetic variation and population structure with multilocus fingerprinting Mol Ecol 1998 7 1337 1346 10.1046/j.1365-294x.1998.00454.x Römling U Grothues D Heuer T Tümmler B Physical genome analysis of bacteria Electrophoresis 1992 13 626 631 1459079 Holt RJ Strike P Bruce DK Phylogenetic analysis of tnpR genes in mercury resistant soil bacteria: the relationship between DNA sequencing and RFLP typing approaches FEMS Microbiol Lett 1996 144 95 102 8870257 10.1016/0378-1097(96)00345-X Arens M Methods for subtyping and molecular comparison of human viral genomes Clin Microbiol Rev 1999 12 612 626 10515905 Takewaki S Okuzumi K Manabe I Tanimura M Miyamura K Nakahara K Yazaki Y Ohkubo A Nagai R Nucleotide sequence comparison of the mycobacterial dnaJ gene and PCR-restriction fragment length polymorphism analysis for identification of mycobacterial species Int J Syst Bacteriol 1994 44 159 166 7907223 Russo CAM Takezaki N Nei M Efficiencies of different genes and different tree-building methods in recovering a known vertebrate phylogeny Mol Biol Evol 1996 13 525 536 8742641 Olive DM Bean P Principles and applications of methods for DNA-based typing of microbial organisms J Clin Microbiol 1999 37 1661 1669 10325304 Goldberg TL Weigel RM Hahn EC Scherba G Comparative utility of restriction fragment length polymorphism analysis and gene sequencing to the molecular epidemiological investigation of a viral outbreak Epidemiol Infect 2001 126 415 424 11467798 10.1017/S0950268801005489 Nei M Kumar S Molecular Evolution and Phylogenetics 2000 New York: Oxford University Press Qiao B Investigation of the accuracy of partial genome sequencing and restriction fragment analysis in determination of genetic relationships: a computer simulation study PhD dissertation, University of Illinois at Urbana-Champaign 2003 Chan S-Y Bernard H-U Ratterree M Birkebak TA Faras AJ Ostrow RS Genomic diversity and evolution of papillomaviruses in rhesus monkeys J Virol 1997 71 4938 4943 9188556 De Villiers E-M Fauquet C Broker TR Bernard H-U zur Hausen H Classification of papillomaviruses Virology 2004 324 17 27 15183049 10.1016/j.virol.2004.03.033 Gao F Yue L Robertson DL Hill SC Hui H Biggar RJ Neequaye AE Whelan TM Ho DD Shaw GM Sharp PM Hahn BH Genetic diversity of human immunodeficiency virus type 2: evidence of distinct sequence subtypes with differences in virus biology J Virol 1994 68 7433 7447 7933127 Greiser-Wilke I Fritzmeier J Koenen F Vanderhallen H Rutili D de Mia G-M Romero L Rosell R Sanchez-Vizcaino JM San Gabriel A Molecular epidemiology of a large classical swine fever epidemic in the European Union in 1997–1998 Vet Microbiol 2000 77 17 27 11042397 10.1016/S0378-1135(00)00253-4 Forsberg R Oleksiewicz MB Krabbe Petersen A-M Hein J Bøtner A Storgaard T A molecular clock dates the common ancestor of European-type porcine reproductive and respiratory syndrome virus at more than 10 years before the emergence of disease Virology 2001 289 174 179 11689039 10.1006/viro.2001.1102 Knowles NJ Samuel AR Molecular epidemiology of foot-and-mouth disease virus Virus Res 2003 91 65 80 12527438 10.1016/S0168-1702(02)00260-5 Goering RV Duensing TD Rapid field inversion gel electrophoresis in combination with a rRNA gene probe in the epidemiological evaluation of Staphylococci J Clin Microbiol 1990 28 426 429 1691206 Maslow JN Mulligan ME Arbeit RD Molecular epidemiology: application of contemporary techniques to the typing of microorganisms Clin Infect Dis 1993 17 153 164 8399860 Tenover FC Arbeit RD Goering RV the Molecular Typing Working Group of the Society for Healthcare Epidemiology of America How to select and interpret molecular strain typing methods for epidemiological studies of bacterial infections: a review for healthcare epidemiologists Infect Control 1997 18 426 439 Laber TL Iverson JT Liberty JA Giese SA The evaluation and implementation of match criteria for forensic analysis of DNA J Forensic Sci 1995 40 1058 1064 8522913 Duewer DL Lalonde SA Aubin RA Fourney RM Reeder DJ Interlaboratory comparison of autoradiographic DNA profiling measurements: precision and concordance J Forensic Sci 1998 43 465 471 9608684 Gill P Evett IW Woodroffe S Lygo JE Millican E Webster M Databases, quality control and interpretation of DNA profiling in the Home Office Forensic Science Service Electrophoresis 1991 12 204 209 2040267 Hillis DM Mable BK Larson A Davis SK Zimmer EA Hillis DM, Moritz C, Mable BK Nucleic acids IV: sequencing and cloning In Molecular Systematics 1996 Sunderland, Massachusetts: Sinauer 321 381 Genbank Database Thompson JD Higgins DG Gibson TJ CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice Nucleic Acids Res 1994 22 4673 4680 7984417 Kimura M A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences J Mol Evol 1980 16 111 120 7463489 Kimura M Estimation of evolutionary distances between homologous nucleotide sequences Proc Natl Acad Sci USA 1981 78 454 458 6165991 Sambrook J Fritsch EF Maniatis T Molecular Cloning – A Laboratory Manual 1989 2 New York: Cold Spring Harbor Laboratory Press Nakisa RC DIGEST, version 1.0 London: Imperial College of Science, Technology and Medicine 1993 Nei M Molecular Evolutionary Genetics 1987 New York: Columbia University Press Mantel N The detection of disease clustering and a generalized regression approach Cancer Res 1967 27 209 220 6018555 Saitou N Nei M The Neighbor-joining method: a new method for reconstructing phylogenetic trees Mol Biol Evol 1987 4 406 425 3447015 Kumar S Tamura K Jakobsen IB Nei M MEGA: Molecular Evolutionary Genetics Analysis Software, version 2.1 Tempe: Arizona State University 2001 Swafford DL Olsen GJ Waddell Hillis DM Hillis DM, Moritz C, Mable BK Phylogenetic Inference In Molecular Systematics 1996 Sunderland, Massachusetts: Sinauer 407 514 Page RDM COMPONENT, version 2.0 London: The Natural History Museum 1993 Robinson DF Foulds LR Comparison of phylogenetic trees Math Biosci 1981 53 131 147 10.1016/0025-5564(81)90043-2 Penny D Hendy MD The use of tree comparison metrics Syst Zool 1985 34 75 82

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==== Front BMC BioinformaticsBMC Bioinformatics1471-2105BioMed Central London 1471-2105-5-1031528386110.1186/1471-2105-5-103Methodology ArticleImproving the scaling normalization for high-density oligonucleotide GeneChip expression microarrays Lu Chao 1chao.lu@utoronto.ca1 Microarray Facility, The Centre for Applied Genomics, The Hospital for Sick Children, 555 University Avenue, Elm Wing Room 10104, Toronto, Ontario M5G 1X8, Canada2004 29 7 2004 5 103 103 17 7 2003 29 7 2004 Copyright © 2004 Lu; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background Normalization is an important step for microarray data analysis to minimize biological and technical variations. Choosing a suitable approach can be critical. The default method in GeneChip expression microarray uses a constant factor, the scaling factor (SF), for every gene on an array. The SF is obtained from a trimmed average signal of the array after excluding the 2% of the probe sets with the highest and the lowest values. Results Among the 76 U34A GeneChip experiments, the total signals on each array showed 25.8% variations in terms of the coefficient of variation, although all microarrays were hybridized with the same amount of biotin-labeled cRNA. The 2% of the probe sets with the highest signals that were normally excluded from SF calculation accounted for 34% to 54% of the total signals (40.7% ± 4.4%, mean ± sd). In comparison with normalization factors obtained from the median signal or from the mean of the log transformed signal, SF showed the greatest variation. The normalization factors obtained from log transformed signals showed least variation. Conclusions Eliminating 40% of the signal data during SF calculation failed to show any benefit. Normalization factors obtained with log transformed signals performed the best. Thus, it is suggested to use the mean of the logarithm transformed data for normalization, rather than the arithmetic mean of signals in GeneChip gene expression microarrays. Microarraynormalizationgene expressionDNARNAoligonucleotideGeneChipscaling ==== Body Background The high-density oligonucleotide microarray, also known as GeneChip®, made by Affymetrix Inc (Santa Clara, CA), has been widely used in both academic institutions and industrial companies, and is considered as the "standard" of gene expression microarrays among several platforms. A single GeneChip® can hold more than 50,000 probe sets for every gene in human genome. A probe set is a collection of probe pairs that interrogates the same sequence, or set of sequences, and typically contains 11 probe pairs of 25-mer oligonucleotides [1-3]. Each pair contains the complementary sequence to the gene of interest, the so-called perfect match (PM), and a specificity control, called the Mismatch (MM) [3]. Gene expression level is obtained from the calculation of hybridization intensity to the probe pairs and is referred to as the "signal" [4-10]. The normalization method used in GeneChip software is called scaling and is defined as an adjustment of the average signal value of all arrays to a common value, the target signal value in order to make the data from multiple arrays comparable [4,11]. The purpose of data normalization is to minimize the effects of experimental and/or technical variations so that meaningful biological comparisons can be made and true biological changes can be found among multiple experiments. Several approaches have been proposed and shown to be effective and beneficial. They were mostly from studies on two-color spotted microarrays [12-19]. Some authors proposed normalization of the hybridization intensities, while others preferred to normalize the intensity ratios. Some used global, linear methods, while others used local, non-linear methods. Some suggested using the spike-in controls, or house-keeping genes, or invariant genes, while others preferred all the genes on the array. For GeneChip data, some have proposed different models to normalize signal values or normalize probe pair values [10,20-24]. Despite the presence of other alternatives, many biologists still use the default scaling method and consider that such method is satisfactory and is useful to identify biological alterations [23,25,26]. With the increasing awareness and usage of GeneChip technology and willingness to continue to use GeneChip software among many biologists, it is worth improving the performance or correcting the problems of the software. In this report, the author has demonstrated that in the scaling algorithm excluding 2% of the probe sets with the highest and the lowest values did not have much benefit. However, the logarithmic transformation of signal values prior to scaling proved to be the optimum normalization strategy and is strongly recommended. Results The statistical algorithm in current GeneChip software (MAS 5 and GCOS 1) for gene expression microarray data has eliminated the negative gene expression values, a problem present in earlier versions of the software [5,7]. It uses a robust averaging method based on the Tukey biweight function to calculate the gene expression level from the logarithm transformed hybridization data [3-5,11]. The reported data of a probe set is the antilog of the Tukey biweight mean multiplied by a SF and/or a normalization factor (NFaffy). When both the SF and NFaffy are equal to 1, there is no normalization or manipulation of original data. Both NFaffy and SF are computed in virtually the same way. NFaffy is calculated in comparison analysis to compare the array average of one experiment with that of a baseline experiment, while SF is obtained from the signal average of one experiment comparing with a common value, the target signal in absolute analysis [3-5,11,22]. The average value used in GeneChip is a trimmed average. It is not calculated from all probe sets, but from 96% of the probe sets after the 2% of the probe sets with the highest and the 2% of the lowest signals were removed. In this report, a total of 76 experiments with rat U34A GeneChip were analyzed. As shown in Table 1, the total hybridization signals varied although all arrays were hybridized with the same amount of biotin-labeled cRNA and scanned with the same scanner of identical settings. The array of the highest hybridization intensities had 2.8 times more signals than that of the lowest. The average array signals had 25.8% variation in terms of coefficient of variation. The mean signals were significantly greater than the median signals on each array, indicating a non-normal distribution. The density plot showed a long-tailed and skewed distribution (not shown) and the average of such data is known to be sensitive to the larger values in the data set. The rat U34A GeneChip contained 8799 probe sets; hence 2% was about 176 probe sets. The sum of the 2% of the probe sets with the lowest signals accounts for less than 0.1% of the total signals (0.05% ± 0.01%, mean ± SD, n = 76) and its impact on SF calculation can be ignored. However, the sum of the 2% of the probe sets with the highest signals, the TrimTotal as used in this report, was responsible for about 40% of the total signals (from 34% to 54%, Table 1). The remaining 96% of the probe sets used for SF calculation, produced only about 60% of the signals. Excluding 4% of the probe sets did not reduce the variation, but rather slightly increased the variation, which in turn resulted in a wider range of SFs (Table 1). It was also found that the TrimTotal was highly correlated with total signal (R = 0.928), but less with medians (R = 0.536) and the mean of log signals (R = 0.643). The trimmed percentage (Tp) was found to be negatively associated with the median (R = 0.558, b = -1.116) and the mean of log signals (R = 0.495, b = -0.968), but not with the total signal of all probe sets. Among other approaches to global linear normalization, one can also use the median signal or the mean of logarithm transformed signals to calculate the NF. NFLogMean showed a higher correlation with NFMedian than with SF. There were larger differences between NFLogMean and SF than those between NFLogMean and NFMedian (Fig. 1). To test if the larger difference was a result of removing 4% of the probe sets from the calculation, another NF, the NFTrimLogMean was obtained using the same data as for SF, but with a log transformation. There is a very significant correlation between NFTrimLogMean and NFLogMean (R = 0.9998). The 4% of the probe sets that was removed from NFTrimLogMean calculation reduced the total data by only 4% after log transformation. Since it is impossible to obtain the true normalization factor, an average of the four global linear NFs mentioned above was used instead to estimate the 'true' NF. To compare them with the true NF, a score (NFscore) is introduced. Each NF is calculated against the respective 'true' NF to obtain its NFscore. The average NFscore (± SD) is 7.01% (± 6.24%), 4.51% (± 3.48%), 2.25%(± 2.33%) and 1.95% (± 1.61%), and the sum of NFscore is 5.33, 3.43, 1.71 and 1.48 for SF, NFMedian, NFTrimLogMean and NFLogMean, respectively (Fig. 1). The sum of NFscore indicated an accumulated variation from the true NF, and the larger the number, the larger the accumulated variation. An attempt to add a 5th NF obtained from the arithmetic mean of all probe sets of the array was also made to calculate and compare NFscore with each NFs, and the results showed the same conclusion (data not shown). It is fair to conclude that NFLogMean produced the least variation. Discussion Logarithmic transformation is a well-accepted approach for stabilizing variance and has become a common choice for data transformation and normalization for spotted microarrays [12,16]. Much improvement has been made in GeneChip microarray technology and accompanying software during the past few years. The current version of GeneChip software has improved its performance and is better than the earlier versions that used the Average Difference to express levels of gene expression [3,4]. However, the normalization algorithm was inherited and remains the only and default option for gene expression data processing in both MAS 5 and the newly released GeneChip Operating Software (GCOS) software. They continue to use the arithmetic mean of signals to obtain the SF in absolute analysis (single array) and the NF in comparison analysis (two arrays) [3-5,7,11,22]. It is clearly shown here that the trimmed average and the resulting SF had a larger variance than the median-based NF, or the NF based on the mean of log transformed signals. Similar results were observed in other GeneChip expression arrays, such as mouse U74A and human U133A (data not shown). Elimination of the highest and the lowest 2% of the probe set signals did not stabilize the trimmed means. When intra-array variance was reduced by 40%, this approach cannot be considered to be optimal. The logarithmic transformation of signals stabilized the variation well and made the normalization process much less dependent upon the mean and less affected by the outliers. Although simple and popular, the global linear normalization has its drawbacks, especially when the relationship among multiple experiments or genes is not linear. To address such problems, several methods have been proposed to conduct local and non-linear normalization, [12,14-17,20,22,27]. Data normalization is a very critical and important step for microarray data mining process. The use of different approaches to normalization may have a profound impact on the selection of differentially expressed genes and conclusions about the underlying biological processes especially when subtle biological changes are investigated [12,16,28]. Conclusions Normalization of microarray data allows direct comparison of gene expression levels among experiments. A global linear normalization, called scaling has been widely used in GeneChip microarray technology for gene expression analysis. The scaling factor (SF) is calculated from a trimmed average of gene expression level after excluding the 2% of the data points of the highest values and the lowest values. It is shown here that the 2% of the probe sets of the highest signals contained from 34% to 54% of the total signals. Elimination of the outliers did not reduce, but increased the variation among multiple arrays. Instead, normalization factors obtained from the mean of the log transformed signals had the best performance. Thus, the current scaling method, although widely used, is not optimal and needs further improvement. The mean of logarithm transformed signals is highly recommended to use for normalization factor calculation. Methods GeneChip experiments and data Total RNA was isolated from rat tissues or cells in Trizol reagent and purified with Qiagen Rneasy kit. cDNA was synthesized in presence of oligo(dT)24-T4 (Genset Corp, La Jolla, CA) and biotinlated UTP and CTP were used to generate biotin labeled cRNA according to the recommended protocols [29]. Rat genome microarray, U34A GeneChip (Affymetrix Inc., Santa Clara, CA) was used and hybridized with 15 μg of gel-verified fragmented cRNA. Hybridization intensity was scanned in GeneArray 2500 scanner (Agilent, Palo Alto, CA) with Microarray Suite (MAS) 5.0 software [4]. Data from a total of 76 independent GeneChip experiments were used in this study. Normalization factor (NF) Gene expression data exported from MAS 5.0 were submitted to a Perl script to calculate different normalization factors. In the scaling approach, a trimmed average signal is calculated after excluding 2% probe sets with the highest signals and 2% with the lowest signal values. The scaling factor (SF) is obtained using equation (1) in comparison with a chosen fixed number, called the target signal (TS) and is verified with the results from MAS 5.0 of the same settings [3,4,11]. SFj = TS / STrimMeanj     (1) Other normalization factors for comparison were obtained by the following: NFMedianj = TS / Smedj     (2) NFLogMeanj = 2 nfj where i = 1..., n represents the probe sets, j = 1..., J represented the array experiments, Si is the signal of the anti-log of a robust average (Tukey biweight) of log(PM-MM) reported from MAS 5.0 [5], Smedj is the median signal on the array j, STrimMeanj is the trimmed average on array j after excluding 2% of the probe sets with the highest and the lowest signals [3,4,11,22]. NFMedianj is obtained by using the median signal on array j, and NFLogMeanj is obtained by using the mean of log transformed signals. TS was set to 150, 38 and 38 for SF, NFMedian and NFLogMean, respectively in order to have similar NFs. In comparison with different NFs, a score, NFscore is introduced. NFscorej = (NFj - TrueNFj)/TrueNFj, and TrueNFj = (SFj + NFMedianj + NFLogMeanj + NFTrimLogMeanj)/4, where NFTrimLogMeanj, was calculated from equation (3) excluding the 2% of the probe sets with the highest and lowest signals, TrueNFj was used as a 'true' NF. Sum of . Other analysis Unless otherwise specified, logarithm transformation is carried out with the logarithm base 2. Trimmed total signal TrimTotal is the sum of the signals from the 2% of the probe sets with the highest signal values. Total signal Total is the sum of the signals of all probe sets in the array, and trimmed percentage Tpj = (TrimTotalj / Totalj) × 100%. Abbreviations GeneChip® is the registered trademark owned by Affymetrix Inc. PM: perfect Match; MM: mismatch; SF: scaling factor; NF: normalization factor; TS: target signal Short phrase: Normalization of GeneChip microarray data Acknowledgements I would like to acknowledge the support from Dr. H. D. Lipshitz, Dr. S. Scherer, The Centre for Applied Genomics, and The Hospital for Sick Children. The excellent technical work by Lan He is highly appreciated. I would also like to thank Drs. P. Liu, M. Post, K. Tanswell, G. Fantus and S. Keshavjee for sharing their U34A data. Review and comments from Drs. C. Greenwood, J. Beyene, C.E. M'lan and P. McLoughlin are highly appreciated. Finally, suggestions to improve this paper from the editor and referees are deeply appreciated. Figures and Tables Figure 1 (A) Comparison among different normalization factors. NFLogMean (x-axis) is plotted against SF (red open triangle) and NFMedian (black closed circle). The correlation between NFLogMean and NFMedian is higher (R = 0.971) than that between NFLogMean and SF (R = 0.918). (B) The NF score, NFscore, for SF (red open triangle), NFMedian (blue open diamond) and NFLogMean (black closed circle) is expressed as a function of respective 'true NF'. NFTrimLogMean is not shown here to simplify the graph since it is similar to NFLogMean. See also in Methods. Table 1 Summary of signal data in 76 rat genome U34A GeneChip microarrays. Lowest Highest Mean SD CV (%) Total signal 832,561.4 3,161,392.7 2,039,655.7 526,295.0 25.80% Sum of signals used for SF 524,513.7 1,986,236.9 1,212,296.5 336,138.0 27.73% Trimmed total 308,047.7 1,240,257.3 827,359.1 215,325.1 26.03% Mean signal 94.6 359.3 231.0 59.8 25.80% Median of signals 17.8 54.8 35.7 8.7 24.41% Mean of log signals 4.3 5.8 5.1 0.4 7.17% Trimmed percentage 34.4 54.1 40.7 4.4 10.70% "Total signal" is the sum of all the signals on each array. "Sum of signals used for SF" is the sum of signals excluding the trimmed data and used to calculate SF. "Trimmed total" is the sum of the 2% probe sets with the highest signals on the array. "Mean of log signals" is the mean of log2 transformed signals. "Trimmed percentage" = (Trimmed total/Total signal) × 100%. See also in Methods. The "lowest" and "highest" showed the lowest and highest number in the category among the 76 chips, respectively. The mean, standard deviation (SD) and coefficient of variation (CV) were also calculated. ==== Refs Lipshutz RJ Fodor SP Gingeras TR Lockhart DJ High density synthetic oligonucleotide arrays Nat Genet 1999 21 20 24 9915496 10.1038/4447 Lockhart DJ Dong H Byrne MC Follettie MT Gallo MV Chee MS Mittmann M Wang C Kobayashi M Horton H Brown EL Expression monitoring by hybridization to high-density oligonucleotide arrays Nat Biotechnol 1996 14 1675 1680 9634850 Affymetrix GeneChip Expression Analysis: Data Analysis Fundamentals http://wwwaffymetrixcom/ Affymetrix Affymetrix Microarray Suite 5.0 User's Guide 2001 2002 Santa Clara, CA, USA, Affymetrix Inc Hubbell E Liu WM Mei R Robust estimators for expression analysis Bioinformatics 2002 18 1585 1592 12490442 10.1093/bioinformatics/18.12.1585 Li C Wong WH Model-based analysis of oligonucleotide arrays: expression index computation and outlier detection Proc Natl Acad Sci U S A 2001 98 31 36 11134512 10.1073/pnas.011404098 Liu WM Mei R Di X Ryder TB Hubbell E Dee S Webster TA Harrington CA Ho MH Baid J Smeekens SP Analysis of high density expression microarrays with signed-rank call algorithms Bioinformatics 2002 18 1593 1599 12490443 10.1093/bioinformatics/18.12.1593 Sasik R., Calvo, E., and Corbeil, J. Statistical analysis of high-density oligonucleotide arrays: a multiplicative noise model Bioinformatics 2002 18 1633 1640 12490448 10.1093/bioinformatics/18.12.1633 Naef F Hacker CR Patil N Magnasco M Empirical characterization of the expression ratio noise structure in high-density oligonucleotide arrays Genome Biol 2002 3 RESEARCH0018 11983059 10.1186/gb-2002-3-4-research0018 Irizarry RA Bolstad BM Collin F Cope LM Hobbs B Speed TP Summaries of Affymetrix GeneChip probe level data Nucleic Acids Res 2003 31 e15 12582260 10.1093/nar/gng015 Affymetrix GeneChip Operating Software: User's Guide http://wwwaffymetrixcom/ 1.0 Quackenbush J Microarray data normalization and transformation Nat Genet 2002 32 Suppl 496 501 12454644 10.1038/ng1032 Culhane AC Perriere G Considine EC Cotter TG Higgins DG Between-group analysis of microarray data Bioinformatics 2002 18 1600 1608 12490444 10.1093/bioinformatics/18.12.1600 Durbin BP Hardin JS Hawkins DM Rocke DM A variance-stabilizing transformation for gene-expression microarray data Bioinformatics 2002 18 Suppl 1 S105 10 12169537 Kepler TB Crosby L Morgan KT Normalization and analysis of DNA microarray data by self-consistency and local regression Genome Biol 2002 3 RESEARCH0037 12184811 10.1186/gb-2002-3-7-research0037 Yang YH Dudoit S Luu P Lin DM Peng V Ngai J Speed TP Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation Nucleic Acids Res 2002 30 e15 11842121 10.1093/nar/30.4.e15 Schadt EE Li C Ellis B Wong WH Feature extraction and normalization algorithms for high-density oligonucleotide gene expression array data J Cell Biochem Suppl 2001 Suppl 37 120 125 11842437 10.1002/jcb.10073 Hill AA Brown EL Whitley MZ Tucker-Kellogg G Hunter CP Slonim DK Evaluation of normalization procedures for oligonucleotide array data based on spiked cRNA controls Genome Biol 2001 2 RESEARCH0055 11790258 10.1186/gb-2001-2-12-research0055 Yang IV Chen E Hasseman JP Liang W Frank BC Wang S Sharov V Saeed AI White J Li J Lee NH Yeatman TJ Quackenbush J Within the fold: assessing differential expression measures and reproducibility in microarray assays Genome Biol 2002 3 research0062 12429061 Irizarry RA Hobbs B Collin F Beazer-Barclay YD Antonellis KJ Scherf U Speed TP Exploration, normalization, and summaries of high density oligonucleotide array probe level data Biostatistics 2003 4 249 264 12925520 10.1093/biostatistics/4.2.249 Li C Hung Wong W Model-based analysis of oligonucleotide arrays: model validation, design issues and standard error application Genome Biol 2001 2 RESEARCH0032 11532216 Bolstad BM Irizarry RA Astrand M Speed TP A comparison of normalization methods for high density oligonucleotide array data based on variance and bias Bioinformatics 2003 19 185 193 12538238 10.1093/bioinformatics/19.2.185 Geller SC Gregg JP Hagerman P Rocke DM Transformation and normalization of oligonucleotide microarray data Bioinformatics 2003 19 1817 1823 14512353 10.1093/bioinformatics/btg245 Stuart RO Bush KT Nigam SK Changes in global gene expression patterns during development and maturation of the rat kidney Proc Natl Acad Sci U S A 2001 98 5649 5654 11331749 10.1073/pnas.091110798 Tusher VG Tibshirani R Chu G Significance analysis of microarrays applied to the ionizing radiation response Proc Natl Acad Sci U S A 2001 98 5116 5121 11309499 10.1073/pnas.091062498 Knudtson KL Griffin C Iacobas DA Johnson K Khitrov G Levy S Massimi A Nowak N Viale A Grill G Brooks AI A current profile of microarray laboratories: the 2002-2003 ABRF microarray research group survey of laboratories using microarray technologies http://wwwabrforg Tseng GC Oh MK Rohlin L Liao JC Wong WH Issues in cDNA microarray analysis: quality filtering, channel normalization, models of variations and assessment of gene effects Nucleic Acids Res 2001 29 2549 2557 11410663 10.1093/nar/29.12.2549 Hoffmann R Seidl T Dugas M Profound effect of normalization on detection of differentially expressed genes in oligonucleotide microarray data analysis Genome Biol 2002 3 RESEARCH0033 12184807 Affymetrix GeneChip Expression Analysis: Technical Manual http://wwwaffymetrixcom/

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==== Front BMC BioinformaticsBMC Bioinformatics1471-2105BioMed Central London 1471-2105-5-991527293510.1186/1471-2105-5-99Research ArticleAccuracy of cDNA microarray methods to detect small gene expression changes induced by neuregulin on breast epithelial cells Yao Bin 15binyao@genetics.wayne.eduRakhade Sanjay N 1srakhade@cmb.biosci.wayne.eduLi Qunfang 1liqu@karmanos.orgAhmed Sharlin 2sahmed@med.wayne.eduKrauss Raul 4rkraus@post.harvard.eduDraghici Sorin 3sod@mercury.cs.wayne.eduLoeb Jeffrey A 12jloeb@med.wayne.edu1 Center for Molecular Medicine and Genetics, Wayne State University, Detroit, Michigan, USA2 Department of Neurology, Wayne State University, Detroit, Michigan, USA3 Department of Computer Science, Wayne State University, Detroit, Michigan, USA4 Newton, Massachusetts, USA5 MCBI Wayne State Node, Wayne State University, Detroit, Michigan, USA2004 23 7 2004 5 99 99 19 5 2004 23 7 2004 Copyright © 2004 Yao et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background cDNA microarrays are a powerful means to screen for biologically relevant gene expression changes, but are often limited by their ability to detect small changes accurately due to "noise" from random and systematic errors. While experimental designs and statistical analysis methods have been proposed to reduce these errors, few studies have tested their accuracy and ability to identify small, but biologically important, changes. Here, we have compared two cDNA microarray experimental design methods with northern blot confirmation to reveal changes in gene expression that could contribute to the early antiproliferative effects of neuregulin on MCF10AT human breast epithelial cells. Results We performed parallel experiments on identical samples using a dye-swap design with ANOVA and an experimental design that excludes systematic biases by "correcting" experimental/control hybridization ratios with control/control hybridizations on a spot-by-spot basis. We refer to this approach as the "control correction method" (CCM). Using replicate arrays, we identified a decrease in proliferation genes and an increase in differentiation genes. Using an arbitrary cut-off of 1.7-fold and p values <0.05, we identified a total of 32 differentially expressed genes, 9 with the dye-swap method, 18 with the CCM, and 5 genes with both methods. 23 of these 32 genes were subsequently verified by northern blotting. Most of these were <2-fold changes. While the dye-swap method (using either ANOVA or Bayesian analysis) detected a smaller number of genes (14–16) compared to the CCM (46), it was more accurate (89–92% vs. 75%). Compared to the northern blot results, for most genes, the microarray results underestimated the fold change, implicating the importance of detecting these small changes. Conclusions We validated two experimental design paradigms for cDNA microarray experiments capable of detecting small (<2-fold) changes in gene expression with excellent fidelity that revealed potentially important genes associated with the anti-proliferative effects of neuregulin on MCF10AT breast epithelial cells. ==== Body Background Spotted cDNA microarrays are used in high-throughput experiments that interrogate the relative expression of thousands of genes simultaneously for many biological processes with wide applications in biological and medical research. Typically in a two-dye spotted cDNA microarray experiment, two mRNA samples are transcribed into cDNAs, labeled with two different fluorescent dyes, commonly Cy3 and Cy5, and hybridized on the same slide. The relative gene expression level is then measured as a ratio of the intensities of the fluorescent dyes. However, the signal intensity of the dye, which indirectly represents the gene expression level, can be affected by many other sources of error such as dye efficiency, sample preparation, and the variability of the biological samples [1,2]. An important question is how to identify differentially expressed genes, some of which change only minimally (<2-fold), given many known and potentially unknown sources of variance in the microarray experiment. In order to reduce false positive rates, many published experiments use a cut-off of 2- to 3-fold [3-5]. This limits the ability of the microarray experiment to detect small, but biologically important changes. In fact, recent reports have shown that microarrays can significantly underestimate gene expression changes and therefore a high cut-off will miss important changes [6]. Although more sophisticated statistical methods have been proposed for single slide analysis [7-13], it is becoming clear that in order to reduce random variance, replication becomes more and more important in microarray experimental design by greatly increasing the power of the experiment to measure small gene expression changes [2,13-17]. As a relatively new technique, many new theories have been developed for data analysis and experimental design, but few of these theories have been rigorously tested against a well-established standard method such as the Northern blot. In this paper we compared two experimental design and analysis methods performed on quadruplicate arrays that include a dye-swap design [18,19] and a modified reference design method that uses a control-control hybridization to correct for systematic experimental errors, that we refer to as the "control correction method" (CCM). We demonstrate that both experimental designs accurately identified small (<2-fold) gene expression changes after a 24-hour treatment of MCF10AT breast epithelial cells with the growth and differentiation factor neuregulin. These changes correlate well with the anti-proliferative effects of neuregulin resulting in a relative decrease in proliferative genes and increase in anti-proliferative genes that will be important for future investigations. Results The results presented in this paper demonstrate two, complementary cDNA microarray methods capable of reliably revealing small changes in gene expression in transformed human breast epithelial MCF10AT cells after treatment with neuregulin. Since, as shown in Fig. 1, treatment of these cells with neuregulin significantly slows their growth rate, identifying early gene expression changes in this process will be important in understanding how neuregulin regulates cell growth in both normal and malignant breast epithelium, and will also provide both biological markers and potential targets in breast cancer. Large quantities of highly purified total RNA were isolated from MCF10AT cells treated with or without neuregulin for 24 hours and used both for microarray experiments and northern blot confirmation studies. Experimental designs to address systematic errors As with most experimental methods, replicate measurements can reduce random errors. Equally important are systematic errors. Systematic errors result from a constant tendency to over- and under-estimate true values and cannot be eliminated by replicate analysis, since they are often highly reproducible. An example of such a systematic error is a gene-specific dye effect, also called "dye–gene" interaction [18], and is shown in Fig. 2A. For a given gene spotted in duplicate (arrows), the red signal labeling the treated sample (T) is much brighter than the green signal for the control sample (C). This was highly reproducible for both spots on the same array and between multiple arrays. One way to determine whether the apparent up-regulation of this gene is true, is to use the same control sample labeled with both red and green dyes and perform a control/control (C/C) hybridization. Fig. 2A shows that the same intense red signal is seen in the C/C hybridization as was seen in the treated/control (T/C), demonstrating that this signal is a systematic error producing a false positive gene expression change. Given the unavoidable presence of these systematic errors, methods to correct these errors are needed. One way to correct for systematic errors in microarray experiments is to take advantage of C/C hybridizations to correct the T/C hybridizations. This requires a modified reference design, which we refer to as a "control correction" design. This is different from a common reference design used previously [19,20]. Here, each spot of the T/C hybridization is "corrected" by the same spot from the C/C hybridization for systematic errors. A second method that will also correct for systematic errors is a "dye-swap" design [16,17,19]. The dye-swap design uses an ANOVA to calculate gene expression changes from replicate cDNA microarrays probed with T/C hybridizations performed where the dye color is swapped. Included in the ANOVA are factors to correct for systematic errors such as dye and dye-gene interactions. The "control correction" and the dye-swap designs are compared in Fig. 2B. Each of these experimental designs was performed on quadruplicate arrays. Each of these two designs required its own analysis method. While we used an analysis method that utilizes individual t-tests for each spot for the CCM, we compared both ANOVA and Bayesian analysis methods for the dye-swap design. Control correction method experimental design and results A flow chart for the control correction method is shown in Fig. 2C. All microarrays used in this study were from the same lot of 3333 gene spotted cDNA slides (similar to the commercially available NEN MicroMax 2400 slides with 933 additional genes (Alphagene Inc., Woburn, MA) where each gene was spotted in duplicate, and hybridized using an optimized, two-step hybridization protocol with either Cy3 or Cy5-labeled dendrimer complexes (Genisphere, Hatfield, PA). A key advantage of the Genisphere Dendrimer system is the need for only 3 μg of total RNA per array without the need for a potentially non-linear amplification step to boost the signal. After scanning and spot-wise local background correction (Imagene Software, Biodiscovery, CA), a log Cy5/Cy3 ratio versus log signal intensity MA plot was prepared and shown in Fig 3A[20]. Without any correction, the ratio vs. intensity plot shows a banana shape as ratios trend downward in the low intensity range. This suggests an intensity-dependent dye effect. In order to correct this and to normalize data sets between different slides, an intensity-dependent normalization procedure was performed that fits the data to a lowess curve as a function of signal intensity [21]. After normalization, the log ratios became more evenly distributed around zero (Fig. 3B). However, despite this relatively even distribution, histograms of normalized log ratios for T/C and C/C display long tails to the left as shown in the histograms in Fig. 4A and the quantile-qauntile plots in Fig. 4B. Since there should be no treatment effects on the C/C slides, a symmetric, normal distribution would have been expected. The skewed appearances of the normalized distributions indicate additional, uncorrected systematic errors in both T/C and C/C hybridizations. "Correction" of each spot by subtracting the log (C/C) ratios from the log (T/C) ratios produces an approximately normal distribution of the log (T/C) ratios (shown on the bottom of Figs. 4A and 4B). In addition to the systematic errors that occur on a spot-by-spot basis shown in Fig. 2A, systematic errors were found as a function of slide location, particularly at the edge of the arrays. These errors were also corrected by this method (data not shown). Yang and Dudoit proposed a within slide normalization for this type of spatial effect [21], however, one concern for within slide normalization is that if the number of genes is small in each spatial group, the assumption that there will be an equal proportion of up- and down-regulated genes may be untrue. As a final step, a t-test was performed to compare the normalized log ratios of T/C and C/C for each gene. This yields p values for each control-corrected fold change calculated as log (T/C)-log (C/C). In Fig. 5, the average and standard deviation of gene expression ratios for the log (T/C) and log (C/C) are plotted for the genes using 1.7-fold and p < 0.05 cut-offs. This clearly demonstrates the importance of correcting each log (T/C) value with the corresponding log (C/C) control value. For example, while some log (T/C) ratios are close to zero, by using the log (C/C) as baseline, true gene expression changes above or below this were identified that would otherwise have been missed. The 1.7-fold cutoff was chosen to be within the detection range of northern blot analyses, which we felt would be the most sensitive method to confirm these small changes. A volcano plot, shown in Fig. 6A, summaries 46 differentially-regulated genes that met these criteria for the CCM. Comparison of the control correction to the dye-swap design Many have proposed that a dye-swap experimental design combined with an ANOVA will correct for systematic errors [17-19]. To verify this and compare the dye-swap design to the control correction design, a dye-swap experiment was performed on quadruplicate arrays using the same RNA samples and the two interconnect ANOVA model of Wolfinger et al [22,23]. Using this experimental design with the same cut-off values, 14 differentially expressed genes were identified and are presented as a volcano plot alongside that of the CCM (Fig. 6B). Table 1 lists those genes that met our selection criteria, together with their fold-change, p values, and functional classifications. Only 5 genes were found in common for both methods. The genes have been broadly grouped into proliferation, differentiation, and unclassified genes in order to observe trends in the neuregulin-induced gene expression changes that could be important in regulating cell growth. A general trend showing a down-regulation of proliferation genes and up-regulation of differentiation genes was observed. This includes several oncogenes, cell cycle control and cell proliferation genes that were all down-regulated; and tumor suppressor genes, growth inhibition and differentiation genes were up-regulated. This pattern is consistent with the anti-proliferative/differentiation effects of neuregulin on MCF10AT human breast epithelial cells. Verification of microarray accuracy by northern blot analysis To confirm these gene expression changes and to determine the accuracy of each experimental method, we selected 23 genes for verification by northern blot. We chose all 5 genes detected by both methods, 6 up-regulated and 5 down-regulated genes from the control correction design, and 7 genes from the dye-swap experiment. The selection of genes was not random, as we selected a balanced complement of genes of variable intensity that were both up- and down-regulated. The probes used for northern blots were generated by PCR from clones used to spot the arrays. Each blot contained triplicate control and treated samples and was re-probed multiple times. Fig. 7 summarizes the northern blot results for these 23 genes. The band intensities were quantified, normalized to total ribosomal RNA for each gel, and averaged to produce a fold change that was compared directly to the fold change from the microarrays. In general, differential gene expression was confirmed by the northern blots for both array design methods. For the dye-swap method only 1 of 12 genes was a false positive, while 4 out of 16 genes were false positives in the control correction method. Down-regulated genes were verified more reliably in the control correction method (10/10) than up-regulated genes (2/6). All differentially expressed genes common to both methods were confirmed.. Since the ANOVA method we used can sometimes underestimate the variance, we re-analyzed our dye-swap data with a Bayesian method using a regularized t-test as implemented in Cyber-T [24]. This analysis revealed 16 differentially expressed genes using the same cut-offs, 10 of which were in common with the ANOVA method (Table 1). A greater number of genes were identified using the regularized t-test, and the corresponding p values for these genes were lower. Based on the previous northern blot data, 8/9 (89%) of these were confirmed. Discussion Gene expression changes in MCF10AT cells suggest a rapid anti-proliferative effect of neuregulin MCF10AT cells are a human breast epithelial cell line stably transfected with a mutant ras oncogene. These cells are pre-malignant, but can progress to invasive carcinoma [25,26]. Given that neuregulin can differentially affect the growth properties of different cell lines, we used the MCF10AT cell line as model system to identify genes that may be down-stream from neuregulin activation and could thus be studied further for their roles in breast cancer cells that respond differentially to neuregulin. Combining two cDNA microarray experimental design methods, we have identified genes differentially expressed by neuregulin treatment that correlated with a significant decrease in their growth rate. The pattern of expression clearly shows an anti-proliferative effect of neuregulin on the MCF10AT cells with a reduction in genes associated with proliferation such as heat shock proteins, oncogenes, cell cycle control genes, genes involved in fatty acid and sugar synthesis, transcription and translation together with an increase in differentiation genes including tumor suppressor genes, DNA damage repair genes, growth inhibition genes and differentiation genes. We further showed that these effects are biologically consistent with the rapid, anti-proliferative effects of neuregulin on cell number. Additional experiments have shown that these genes are important biological markers for the degree of malignancy in other breast epithelial cell lines that have differential proliferation responses to neuregulin (Li Q, Ahmed S, and Loeb JA, unpublished results). Both experimental designs demonstrate a high confirmation rate for small changes in gene expression One of the important tasks in microarray technology is to design experiments and develop statistical tools to obtain data efficiently and accurately to answer fundamental questions in biology. In many experiments, this requires the ability to detect small changes in gene expression with high fidelity. In this study we compared two common experimental design paradigms for cDNA microarrays and determined their accuracy by northern blot. Both methods identified small expression changes with considerable accuracy. In the control correction design, we used control hybridizations to correct for systematic errors on a spot-by-spot basis. The method is based on an assumption that systematic errors from slides made from the same lot and processed identically do not vary significantly. To minimize the possible variance of systematic errors in T/C slides and C/C slides we maintained strict experimental conditions, such as same-day sample preparation and same-day hybridization. We also used the same control samples for both the T/C and C/C hybridizations instead of using an arbitrary control sample that might be quite different in mRNA composition [19]. This results in similar spot intensities for each gene both in the treatment and the control and will minimize any differences that could be caused by the different mRNA compositions from different samples. This spot-by-spot control correction can eliminate systematic errors that cannot be corrected with slide-wise normalization. Similarly, in the dye-swap design, two different dyes are used to label the same sample, which enables the correction of dye-gene interactions in the ANOVA model. A summary of the results from this study are shown in the Venn diagrams in Fig. 8. Using the 1.7-fold and p < 0.05 cut-offs, the overall verification rate was 75% for the CCM and 92% for the dye-swap method using ANOVA. Among the 18 confirmed expression changes, all were below 3-fold and only six were above 2-fold. Many of the expression changes below 2-fold on the microarrays underestimated the fold-change measured by northern blotting. The accuracy was not dependent on microarray spot intensity as genes with both low and high signal intensities had similar verification rates (data not shown). The confirmation rates for both methods are comparable to methods reported by Mutch (87.5%) [27] and Tusher (92%) [28]. Of particular importance in this study is our high confirmation rates for genes differentially expressed by 2-fold or less. The t-test used for the CCM and ANOVA for the dye-swap method depend on assumptions of Gaussian distributions that may or may not be present in a microarray experiment with a small number of replicates. Some efforts have been made to develop Bayesian frameworks that incorporate prior distributions in order to estimate the noise [24,29,30]. We therefore re-analyzed our dye-swap data using a "regularized" t-test [24]. Using this, we identified 16 genes that met our cut-off criteria, 10 of which were in common with the ANOVA analysis. Of those genes that we measured by northern blot analysis, 8/9 or 89% were verified. In summary, the regularized t-test revealed more genes than the ANOVA method with generally lower p values. If we eliminate the 1.7-fold cut-off, but maintain the p value <0.05, the CCM identified 493 genes, the ANOVA identified 499 genes, and the regularized t-test identified 729 differentially expressed genes (Fig. 8B). Among these, 399 were in common between the regularized t-test and ANOVA, 248 in common between the CCM and the regularized t-test, and 188 in common between the CCM and the ANOVA. These results demonstrate that if the false-positive rate remains the same, the regularized t-test is more sensitive than the traditional ANOVA and has extensive overlap, while the CCM has the least overlap between the other methods, but identifies different genes with slightly less specificity. In our analysis, we selected genes based on their p values obtained from replicates of individual spots and did not adjust these p-values for multiple comparisons. This may be a major cause for the higher false positive rates for both of our experimental designs. For the CCM, if we apply Bonferroni correction, while we can eliminate all false positives, we would also miss a majority of the differentially expressed genes verified by Northern blotting. Therefore, if accuracy is the main purpose of a study, multiple comparison corrections should be used, while if sensitivity is the main purpose, then it should not be used with the understanding that the accuracy will be lower. Comparison of a dye-swap versus a control correction method experimental design For our experimental design, the dye-swap method had a higher confirmation rate than the control correction method. This is, in part, due to the smaller variance that results from an effective doubling of the number of treated samples in the dye-swap method compared to the control correction method. Despite the higher degree of accuracy, the dye-swap design identified fewer genes and only detected down-regulated genes, whereas the control correction identified 3-times the number of genes that were both up- and down-regulated. However the control correction method was less specific for up-regulated genes. These differences may not solely reflect methodological differences, but likely result from experimental variability produced by performing the experiments independently on different days. Nonetheless, the results presented here suggest that both methods have clear merit in their abilities to show true gene expression changes, particularly for expression changes of 2-fold or less, and for genes with low signal intensities and/or low abundance. The final decision as to which method is preferred depends on the experimental design. For example, the amount of sample and number of replicates required are important considerations both in terms of how difficult the RNA is to obtain and the number of samples that need to be compared. This also translates into the cost to perform the experiment. For instance, the dye-swap method generates a larger sample size for the same number of slides, thus producing greater significance when comparing gene expression between two samples. However this method requires a minimum of two slides and two different labeling reactions per sample. If the amount of sample is limited or population level replication is more desirable than individual sample replication, the control correction is more efficient since individual replicates for reverse dye labeling are not required and each sample can be run with only one slide. For example, to compare 6 treatment samples with a single control sample would require a minimum of 12 microarrays using the dye-swap method, whereas the minimum number of 8 arrays is possible using the control correction method; 6 for treatment samples and 2 for controls. Another common experimental design used for time course or dose response studies is the reference design. In fact, the control correction method described here is essentially a modified reference design method where the zero time or dose point is the control-control comparison. As discussed above, using a very similar control sample to correct the series will give less false positives and negatives and a more accurate absolute value of the observed change than a dissimilar, pooled reference sample. Under-estimation of fold changes by cDNA microarrrays Although our cDNA microarray results were accurate, the measured changes generally underestimated the actual changes measured by northern blots. Yuen et al. [6] similarly found that both oligonucleotide arrays (GeneChips by Affymetrix) and cDNA arrays underestimate fold changes compared to quantitative RT-PCR. The cause for this underestimation is not clear, however, it may be due to the limited dynamic range of dye signal or non-specific binding of the dye. Nonetheless, the limitations in accuracy and fold change estimation are far outweighed by the ability of microarrays to identify biologically important gene expression changes. Conclusions This study demonstrated that dye-swap and control correction experimental design paradigms for cDNA microarray experiments are capable of detecting small, biologically important changes in gene expression with excellent fidelity while revealing important down-stream anti-proliferative effects of neuregulin on breast epithelial cells for future studies. Methods cDNA microarrays Human cDNA glass microarrays, called the Alphamax Genechip, were obtained from Alphagene Inc. (Woburn, MA) containing 3333 cDNAs spotted in duplicate. The cDNAs used are identical to commercially available Micromax 2400 slides from Perkin Elmer Life Sciences (Boston, MA), most of which were derived from a human fetal brain cDNA library, with an additional 933 genes (gene list available upon request). MCF10AT cell culture – MCF10AT cells were from Dr. Robert Pauley at the Karmanos Cancer Institute (Detroit, MI). The cells were cultured in DMEM/F12 media (Invitrogen) supplemented with 5% horse serum (Invitrogen), 10 mM HEPES buffer (Invitrogen), 10 μg/ml insulin (Sigma), 20 ng/ml EGF (Upstate Biotechnology), 100 ng/ml cholera enterotoxin (CalBiochem) and 0.5 μg/ml hydrocortisone (Sigma) at 37°C in 5% CO2 incubator. Neuregulin treatment and RNA extraction – A recombinant human NRG β1 polypeptide (amino acids 14–246) was generously provided by AMGEN (Thousand Oaks, CA). After 3 days of culture, MCF10AT cells were treated with human recombinant neuregulin β1 form for 24 hours. MCF10AT cells grown under similar conditions without neuregulin treatment were used as a control. The cells were then harvested and total RNA was extracted using Ultraspec (Biotecx laboratories). The total RNA was cleaned up by Rneasy kit (Qiagen) and quantified using a fluorescent dye binding assay, Ribogreen (Molecular Probes). RNA purity was assessed by agarose gel electrophoresis. Proliferation assays were performed by counting quadruplicate cultures plated at 5000 cells/well using a hemocytometer. Microarray hybridization – cDNA microarrays were used in a 2-step hybridization protocol that was optimized for the Genisphere dendrimer labeling method. Total RNA was reverse transcribed into cDNA containing a unique 5' primer tag, using the Genisphere 3DNA expression array detection kit. In brief, for each reaction, 3 μg of total RNA was reverse transcribed using 0.2 μM oligo-dT-Genisphere capture primer, 0.5 mM dNTP, 200 U Superscript II (Invitrogen) in 1X first strand Superscript II buffer at 42°C for 2 h. The RNA from the DNA/RNA hybrids was denatured with 0.5 M NaOH / 50 mM EDTA at 65°C for 10 min. The reaction was neutralized using 1 M Tris-HCl ph 7.5. The contents of the tube containing the NRG-treated and control cDNA were then mixed together and 3 μl linear acrylamide (Ambion) and 250 μl of 3 M ammonium acetate were added to them. cDNA was precipitated by adding 100% Ethanol and incubating at -20°C for 30 min. The cDNA was collected in a pellet by centrifugation at 13000 rpm for 15 min in a microcentrifuge. and resuspended in Alternate (formamide-containing) Hybridization buffer (Genisphere) at 65°C for 10 min and modified LNA blocker (Genisphere) with denatured Cot 1 DNA. The entire mixture was added to the pre-hybridized array (Alphamax) for hybridization at 55°C for at 36 hr. A clear increase in signal was obtained with a 36 h hybridization compared to 16 h. After hybridization, the arrays were washed with 2X SSC and 0.2% SDS at 60°C for 15 min, followed by a wash with 2X SSC and another with 0.2X SSC at room temperature. For fluorescence detection, a second hybridization with the dendrimer was optimal. 2.5 μl each of the Cy3 and Cy5 dendrimer in Hybridization Buffer (Vial 6, Genisphere kit) were mixed with denatured Cot1 DNA and differential expander and the mixture was added to the pre-hybridized slides for hybridization at 60°C for 2 hrs. The slides were washed again as described above. Microarray data analysis method Analysis of CCM experiment Arrays were scanned with a GenePix 4000 A scanner (Axon Instruments, Inc., Union City, CA). Images were quantified using ImaGene Software (Biodiscovery, Inc. Marina del Rey, CA) that uses a local background subtracted from the signal. Signals not consistently detectable (background corrected signal lower than 2 times of background standard deviation) were eliminated. We fitted loess curve to the log transformed data using the "loess" function in SAS software (SAS Institute Inc., NC) for intensity dependent normalization followed by a t-test to compare T/C with C/C ratio, gene by gene. The t-test was performed on the normalized log ratio with Welch correction for unequal variance. The control corrected fold change was calculated as: log (fold) = log(T/C)-log(C/C) Analysis of dye-swap experiment For the dye-swap method we performed the same background correction and data filtering for absent genes and log transformations. We then used a two interconnect ANOVA model [22,23] and Mixed Model Analysis of Microarray Data (MANMADA) to identify differentially expressed genes. First we use a normalization model for log-transformed intensity measurements: yij = μ + Ai + Dj + ADij + εij Where μ is the sample mean, Ai is the effect of ith array, Dj is the effect of dye cy3 or cy5, ADij is array dye interaction and εij is random error. The residue from normalization model is then used in following gene model to find treatment effects on each gene: rijkg = Aig + Djg + Tkg Where rijkg is the residual of each gene from the normalization model, Tkg is the treatment effect (control or treated), and Aig and Djg are the array and dye effects, respectively. The expression change for each gene is thus: log (fold) = Ttreated-Tcontrol Northern blots 5 μg total RNA isolated from MCF10AT cells was run on a 1.3% Agarose/2.2M Formaldehyde gel as described previously [31]. Probes were prepared by PCR from the same clones used to spot the slides provided by Alphagene Inc except for AJ224442, X86779 and U62739, where clones BC011696, BI754516 and BG763631, with of over 99% identity, were used as substitutes. Probes were generated by random priming using PrimiT II kit (Stratagene) radiolabeled probes. The auto-radiographs within the linear range of the film were scanned with a flatbed scanner with transparency adapter and quantified using MetaMorph (Universal Imaging) analysis software as described previously [32]. For time course measurements, the amount of signal normalized for loading with either 18S RNA or GAPDH were plotted together after first setting 100% to the intensity of the control measurement at 48 hours and setting the lowest intensity value to 0%. Authors' contributions BY analyzed microarray data. SR carried out microarray experiment. QL conducted MCF10AT cell culture and mRNA extraction. SA carried out northern blots experiments. RK provide input on microarray experiments. SD contributed ideas to data analysis. JAL conceived and design the experiment. Acknowledgements This work was supported by the Ralph C. Wilson, Sr. and Ralph C. Wilson, Jr. Medical Research Foundation (JAL), NINDS (NIH) R01 NS45207 (JAL), and the American Cancer Society 85-003-14 (JAL). SNR was supported by a pre-doctoral fellowship from the Epilepsy Foundation of America. We thank Robert Getts from Genisphere for helpful discussions on optimizing the dendrimer labeling system and Thomas Beaumont for helpful comments on the manuscript. Figures and Tables Figure 1 Anti-proliferative effects of neuregulin on MCF10AT cells. Quadruplicate cultures of MCF10AT cells were treated with and without 1 nM neuregulin 3 days after plating and cell counts were performed demonstrating a significant decrease in their growth 24 and 48 hours after treatment. The p value for 24 hr was 0.0011, and for 48 hr was 1.46E-05. Figure 2 (A) Highly reproducible systematic errors from gene-dye interactions. The arrows demonstrate intense red dye labeling for a given gene spotted in duplicate both for the T/C slide where the treated sample is labeled with red dye (Cy5) and control sample is labeled with green dye (Cy3), as well as in the C/C slide where the same sample is labeled both red and green. (B) Experimental designs. Two different experimental methods were compared: A dye-swap approach, where the dye color is reversed for T/C hybridizations, and a "control correction" design, where T/C and C/C hybridizations are performed without reversing the dyes. T denotes the neuregulin treated cells, while C denotes the untreated, control cells. Each arrows represent a replicate and the tails of the arrows indicate cy5 labeling and the heads indicate cy3 labeling. (C) Data processing flow chart for the control correction method. Figure 3 Array and intensity-dependent variation can be corrected by normalization based on intensity. (A) This is an MA-plot before normalization for one of T/C slides that plots the log intensity ratios against the averaged intensities at both wavelengths: M = log (T/C) and A = 1/2log(T*C). The majority of the data is less than zero in a "banana" or "comma" shaped distribution. This demonstrates a systematic, intensity-dependent dye effect, prominent at lower intensities. (B) After normalization using the lowess function, the MA-plot shows a more even distribution at all intensities. Figure 4 Control correction of each spot markedly improves the distribution of log ratios. (A) Histograms show that T/C and C/C log ratio distributions after lowess normalization still have a marked asymmetry with a larger tail towards the left (increased down-regulated genes). The distribution becomes symmetric after subtracting the log (C/C) from the log (T/C). (B) Quantile-quantile plots similarly show that the log ratio distribution becomes more normal after correction of each spot with the control ratio. Figure 5 The control correction method identifies gene expression changes from spots with variable C/C ratios. The log ratios for each gene are plotted both for the T/C (□) and the corresponding C/C (▲) hybridizations for the 46 genes selected from control correction method. The error bars represent one standard deviation in each direction. Figure 6 Both control correction and dye-swap methods reveal statistically significant changes in gene expression. Volcano plots of the control correction method (A) and the dye-swap method (B) reveal a small proportion of genes that met our arbitrary criteria of having >1.7 fold changes with p values <0.05, determined individually for each gene. The horizontal lines on each graph represent p = 0.05. The vertical lines represent 1.7 fold changes, both up- and down-regulated. Genes shown in blue in upper left and right areas were selected for northern blot confirmation. Figure 7 Northern blots confirm a majority of gene expression changes for both methods. The far right-hand column shows northern blot results performed in triplicate for genes identified by each microarray design method. For each gene, the fold-change from the microarray together with the average fold-change quantified from the northern blots is shown. To correct for loading differences, in the northern blots each measurement was normalized to the corresponding amount of 18S rRNA measured on each gel. A representative example of the 18S rRNA is shown on the bottom of the figure. Two of the Z74615 northern blot bands were discarded due to contamination. Down-regulated, up-regulated, and false positive genes that were not confirmed by northern blots are indicated. Figure 8 Summary of confirmation rates for the two methods. (A) A Venn diagram summarizes the number of genes identified by each experimental method using 1.7-fold and p < 0.05 cut-offs and the verification rate by northern blot. While all 5 genes common to both methods were confirmed, 7 out of 11 genes from control correction method were confirmed, and 6 out of 7 genes from the dye-swap method using the ANOVA were confirmed. 8 out of 9 genes identified with the regularized t-test were confirmed. (B) A Venn diagram summarizes the number of genes identified by each experimental method of p < 0.05 without a fold change restriction. Table 1 List of identified genes. Gene accession numbers, gene descriptions, fold-changes, and p-values for genes identified by the dye-swap method with ANOVA and regularized t-test analysis and the control correction method (CCM). Genes are broadly classified into three groups: proliferation-related, differentiation-related and unclassified. Proliferation-Related Genes Classification Acc# Gene Description CCM fold CCM p-value Dye-Swap fold Dye-Swap p-value Regularized fold Regularized p-value Heat shock proteins NM_006597 heat shock 70 kDa protein 8 -2.8 9.5E-6 -2.9 4.2E-7 -2.9 8.4E-13 M34664 heat shock 60 kDa protein 1 (chaperonin) -1.9 3.9E-6 -1.9 4.8E-10 L15189 heat shock 70 kDa protein 9B (mortalin-2) -2.2 1.4E-3 -1.8 1.8E-6 -1.8 6.5E-6 M22382 Human mitochondrial matrix protein P1 -1.8 1.5E-5 -1.7 2.9E-9 M94859 Human calnexin mRNA, complete cds -1.8 4.1E-3 L27706 Human chaperonin protein (Tcp20) gene complete cds -2.1 3.8E-4 Transcription and translation D29677 helicase with zinc finger domain -1.9 3.1E-5 -1.9 2.8E-10 X91257 seryl-tRNA synthetase -1.8 1.2E-3 -1.8 4.5E-8 -1.9 2.0E-11 D30655 eukaryotic translation initiation factor 4A, isoform 2 -1.7 5.5E-5 U76111 Human translation repressor NAT1 mRNA, complete cds -1.7 8.9E-3 M74719 transcription factor 4 -1.9 2.0E-3 X13293 Human mRNA for B-myb gene 1.7 4.2E-9 U00968 Human SREBP-1 mRNA -1.7 8.4E-9 L41490 eukaryotic translation elongation factor 1 alpha 1-like 14 -1.8 1.4E-5 -1.7 5.3E-5 -1.8 5.0E-12 Fatty acid and sugar metabolism D16481 Homo sapiens mRNA for mitochondrial 3-ketoacyl-CoA thiolase beta-subunit of trifunctional protein, complete cds -1.8 5.6E-5 Y00711 Human mRNA for lactate dehydrogenase B (LDH-B) -1.8 6.9E-5 -1.7 2.4E-8 D78130 Homo sapiens mRNA for squalene epoxidase, complete cds -1.9 1.2E-5 -1.8 9.5E-7 M37154 Human glutamate dehydrogenase (GDH) mRNA, complete cds -1.8 4.0E-3 -1.7 8.0E-4 U62961 3-oxoacid CoA transferase -2.0 1.2E-4 Y13647 Homo sapiens mRNA for stearoyl-CoA desaturase -1.9 1.5E-6 GTPase Y13286 Homo sapiens mRNA for GDP dissociation inhibitor beta -1.8 1.8E-5 -1.7 1.3E-6 X51408 Human mRNA for n-chimaerin 2.1 1.8E-2 Cell cycle U47413 Human cyclin G1 mRNA, complete cds -1.7 9.6E-7 AF139897 Homo sapiens BASS1 (BASS1) mRNA, partial cds -1.8 1.8E-3 D00265 Homo sapiens mRNA for cytochrome c, partial cds -2.0 2.0E-2 X68836 H. sapiens mRNA for S-adenosylmethionine synthetase -2.2 8.3E-6 U19251 Homo sapiens neuronal apoptosis inhibitory protein mRNA, complete cds 1.8 1.1E-2 S45630 alpha B-crystallin=Rosenthal fiber component [human, glioma cell line, mRNA, 691 nt] 2.1 2.7E-3 X86779 H. sapiens mRNA for FAST kinase 1.7 1.9E-2 Oncogenes X03541 Human mRNA of trk oncogene -1.8 3.1E-3 M19722 Human fgr proto-oncogene encoded p55-c-fgr protein, complete cds -1.9 5.0E-3 X77548 H. sapiens cDNA for RFG -2.1 1.5E-3 Proliferation D63390 platelet-activating factor acetylhydrolase, isoform Ib, beta subunit 30 kDa -1.8 4.4E-4 U62739 Human branched-chain amino acid aminotransferase (ECA40) mRNA, complete cds 1.7 1.2E-2 L12350 Human thrombospondin 2 (THBS2) mRNA, complete cds 1.9 2.2E-3 X06614 Human mRNA for receptor of retinoic acid 1.7 2.8E-2 Y07921 Human mRNA for serine protease -1.7 1.1E-6 Differentiation-Related Genes Tumor suppressor AF042857 Homo sapiens lung cancer antigen NY-LU-12 variant A mRNA, complete cds 2.1 4.4E-3 Differentiation M21300 Human small proline rich protein (sprI) mRNA, clone 15B 1.7 2.0E-4 ECM and vesicle trafficking M15395 Human leukocyte adhesion protein (LFA-1/Mac-1/p150,95 family) beta subunit mRNA 2.0 2.8E-2 S72869 H4(D10S170) = putative cytoskeletal protein [human, thyroid, mRNA, 3011 nt] -1.9 3.2E-2 D21267 SNAP25 synaptosomal-associated protein, 25 kDa 1.9 1.7E-2 U95735 Human thrombospondin 2 (THBS2) mRNA, complete cds -1.8 1.5E-5 X68194 H. sapiens h-Sp1 mRNA -1.7 4.2E-2 Z74615 collagen, type I, alpha 1 2.5 5.3E-3 Immune-response U68030 chemokine (C-C motif) receptor 6 1.8 5.8E-3 X04701 Human mRNA for complement component C1r -2.4 3.3E-2 DNA repair D79983 ring finger protein 144 1.7 2.3E-2 D29013 Homo sapiens mRNA for DNA polymerase beta, complete cds 1.8 7.3E-3 Unclassified Genes J02854 myosin, light polypeptide 9, regulatory 2.6 4.5E-2 X58141 Human mRNA for erythrocyte adducin alpha subunit 2.1 3.2E-2 AJ224442 Homo sapiens mRNA for putative methyltransferase 1.8 3.4E-3 X06661 Human mRNA for 27-kDa calbindin 2.1 9.0E-3 U24266 aldehyde dehydrogenase 4 family, member A1 1.7 2.5E-3 U62432 Human nicotinic acetylcholine receptor alpha3 subunit precursor, mRNA, complete cds 1.8 7.0E-3 U79259 Human clone 23945 mRNA, complete cds -1.7 4.2E-3 M18533 Homo sapiens dystrophin (DMD) mRNA, complete cds -2.5 1.1E-2 J05401 Human sarcomeric mitochondrial creatine kinase(MtCK) gene, complete cds 2.2 1.5E-2 D13315 Human mRNA for lactoyl glutathione lyase -1.7 4.6E-7 AB001740 Homo sapiens mRNA for p27 1.8 8.6E-4 M15661 Human ribosomal protein mRNA -1.7 1.3E-4 ==== Refs Nadon R Shoemaker J Statistical issues with microarrays: processing and analysis Trends Genet 2002 18 265 271 12047952 10.1016/S0168-9525(02)02665-3 Draghici S Kuklin A Hoff B Shams S Experimental design, analysis of variance and slide quality assessment in gene expression arrays Curr Opin Drug Discov Devel 2001 4 332 337 11560067 Schena M Shalon D Heller R Chai A Brown PO Davis RW Parallel human 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==== Front BMC GenetBMC Genetics1471-2156BioMed Central London 1471-2156-5-201527474910.1186/1471-2156-5-20Methodology ArticleA multilocus likelihood approach to joint modeling of linkage, parental diplotype and gene order in a full-sib family Lu Qing 1qlu@darwin.epbi.cwru.eduCui Yuehua 1ycui@stat.ufl.eduWu Rongling 12Rwu@mail.ifas.ufl.edu1 Department of Statistics, University of Florida, Gainesville, Florida 32611 USA2 College of Life Sciences, Zhejiang Forestry University, Lin'an, Zhejiang 311300, People's Republic of China2004 26 7 2004 5 20 20 10 3 2004 26 7 2004 Copyright © 2004 Lu et al; licensee BioMed Central Ltd.2004Lu et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background Unlike a pedigree initiated with two inbred lines, a full-sib family derived from two outbred parents frequently has many different segregation types of markers whose linkage phases are not known prior to linkage analysis. Results We formulate a general model of simultaneously estimating linkage, parental diplotype and gene order through multi-point analysis in a full-sib family. Our model is based on a multinomial mixture model taking into account different diplotypes and gene orders, weighted by their corresponding occurring probabilities. The EM algorithm is implemented to provide the maximum likelihood estimates of the linkage, parental diplotype and gene order over any type of markers. Conclusions Through simulation studies, this model is found to be more computationally efficient compared with existing models for linkage mapping. We discuss the extension of the model and its implications for genome mapping in outcrossing species. ==== Body Background The construction of genetic linkage maps based on molecular markers has become a routine tool for comparative studies of genome structure and organization and the identification of loci affecting complex traits in different organisms [1]. Statistical methods for linkage analysis and map construction have been well developed in inbred line crosses [2] and implemented in the computer packages MAPMAKER [3], CRI-MAP [4], JOINMAP [5] and MULTIMAP [6]. Increasing efforts have been made to develop robust tools for analyzing marker data in outcrossing organisms [7-12], in which inbred lines are not available due to the heterozygous nature of these organisms and/or long-generation intervals. Genetic analyses and statistical methods in outcrossing species are far more complicated than in species that can be selfed to produce inbred lines. There are two reasons for this. First, the number of marker alleles and the segregation pattern of marker genotypes may vary from locus to locus in outcrossing species, whereas an inbred line-initiated segregating population, such as an F2 or backcross, always has two alleles and a consistent segregation ratio across different markers. Second, linkage phases among different markers are not known a priori for outbred parents and, therefore, an algorithm should be developed to characterize a most likely linkage phase for linkage analysis. To overcome these problems of linkage analysis in outcrossoing species, Grattapaglia and Sederoff [13] proposed a two-way pseudo-testcross mapping stratety in which one parent is heterozygous whereas the other is null for all markers. Using this strategy, two parent-specific linkage maps will be constructed. The limitation of the pseudo-testcross strategy is that it can only make use of a portion of molecular markers. Ritter et al. [7] and Ritter and Salamini [9] proposed statistical methods for estimating the recombination fractions between different segregation types of markers. Using both analytical and simulation approaches, Maliepaard et al. [10] discussed the power and precision of the estimation of the pairwise recombination fractions between markers. Wu et al. [11] formulated a multilocus likelihood approach to simultaneously estimate the linkage and linkage phases of the crossed parents over multiple markers. Ling [14] proposed a three-step analytical procedure for linkage analysis in out-crossing populations, which includes (1) determining the parental haplotypes for all of the markers in a linkage group, (2) estimating the recombination fractions, and (3) choosing a most likely marker order based on optimization analysis. This procedure was used to analyze segregating data in an outcrossing forest tree [15]. Currently, none of these models for linkage analysis in outcrossing species can provide a one-step analysis for the linkage, parental linkage phase and marker order from segregating marker data. In this article, we construct a unifying likelihood analysis to simultaneously estimate linkage, linkage phases and gene order for a group of markers that display all possible segregation patterns in a full-sib family derived from two outbred parents (see Table 1 of Wu et al. [11]). Our idea here is to integrate all possible linkage phases between a pair of markers in the two parents, each specified by a phase probability, into the framework of a mixture statistical model. In characterizing a most likely linkage phase (or parental diplotype) based on the phase probabilities, the recombination fractions are also estimated using a likelihood approach. This integrative idea is extended to consider gene orders in a multilocus analysis, in which the probabilities of all possible gene orders are estimated and a most likely order is chosen, along with the estimation of the linkage and parental diplotype. We perform extensive simulation studies to investigate the robustness, power and precision of our statistical mapping method incorporating linkage, parental diplotype and gene orders. An example from the published literature is used to validate the application of our method to linkage analysis in outcrossing species. Table 1 Estimation from two-point analysis of the recombination fraction ( ± SD) and the parental diplotype probability of parent P () and Q () for five markers in a full-sib family of n = 100 Parental diplotype r = 0.05 r = 0.20 Marker Pa × Qa | | | | a b c d | | | | 0.530 ± 0.0183 0.2097 ± 0.0328 a b a b 0.9960 0.9972 0.9882 0.9878 | | | | 0.0464 ± 0.0303 0.2103 ± 0.0848 a o × o a 1 (0b) 0(1b) 1 (0b) 0(1b) | | | | 0.0463 ± 0.0371 0.1952 ± 0.0777 a b b b 1 1/0c 1 1/0c | | | | 0.0503 ± 0.0231 0.2002 ± 0.0414 a b c d 1 1/0c 1 1/0c aShown is the parental diplotype of each parent for the five markers hypothesized, where the vertical lines denote the two homologous chromosomes. bThe values in the parentheses present a second possible solution. For any two symmetrical markers (2 and 3), = 1, = 0 and = 0, = 1 give an identical likelihood ratio test statistic (Wu et al. 2002a). Thus, when the two parents have different diplotypes for symmetrical markers, their parental diplotypes cannot be correctly determined from two-point analysis. cThe parental diplotype of parent P2 cannot be estimated in these two cases because marker 4 is homozygous in this parent. The MLE of r is given between two markers under comparison, whereas the MLEs of p and q given at the second marker. Two-locus analysis A general framework Suppose there is a full-sib family of size n derived from two outcrossed parents P and Q. Two sets of chromosomes are coded as 1 and 2 for parent P and 3 and 4 for parent Q. Consider two marker loci and , whose genotypes are denoted as 12/12 and 34/34 for parent P and Q, respectively, where we use / to separate the two markers. When the two parents are crossed, we have four different progeny genotypes at each marker, i.e., 13, 14, 23 and 24, in the full-sib family. Let r be the recombination fraction between the two markers. In general, the genotypes of the two markers for the two parents can be observed in a molecular experiment, but the allelic arrangement of the two markers in the two homologous chromosomes of each parent (i.e., linkage phase) is not known. In the current genetic literatuire, a linear arrangement of nonalleles from different markers on the same chromosomal region is called the haplotype. The observable two-marker genotype of parent P is 12/12, but it may be derived from one of two possible combinations of maternally- and paternally-derived haplotypes, i.e., [11] [22] or [12] [21], where we use [] to define a haplotype. The combination of two haplotypes is called the diplotype. Diplotype [11] [22] (denoted by 1) is generated due to the combination of two-marker haplotypes [11] and [22], whereas diplotype [12] [21] (denoted by ) is generated due to the combination of two-marker haplotypes [12] and [21]. If the probability of forming diplotype [11] [22] is p, then the probability of forming diplotype [12] [21] is 1 - p. The genotype of parent Q and its possible diplotypes [33] [44] and [34] [43] can be defined analogously; the formation probabilities of the two diplotypes are q and 1 - q, respectively. The cross of the two parents should be one and only one of four possible parental diplotype combinations, i.e., [11] [22] × [33] [44]), [11] [22] × [34] [43], [12] [21] × [33] [44] and [12] [21] × [34] [43], expressed as 11, 1, 1 and , with a probability of pq, p(1 - q), (1 - p)q and (1 - p) (1 - q), respectively. The estimation of the recombination fraction in the full-sib family should be based on a correct diplotype combination [10]. The four combinations each will generate 16 two-marker progeny genotypes, whose frequencies are expressed, in a 4 × 4 matrix, as for [11] [22] × [33] [44], for [11] [22] × [34] [43], for [12] [21] × [33] [44] and for [12] [21] × [34] [43]. Note that these matrices are expressed in terms of the combinations of the progeny genotypes for two markers and , respectively. Let n = (nj1j2)4 × 4 denote the matrix for the observations of progeny where j1,j2 = 1 for 13, 2 for 14, 3 for 23, or 4 for 34 for the progeny genotypes at these two markers. Under each parental diplotype combination, nj1j2 follows a multinomial distribution. The likelihoods for the four diplotype combinations are expressed as where N1 = n11 + n22 + n33 + n44, N2 = n14 + n23 + n32 + n41, N3 = n12 + n21 + n34 + n43, and N4 = n13 + n31 + n24 + n42. It can be seen that the maximum likeihood estimate (MLE) of r () under the first diplotype combination is equal to one minus under the fourth combination, and the same relation holds between the second and third diplotype combinations. Although there are identical plug-in likelihood values between the first and fourth combinatins as well as between the second and third combinations, one can still choose an appropriate from these two pairs because one of them leads to greater than 0.5. Traditional approaches for estimating the linkage and parental diplotypes are to estimate the recombination fractions and likelihood values under each of the four combinations and choose one legitimate estimate of r with a higher likelihood. In this study, we incorporate the four parental diplotype combinations into the observed data likelihood, expressed as where Θ = (r, p, q) is an unknown parameter vector, which can be estimated by differentiating the likelihood with respect to each unknown parameter, setting the derivatives equal to zero and solving the likelihood equations. This estimation procedure can be implemented with the EM algorithm [2,11,16]. Let H be a mixture matrix of the genotype frequencies under the four parental diplotype combinations weighted by the occurring probabilities of the diplotype combinations, expressed as where Similar to the expression of the genotype frequencies as a mixture of the four diplotype combinations, the expected number of recombination events contained within each two-marker progeny genotype is the mixture of the four different diplotype combinations, i.e., where the expected number of recombination events for each combination are expressed as Define The general procedure underlying the {τ + 1}th EM step is given as follows: E Step: At step τ, using the matrix H based on the current estimate r{τ}, calculate the expected number of recombination events between two markers for each progeny genotype and , where dj1j2, hj1j2, pj1j2 and qj1j2 are the (j1j2)th element of matrix D, H, P and Q, respectively. M Step: Calculate r{τ+1} using the equation, The E step and M step among Eqs. (4) – (7) are repeated until r converges to a value with satisfied precision. The converged values are regarded as the MLEs of Θ. Model for partially informative markers Unlike an inbred line cross, a full-sib family may have many different marker segregation types. We symbolize observed marker alleles in a full-sib family by A1, A2, A3 and A4, which are codominant to each other but dominant to the null allele, symbolized by O. Wu et al. [11] listed a total of 28 segregation types, which are classified into 7 groups based on the amount of information for linkage analysis: A. Loci that are heterozygous in both parents and segregate in a 1:1:1:1 ratio, involving either four alleles A1A2 × A3A4, three non-null alleles A1A2 × A1A3, three non-null alleles and a null allele A1A2 × A3O, or two null alleles and two non-null alleles A1O × A2O; B. Loci that are heterozygous in both parents and segregate in a 1:2:1 ratio, which include three groups: B1. One parent has two different dominant alleles and the other has one dominant allele and one null allele, e.g., A1A2 × A1O; B2. The reciprocal of B1; B3. Both parents have the same genotype of two codominant alleles, i.e., A1A2 × A1A2; C. Loci that are heterozygous in both parents and segregate in a 3:1 ratio, i.e., A1O × A1O; D. Loci that are in the testcross configuration between the parents and segregate in a 1:1 ratio, which include two groups: D1. Heterozygous in one parent and homozygous in the other, including three alleles A1A2 × A3A3, two alleles A1A2 × A1A1, A1A2 × OO and A2O × A1A1, and one allele (with three null alleles) A1O × OO; D2. The reciprocals of D1. The marker group A is regarded as containing fully informative markers because of the complete distinction of the four progeny genotypes. The other six groups all contain the partially informative markers since some progeny genotype cannot be phenotypically separated from other genotypes. This incomplete distinction leads to the segregation ratios 1:2:1 (B), 3:1 (C) and 1:1 (D). Note that marker group D can be viewed as fully informative if we are only interested in the heterozygous parent. In the preceding section, we defined a (4 × 4)-matrix H for joint genotype frequencies between two fully informative markers. But for partially informative markers, only the joint phenotypes can be observed and, thus, the joint genotype frequencies, as shown in H, will be collapsed according to the same phenotype. Wu et al. [11] designed specific incidence matrices (I) relating the genotype frequencies to the phenotype frequencies for different types of markers. Here, we use the notation for a (b1 × b2) matrix of the phenotype frequencies between two partially informative markers, where b1 and b2 are the numbers of distinguishable phenotypes for markers and , respectively. Correspondingly, we have . The EM algorithm can then be developed to estimate the recombination fraction between any two partial informative markers. E Step: At step τ, based on the matrix (DH)' derived from the current estimate r{τ}, calculate the expected number of recombination events between the two markers for a given progeny genotype and : where , , and is the (j1j2)th element of matrices (DH)', H', P' and Q', respectively. M Step: Calculate r{τ+1} using the equation, The E and M steps between Eqs. (8) – (11) are repeated until the estimate converges to a stable value. Three-locus analysis A general framework Consider three markers in a linkage group that have three possible orders , and . Let o1, o2 and o3 be the corresponding probabilities of occurrence of these orders in the parental genome. Without loss of generality, for a given order, the allelic arrangement of the first marker between the two homologous chromosomes can be fixed for a parent. Thus, the change of the allelic arrangements at the other two markers will lead to 2 × 2 = 4 parental diplotypes. The three-marker genotype of parent P (12/12/12) may have four possible diplotypes, [111] [222], [112] [221], [121] [212] and [122] [211]. Relative to the fixed allelic arrangement 1|2| of the first marker on the two homologous chromosomes 1 and 2, the probabilities of allelic arragments 1|2| and 2|1| are denoted as p1 and 1 - p1 for the second marker and as p2 and 1 - p2 for the third marker, respectively. Assuming that allelic arrangements are independent between the second and third marker, the probabilities of these four three-marker diplotypes can be described by p1p2, p1(1 - p2), (1 - p1)p2 and (1 - p1) (1 - p2), respectively. The four diplotypes of parent Q can also be constructed, whose probabilities are defined as q1q2, q1(1 - q2), (1 - q1)q2 and (1 - q1) (1 - q2) respectively. Thus, there are 4 × 4 = 16 possible diplotype combinations (whose probabilities are the product of the corresponding diplotype probabilities) when parents P and Q are crossed. Let r12 denote the recombination fraction between markers and , with r23 and r13defined similarly. These recombination fractions are associated with the probabilities with which a crossover occurs between markers and and between markers and . The event that a crossover or no crossover occurs in each interval is denoted by D11 and D00, respectively, whereas the events that a crossover occurs only in the first interval or in the second interval is denoted by D10 and D01, respectively. The probabilities of these events are denoted by d00, d01, d10and d11, respectively, whose sum equals 1. According to the definition of recombination fraction as the probability of a crossover between a pair of loci, we have r12 = d10 + d11, r23 = d01 + d11 and r13 = d01 + d10. These relationships have been used by Haldane [17] to derive the map function that converts the recombination fraction to the corresponsding genetic distance. For a three-point analysis, there are a total of 16 (16 × 4)-matrices for genotype frequencies under a given marker order (), each corresponding to a diplotype combination, denoted by , where for 1|2| or 2 for 2|1| denote the two alternative allelic arrangements of the second and third marker, respectively, for parent P, and for 1|2| or 2 for 2|1| denote the two alternative allelic arrangements of the second and third marker, respectively, for parent Q. According to Ridout et al. [18] and Wu et al. [11], elements in are expressed in terms of d00, d01, d10 and d11. Similarly, there are 16 (16 × 4)-matrices for the expected numbers of crossover that have occurred for D00, D01, D10 and D11 for a given marker order, denoted by , , and respectively. In their Table 2, Wu et al. [11] gave the three-locus genotype frequencies and the number of crossovers on different marker intervals under marker order . Table 2 Estimation from three-point analysis of the recombination fraction ( ± SD) and the parental diplotype probabilities of parent P () and Q () for five markers in a full-sib family of n = 100 Parental diplotype Marker P × Q Case 1 Case 2 Case 1 Case 2 Recombination fraction = 0.05 | | | | a b c d | | | | 0.0511 ± 0.0175 a b a b 0.1008 ± 0.0298 0.9978 0.9986 | | | | 0.0578 ± 0.0269 0.0557 ± 0.0312 a o × o a 0.9977 0 0.0988 ± 0.0277 1 0 | | | | 0.0512 ± 0.0307 0.0476 ± 0.0280 1 1/0 a b b b 0.0932 ± 0.0301 1 1/0 1 1/0 | | | | 0.0514 ± 0.0229 a b c d 1 1 | | | | Recombination fraction = 0.20 | | | | a b c d | | | | 0.2026 ± 0.0348 a b a b 0.3282 ± 0.0482 0.9918 0.9916 | | | | 0.2240 ± 0.0758 0.2408 ± 0.0939 a o × o a 0.9944 0 0.3241 ± 0.0488 1 0 | | | | 0.1927 ± 0.0613 0.1824 ± 0.0614 a b b b 0.3161 ± 0.0502 1 1/0 1 1/0 | | | | 0.2017 ± 0.0393 a b c d 1 1 | | | | Case 1 denotes the recombination fraction between two adjacent markers, whereas case 2 denotes the recombination fraction between the two markers separated by a third marker. See Table 1 for other explanations. The joint genotype frequencies of the three markers can be viewed as a mixture of 16 diplotype combinations and three orders, weighted by their occurring probabilities, and is expressed as Similarly, the expected number of recombination events contained within a progeny genotype is the mixture of the different diplotype and order combinations, expressed as: Also define The occurring probabilities of the three marker orders are the mixture of all diplotype combinations, expressed, in matrix notation, as We implement the EM algorithm to estimate the MLEs of the recombination fractions between the three markers. The general equations formulating the iteration of the {τ + 1}th EM step are given as follows: E Step: As step τ, calculate the expected number of recombination events associated with D00(α), D01 (β), D10(γ), D11(δ) for the (j1j2j3)th progeny genotype (where j1, j2 and j3 denote the progeny genotypes of the three individual markers, respectively): Calculate , , , and , (k = 1,2,3) using where nj1j2j3 denote the number of progeny with a particular three-marker genotype, hj1j2j3, , , , , p1(j1j2j3), p2(j1j2j3), q1(j1j2j3) and q2(j1j2j3) are the (j1j2j3)th element of matrices H, D00, D01, D10, D11, P1, P2, Q1 and Q2, respectively. M Step: Calculate , , and using the equations, The E and M steps are repeated among Eqs. (19) – (32) until d00, d01, d10 and d11 converge to values with satisfied precision. From the MLEs of the g's, the MLEs of recombination fractions r12, r13 and r23 can be obtained according to the invariance property of the MLEs. Model for partial informative markers Consider three partially informative markers with the numbers of distinguishable pheno-types denoted by b1, b2 and b3, respectively. Define is a (b1b2 × b3) matrix of genotype frequencies for three partially informative markers. Similarly, we define , and . Using the procedure described in Section (2.2), we implement the EM algorithm to estimate the MLEs of the recombination fractions among the three partially informative markers. m-point analysis Three-point analysis considering the dependence of recombination events among different marker intervals can be extended to perform the linkage analysis of an arbitrary number of markers. Suppose there are m ordered markers on a linkage group. The joint genotype probabilities of the m markers form a (4m-1 × 4)-dimensional matrix. There are 2m-1 × 2m-1 such probability matrices each corresponding to a different parental diplotype combination. The reasonable estimates of the recombination fractions rely upon the characterization of a most likely parental diplotype combination based on the multilocus likelihood values calculated. The m-marker joint genotype probabilities can be expressed as a function of the probability of whether or not there is a crossover occurring between two adjacent markers, where l1, l2, ..., lm-1 are the indicator variables denoting the crossover event between markers and , markers and , ..., and markers and , respectively. An indicator is defined as 1 if there is a crossover and 0 otherwise. Because each indicator can be taken as one or zero, there are a total of 2m-1 D's. The occurring probability of interval-specific crossover can be estimated using the EM algorithm. In the E step, the expected number of interval specific crossovers is calculated (see Eqs. (19) – (22) for three-point analysis). In the M step, an explicit equation is used to estimate the probability . The MLEs of are further used to estimate m(m - 1)/2 recombination fractions between all possible marker pairs. In m-point analysis, parental diplotypes and gene orders can be incorporated in the model. Monte Carlo simulation Simulation studies are performed to investigate the statistical properties of our model for simultaneously estimating linkage, parental diplotype and gene order in a full-sib family derived from two outbred parents. Suppose there are five markers of a known order on a chromosome. These five markers are segregating differently in order, 1:1:1:1, 1:2:1, 3:1, 1:1 and 1:1:1:1. The diplotypes of the two parents for the five markers are given in Table 1 and using these two parents a segregating full-sib family is generated. In order to examine the effects of parameter space on the estimation of linkage, parental diplotype and gene order, the full-sib family is simulated with different degrees of linkage (r = 0.05 vs. 0.20) and different sample sizes (n = 100 vs. 200). As expected, the estimation precision of the recombination fraction depends on the marker type, the degree of linkage and sample size. More informative markers, more tightly linked markers and larger sample sizes display greater estimation precision of linkage than less informative markers, less tightly linked markers and smaller sample sizes (Tables 1 and 2). To save space, we do not give the results about the effects of sample size in the tables. Our model can provide an excellent estimation of parental linkage phases, i.e., parental diplotype, in two-point analysis. For example, the MLE of the probability (p or q) of parental diplotype is close to 1 or 0 (Table 1), suggesting that we can always accurately estimate parental diplotypes. But for two symmetrical markers (e.g., markers and in this example), two sets of MLEs, = 1, = 0 and = 0, = 1, give an identical likelihood ratio test statistic. Thus, two-point analysis cannot specify parental diplotypes for symmetrical markers even when the two parents have different diplotypes. The estimation precision of linkage can be increased when a three-point analysis is performed (Table 2), but this depends on different marker types and different degrees of linkage. Advantage of three-point analysis over two-point analysis is more pronounced for partially than fully informative markers, and for less tightly than more tightly linked markers. For example, the sampling error of the MLE of the recombination fraction (assuming r = 0.20) between markers and from two-point analysis is 0.0848, whereas this value from a three-point analysis decreases to 0.0758 when combining fully informative marker but increases to 0.0939 when combining partially informative marker . The three-point analysis can clearly determine the diplotypes of different parents as long as one of the three markers is asymmetrical. In our example, using either asymmetrical marker or , the diplotypes of the two parents for two symmetrical markers ( and ) can be determined. Our model for three-point analysis can determine a most likely gene order. In the three-point analyses combining markers , markers and marker , the MLEs of the probabilities of gene order are all almost equal to 1, suggesting that the estimated gene order is consistent with the order hypothesized. To demonstrate how our linkage analysis model is more advantageous over the existing models for a full-sib family population, we carry out a simulation study for linked dominant markers. In two-point analysis, two different parental diplotype combinations are assumed: (1) [aa] [oo] × [aa] [oo] (cis × cis) and (2) [ao] [oa] × [ao] [oa] (trans × trans). The MLE of the linkage under combination (2), in which two dominant alleles are in a repulsion phase, is not as precise as that under combination (1), in which two dominant non-alleles are in a coupling phase [12]. For a given data set with unknown linkage phase, the traditional procedure for estimating the recombination fraction is to calculate the likelihood values under all possible linkage phase combinations (i.e., cis × cis, cis × trans, trans × cis and trans × trans). The combinations, cis × cis and trans × trans, have the same likelihood value, with the MLE of one combination being equal to the subtraction of the MLE of the second combination from 1. The same relationship is true for cis × trans and trans × cis. A most likely phase combination is chosen corresponding to the largest likelihood and a legitimate MLE of the recombination fraction (r ≤ 0.5) [10]. For our data set simulated from [aa] [oo] × [aa] [oo], one can easily select cis × cis as the best estimation of phase combination because it corresponds to a larger likelihood and a smaller (Table 3). Our model incorporating the parental diplotypes can provide comparable estimation precision of the linkage for the data from [aa] [oo] × [aa] [oo] and precisely determine the parental diplotypes (see the MLEs of p and q; Table 3). Our model has great advantage over the traditional model for the data derived from [ao] [oa] × [ao] [oa]. For this data set, the same likelihood was obtained under all possible four diplotype combinations (Table 3). In this case, one would select cis × trans or trans × cis because these two phase combinations are associated with a lower estimate of r. But this estimate of r (0.0393) is biased since it is far less than the value of 0.20 hypothesized. Our model gives the same estimation precision of the linkage for the data derived from [ao] [oa] × [ao] [oa] as obtained when the analysis is based on a correct diplotype combination (Table 3). Also, our model can precisely determine the parental diplotypes ( = = 0 ). Table 3 Comparison of the estimation of the linkage and parental diplotype between two dominant markers in a full-sib family of n = 100 from the traditional and our model Traditional model Our model cis × cis cis × trans trans × cis trans × trans Data simulated from cis × cis Correct diplotype combination Correct Incorrect Incorrect Incorrect Log-likelihooda -46.2 -92.3 -92.3 -46.2 under each diplotype combination 0.1981 ± 0.0446 0.5000 ± 0.0000 0.5000 ± 0.0000 0.8018 ± 0.0446 Estimated diplotype combination Selected under correct diplotype combination 0.1981 ± 0.0446 0.1982 ± 0.0446 Diplotype probability for parent P () 1.0000 ± 0.0000 Diplotype probability for parent Q () 1.0000 ± 0.0000 Data simulated from trans × trans Correct diplotype combination Incorrect Incorrect Incorrect Correct Log-likelihooda -89.6 -89.6 -89.6 -89.6 under each diplotype combination 0.8573 ± 0.1253 0.0393 ± 0.0419 0.0393 ± 0.0419 0.1426 ± 0.1253 Estimated diplotype combination Selected Selected under correct diplotype combination 0.1426 ± 0.1253 0.1428 ± 0.1253 Diplotype probability for parent P () 0.0000 ± 0.0000 Diplotype probability for parent Q () 0.0000 ± 0.0000 aThe log-likelihood values given here are those from one random simulation for each diplotype combination by the traditional model. In three-point analysis, we examine the advantage of implementing linkage analysis with gene orders. Three dominant markers are assumed to have two different parental diplotypes combinations: (1) [aaa] [ooo] × [aaa] [ooo] and (2) [aao] [ooa] × [aao] [ooa]. The traditional approach is to calculate the likelihood values under three possible gene orders and choose one of a maximum likelihood to estimate the linkage. Under combination (1), a most likely gene order can be well determined and, therefore, the recombination fractions between the three markers well estimated, because the likelihood value of the correct order is always larger than those of incorrect orders (Table 4). However, under combination (2), the estimates of linkage are not always precise because with a frequency of 20% gene orders are incorrectly determined. The estimates of r's will largely deviate from their actual values based on a wrong gene order (Table 4). Our model incorporating gene order can provide the better estimation of linkage than the traditional approach, especially between those markers with dominant alleles being in a repulsion phase. Furthermore, a most likely gene order can be determined from our model at the same time when the linkage is estimated. Table 4 Comparison of the estimation of the linkage and gene order between three dominant markers in a full-sib family of n = 100 from the traditional and our model MLE Traditional model Our model Data stimulated from [aaa] [ooo] × [aaa] [ooo] Correct gene order Correct Incorrect Incorrect Estimated best gene order (%a) 100 0 0 0.2047 ± 0.0422 0.2048 ± 0.0422 0.1980 ± 0.0436 0.1985 ± 0.0434 0.3245 ± 0.0619 0.3235 ± 0.0618 0.9860 ± 0.0105 0.0060 ± 0.0071 0.0080 ± 0.0079 Data simulated from [aao] [ooa] × [aao] [ooa] Correct gene order Correct Incorrect Incorrect Estimated best gene order (%a) 80 11 9 0.1991 ± 0.0456 0.8165 ± 0.1003 0.9284 ± 0.0724 0.2104 ± 0.0447 0.1697 ± 0.0907 0.8220 ± 0.0338 0.1636 ± 0.0608 0.2073 ± 0.0754 0.3218 ± 0.0755 0.2703 ± 0.0586 0.7821 ± 0.0459 0.2944 ± 0.0929 0.9952 ± 0.0058 0.0045 ± 0.0058 0.0003 ± 0.0015 aThe percents of a total of 200 simulations that have a largest likelihood for a given gene order estimated from the traditional approach. In this example used to examine the advantage of implementing gene orders, known linkage phases are assumed. Our model is further used to perform joint analyses including more than three markers. When the number of markers increases, the number of parameters to be estimated will be exponentially increased. For four-point analysis, the speed of convergence was slow and the accuracy and precision of parameter estimation have been affected for a sample size of 200 (data not shown). According to our simulation experience, the improvement of more-than-three-point analysis can be made possible by increasing sample size or by using the estimates from two- or three-point analysis as initial values. A worked example We use an example from published literature [18] to demonstrate our unifying model for simultaneous estimation of linkage, parental diplotype and gene order. A cross was made between two triple heterozygotes with genotype AaVvXx for markers , and . Because these three markers are dominant, the cross generates 8 distinguishable genotypes, with observations of 28 for A-/V-/X-, 4 for A-/V-/xx, 12 for A-/vv/X-, 3 for A-/vv/xx, 1 for aa/V-/X-, 8 for aa/V-/xx, 2 for aa/vv/X- and 2 for aa/vv/xx. We first use two-point analysis to estimate the recombination fractions and parental diplotypes between all possible pairs of the three markers. The recombination fraction between markers and is , whose the estimated parental diplotypes are [Av] [aV] × [AV] [av] or [AV] [av] × [Av] [aV]. The other two recombination fractions and the corresponding parental displotypes are estimated as , [Vx] [vX] × [VX] [vx] or [VX] [vx] × [Vx] [vX] and , [AX] [ax] × [AX] [ax], respectively. From the two-point analysis, one of the two parents have dominant alleles from markers and are repulsed with the dominant alleles from marker . Our subsequent three-point analysis combines parental diplotypes and gene orders to estimate the linkage between these three dominant markers. The estimated gene order is . The MLEs of the recombination fractions are , and . The parental diplotype combination is [XAV] [xav] × [XAv] [xaV] or [XAv] [xaV] × [XAV] [xav]. The three-point analysis for these three markers by Ridout et al. [18] led to the estimates of the three recombination fractions all equal to 0.20. But their estimates may not be optimal because the effect of gene order on was not considered. Discussion Several statistical methods and software packages have been developed for linkage analysis and map construction in experimental crosses and well-structured pedigrees [2-6], but these methods need unambiguous linkage phases over a set of markers in a linkage group. For outcrossing species, such as forest trees, it is not possible to know exact linkage phases for any of two parents that are crossed to generate a full-sib family prior to linkage analysis. This uncertainty about linkage phases makes linkage mapping in outcrossing populations much more difficult than that in phase-known pedigrees [7,9]. In this article we present a unifying model for simultaneously estimating the linkage, parental diplotype and gene order in a full-sib family derived from two outbred parents. As demonstrated by simulation studies, our model is robust to different parameter space. Compared to the traditional approaches that calculate the likelihood values separately under all possible linkage phases or orders [9,10,18], our approach is more advantageous in three aspects. First, it provides a one-step analysis of estimating the linkage, parental diplotype and gene order, thus facilitating the implementation of a general method for analyzing any segregating type of markers for outcrossing populations in a package of computer program. For some short-generation-interval outcrossing species, we can obtain marker information from grandparents, parents and progeny. The model presented here allow for the use of marker genotypes of the grandparents to derive the diplotype of the parents. Second, our model for the first time incorporates gene ordering into a unified linkage analysis framework, whereas most earlier studies only emphasized on the characterization of linkage phases through a multilocus likelihood analysis [11,14,15]. Instead of a comparative analysis of different orders, we proposed to determine a most likely gene order by estimating the order probabilities. Third, and most importantly, our unifying approach can significantly improve the estimation precision of the linkage for dominant markers whose alleles are in repulsion phase. Previous analyses have indicated that the estimate of the linkage between dominant markers in a repulsion phase is biased and imprecise, especially when the linkage is not strong and when sample size is small [12]. There are two reasons for this: (1) the linkage phase cannot be correctly determined, and/or (2) there is a fairly high possibility (20%) of detecting a wrong gene order. Our approach provides more precise estimates of the recombination fraction because correct parental diplotypes and a correct gene order can be determined. Our approach will be broadly useful in genetic mapping of outcrossing species. In practice, a two-point analysis can first be performed to obtain the pairwise estimates of the recombination fractions and using this pairwise information markers are grouped based on the criteria of a maximum recombination fraction and minimum likelihood ratio test statistic [2]. The parental diplotypes of markers in individual groups are constructed using a three-point analysis. With a limited sample size available in practice, we do not recommend more-than-three-point analysis because this would bring too many more unknown parameters to be precisely estimated. If such an analysis is desirable, however, one may use the results from these lower-point analyses as initial values to improve the convergence rate and possibly the precision of parameter estimation. In any case, our two- and three-point analysis has built a key stepping stone for map construction through two approaches. One is the least-squares method, as originally developed by Stam [5], that can integrate the pairwise recombination fractions into reconstruction of multilocus linkage map. The second is to use the hidden Markov chain (HMC) model, first proposed by Lander and Green [2], to construct genetic linkage maps by treating map construction as a combinatorial optimization problem. The simulated annealing algorithm [19] for searching for optima of the multilocus likelihood function need to be implemented for the HMC model. A user-friendly package of software that is being written by the senior author will implement two- and three-point analyses as well as the algorithm for map construction based on the estimates of pairwise recombination fractions. This software will be online available to the public. Our maximum likelihood-based approach is implemented with the EM algorithm. We also incorporate the Gibbs sampler [20] into the estimation procedure of the mixture model for the linkage characterizing different parental diplotypes and gene orders of different markers. The results from the Gibbs sampler are broadly consistent with those from the EM algorithm, but the Gibbs sampler is computationally more efficient for a complicated problem than the EM algorithm. Therefore, the Gibbs sampler may be particularly useful when our model is extended to consider multiple full-sib families in which the parents may be selected from a natural population. For such a multi-family design, some population genetic parameters describing the genetic structure of the original population, such as allele frequencies and linkage disequilibrium, should be incorporated and estimated in the model for linkage analysis. It can be anticipated that the Gibbs sampler will play an important role in estimating these parameters simultaneously along with the linkage, linkage phases, and gene order. Authors' contributions QL derived the genetic and statistical models and wrote computer programs. YHC participated in the derivations of models and statistical analyses. RLW conceived of ideas and algorithms, and wrote the draft. All authors read and approved the final manuscript. Acknowledgements We thank two anonymous referees for their constructive comments on the manuscript. This work is partially supported by a University of Florida Research Opportunity Fund (02050259) and a University of South Florida Biodefense Grant (7222061-12) to R. W. The publication of this manuscript is approved as Journal Series No. R-10073 by the Florida Agricultural Experiment Station. ==== Refs Flint J Mott R Finding the molecular basis of quantitative traits: Successes and pitfalls Nat Rev Genet 2001 2 437 445 11389460 10.1038/35076585 Lander ES Green P Construction of multilocus genetic linkage maps in humans Proc Natl Acd Sci USA 1987 84 2363 2367 Lander ES Green P Abrahamson J Barlow A Daly MJ Lincoln SE Newburg L MAPMAKER: an interactive computer package for constructing primary genetic linkage maps of experimental and natural populations Genomics 1987 1 174 181 3692487 Green P Falls K Crooks S Documentation for CRIMAP, version 2.4 Washington Univ School of Medicine, St Louis, MO 1990 Stam P Construction of integrated genetic linkage maps by means of a new computer package: JOINMAP Plant J 1993 3 739 744 10.1046/j.1365-313X.1993.03050739.x Matise TC Perlin M Chakravarti A Automated constrcution of genetic linkage maps using an expert system (MULTIMAP): a human genome linkage map Nat Genet 1994 6 384 390 8054979 Hitter E Gebhardt C Salamini F Estimation of recombination frequencies and construction of RFLP linkage maps in plants from crosses between heterozygous parents Genetics 1990 125 645 654 1974227 Arus P Olarte C Romero M Vargas F Linkage analysis of 10 isozyme genes in Fl segregating almond progenies J Am Soc Hort Sci 1994 119 339 344 Ritter E Salamini F The calculation of recombination frequencies in crosses of allogamous plant species with applications to linkage mapping Genet Res 1996 67 55 65 Maliepaard C Jansen J van Ooijen JW Linkage analysis in a full-sib family of an outbreeding plant species: overview and consequences for applications Genet Res 1997 70 237 250 10.1017/S0016672397003005 Wu RL Ma CM Painter I Zeng ZB Simultaneous maximum likelihood estimation of linkage and linkage phases in outcrossing populations Theor Pop Biol 2002 61 349 363 12027621 10.1006/tpbi.2002.1577 Wu RL Ma CM Wu SS Zeng ZB Linkage mapping of sex-specific differences Genet Res 2002 79 85 96 11974606 10.1017/S0016672301005389 Grattapaglia D R Sederoff Genetic linkage maps of Eucalyptus grandis and Eucalyptus urophylla using a pseudo-testcross: mapping strategy and RAPD markers Genetics 1994 137 1121 1137 7982566 Ling S Constructing genetic maps for outbred experimental crosses PhD thesis, University of California, Berkeley, CA 1999 Butcher PA Williams ER Whitaker D Ling S Speed TP Moran CF Improving linkage analysis in outcrossed forest trees – an example from Acacia mangium Theor Appl Genet 2002 104 1185 1191 10.1007/s00122-001-0820-1 Dempster AP Laird NM Rubin DB Maximum likelihood from incomplete data via EM algorithm J Roy Stat Soc Ser B 1977 39 1 38 Haldane JBS The combination of linkage values and the calculation of distance between the loci of linked factors J Genet 1919 8 299 309 Ridout MS Tong S Vowden CJ Tobutt KR Three-point linkage analysis in crosses of allogamous plant species Genet Res 1998 72 111 121 10.1017/S0016672398003371 van Laarhoven PJM Aarts EHL Simulated Annealing: Theory and Application 1987 D. Reide Publishing Co., Dordrecht, The Netherlands Casella G Empirical Bayes Gibbs sampling Biostatistics 2001 2 485 500 12933638 10.1093/biostatistics/2.4.485

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BMC Genet

10.1186/1471-2156-5-20

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==== Front BMC GenomicsBMC Genomics1471-2164BioMed Central London 1471-2164-5-471526088910.1186/1471-2164-5-47Research ArticleA molecular 'signature' of primary breast cancer cultures; patterns resembling tumor tissue Dairkee Shanaz H 1shanaz@cooper.cpmc.orgJi Youngran 2yji@stanford.eduBen Yong 1ben@cooper.cpmc.orgMoore Dan H 1moore@cooper.cpmc.orgMeng Zhenhang 1zhenhang@cooper.cpmc.orgJeffrey Stefanie S 2ssj@stanford.edu1 California Pacific Medical Center, 2330 Clay Street, San Francisco, CA 94115-1932, USA2 Department of Surgery, Stanford University School of Medicine, MSLS Building, Room P214, 1201 Welch Road, Stanford, CA 94305-5494, USA2004 19 7 2004 5 47 47 2 3 2004 19 7 2004 Copyright © 2004 Dairkee et al; licensee BioMed Central Ltd.2004Dairkee et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background To identify the spectrum of malignant attributes maintained outside the host environment, we have compared global gene expression in primary breast tumors and matched short-term epithelial cultures. Results In contrast to immortal cell lines, a characteristic 'limited proliferation' phenotype was observed, which included over expressed genes associated with the TGFβ signal transduction pathway, such as SPARC, LOXL1, RUNX1, and DAPK1. Underlying this profile was the conspicuous absence of hTERT expression and telomerase activity, a significant increase in TβRII, its cognate ligand, and the CDK inhibitor, p21CIP1/WAF1. Concurrently, tumor tissue and primary cultures displayed low transcript levels of proliferation-related genes, such as, TOP2A, ANKT, RAD51, UBE2C, CENPA, RRM2, and PLK. Conclusions Our data demonstrate that commonly used immortal cell lines do not reflect some aspects of tumor biology as closely as primary tumor cell cultures. The gene expression profile of malignant tissue, which is uniquely retained by cells cultured on solid substrates, could facilitate the development and testing of novel molecular targets for breast cancer. ==== Body Background In breast cancer, cell based experiments are largely conducted with a few spontaneously arising cell lines from late stages of disease that demonstrate unlimited proliferation (immortalization). However, the breadth of tumor heterogeneity and early stages of breast tumorigenesis remain under represented in such assays. We, and others have adapted tissue processing and culture conditions to enable the selective isolation and expansion of tumor cell populations from primary breast cancer [1-9]. Closely reflecting the biological heterogeneity and relatively slower growth rate of malignant cells in primary tumor tissue [10], in vitro tumor cell populations are highly variable at the microscopic level and generally require long intervals between passages. The vast majority of such cultures (>90%) display a finite mitotic lifespan. While molecular changes underlying growth cessation in non-malignant breast epithelial cultures are well studied [reviewed in [11]], barriers to the continued proliferation of tumor-derived cultures remain undetermined. In contradistinction to previous reports on the characteristics of rare immortal cell lines developed from primary tumors [4,5,7,8,12], we have focused on early passage tumor cultures (that may not necessarily culminate as immortal cell lines). This approach encompasses a broader range of disease since <10% of primary breast tumors spontaneously develop into immortal cell lines. Although limited direct comparison of primary breast tumor tissue and corresponding short-term cultures has assisted in authenticating the malignant origin of tumor-derived cultures [1-3,9], relatively little is known regarding the degree of phenotypic and functional concordance between malignant epithelial populations in human breast tissue and their counterparts in vitro. In depth comparative analysis of such isogenic malignant cell populations could provide important insights regarding cellular pathways that function independently of environmental constraints, as well as the genome wide consequences of constitutive growth arrest of breast tumor cells widely encountered in laboratory dishes. Here we describe a comprehensive comparison of matched samples of primary breast carcinoma tissue, and early passage tumor cultures. We have used cDNA microarray-based global gene expression profiling to determine common molecular phenotypes of tumor tissue and tumor-derived epithelial cultures, which distinguish them from cancerous and non-cancerous immortal cell lines. Results In order to ensure the propagation of tumor epithelium without apparent contamination with fibroblasts and other cellular components, previously described methods including the selective release of nests of malignant cells from the connective tissue, were used [2,3]. As illustrated in Figure 1A, the characteristic epithelial morphology, and microscopic heterogeneity between tumor cultures from independent cases was observed. To confirm that these cultures represented pure populations of epithelial cells, indirect cytokeratin immunostaining was performed (Figure 1A). Clinical information and additional cell culture details are listed in Table 1. Figure 1 A. Microscopic phenotype of primary tumor tissue and corresponding tumor-derived epithelial and stromal cell cultures. (1–3) – H & E-stained frozen sections showing histology of representative cases processed for RNA isolation and cell culture. Case number 061T – 1; 066T – 2; 068T – 3. Note abundant tumor cells in the samples. (4–6) – Early passage epithelial cultures; brightfield, 100× magnification. Note morphological variation between cultures in the context of an epithelial phenotype. (7–9) – abundant cytokeratin expression in the cytoplasm of cultured primary tumor cells analyzed by indirect immunofluorescence. Magnification – 400×. (10–12) – tumor-derived fibroblast cultures; brightfield, 100× magnification. Note morphological distinction between epithelial and stromal cells isolated from the same tissue sample. B – E. cDNA-based gene expression profiles of tumor tissue and tumor derived epithelial cultures. Rows represent genes, and columns represent samples. B, C – unsupervised two-dimensional hierarchical clustering of 17 samples. B – cluster shows genes under expressed in primary tumor tissue and tumor cultures compared to immortal cell lines. C – cluster shows genes over expressed in primary tumor cultures and tumor tissue compared to immortal cell lines. D, E – Gene expression patterns, which distinguish between group 1, consisting of immortal cell lines, and group 2, consisting of primary tumor tissue and tumor cultures. D – Results of SAM analysis showing a thumbnail of 681 differentially expressed genes. E – SAM-identified genes which are in common with the cluster in panel B are shown by red vertical bar, and with the cluster in panel C are shown by green vertical bars. Color scale indicates expression level. Table 1 Clinical characteristics of Primary Tumors used for Gene Expression Analysis Primary Tumor Cultures Sample # Sample ID Age TNM Stage Tumor Grade Tumor histology ER status Cell culture passage at RNA isolation 1 022T NA NA 1 IDC NA 3 2 044T 50 NA 3 IDC Neg 2 3 047T 79 II 2 IDC Pos 5 4 054T 59 IV 3 IDC Pos 8, 12 5 061T* 62 III 2 ILC Pos 5, 6 6 066T* 47 II 2 IDC NA 6, 7 7 068T* 52 II 1 IDC Pos 5, 6 8 071T NA II 3 IDC NA 3 9 076T 51 III 2 IDC Pos 2 10 257T 41 IIB 3 IDC Neg 8 11 672T 60 II 3 IDC Neg 5 12 701T 59 I 1 IDC Pos 7 13 713T 77 II 3 IDC+ILC Pos 5, 7 14 1555T 38 NA 2 ILC NA 3, 4 15 1569T NA NA NA IDC NA 3, 4 16 1570T 66 IIA 2 IDC+ILC Pos 2 17 1599T* 64 I 2 IDC NA 3 18 1607T 58 I 1 IDC NA 5 19 1617T 64 III 2 IDC Pos 2 20 1620T 70 III 3 IDC Pos 2 21 1625T 80 IIB 3 IDC Pos 2 * Matched tissue samples analyzed by cDNA microarrays NA – not available; IDC – invasive ductal carcinoma; ILC – invasive lobular carcinoma ER – estrogen receptor; Neg – negative; Pos – positive Concordant aspects of global gene expression in breast cancer tissue and tumor-derived cultures Seventeen RNA samples were analyzed by cDNA microarrays. These were comprised of 4 cases of primary breast tumor tissue and 1–2 matched tumor cultures, 2 additional unmatched tumor cultures, and 4 immortal breast cell lines. Cell lines were selected to represent estrogen receptor (ER) positive (T47D) and ER negative (SKBR3, BT20) tumors, and non-cancerous breast epithelium (ENUt7, ref. [13]). Unsupervised clustering analysis of 7362 clones (4743 unique genes/ESTs) grouped the samples into three separate clusters representing immortal cell lines, tumor tissue, and tumor cultures. Figure 1B displays a cluster of genes, which were over expressed in immortal cell lines but under expressed in tumor tissue and tumor cultures, while Figure 1C displays a 'mirror image' gene expression pattern (under expressed genes in immortal cell lines, which were over expressed in tumor tissue and tumor cultures). The clusters selected for illustration represent ~90% gene correlation. The entire data set displayed additional clusters [Figure S1 – see http://genome-www.stanford.edu/breast_cancer/PTCC/]. Comparisons of large data sets as described above frequently result in "significant" patterns of gene expression by chance alone. We employed the Significance Analysis of Microarrays (SAM) for independently verifying genes that are differentially expressed between classes or groups of samples. SAM analysis identified 930 clones, representing 681 unique genes/ESTs, whose expression was significantly (>2-fold) different between group 1 comprised of immortal cell lines, and group 2 comprised of tumor tissue and tumor cultures (0.05% false discovery rate). A full list of the differentially expressed genes is provided in [Table S2 – see http://genome-www.stanford.edu/breast_cancer/PTCC/]. As expected on the basis of the similarity in gene expression observed between tumor tissue and tumor cultures in the unsupervised array data (Figure 1B,1C), these clusters were also present in the SAM profile (Figure 1D). As shown in Figure 1E, genes upregulated in immortal cell lines (indicated by red vertical bar) reflecting significantly shorter doubling times (for example, RFC4, CENPA, TOP2A, CCNA, MCM7, PCNA, CDC2) were primarily those associated with the 'proliferation' cluster described by Ross et al [14]. In contrast, upregulated transcripts in tumor tissue and tumor cultures (Figure 1E, indicated by green vertical bar) included genes involved in epithelial differentiation (MAL, MAFB, RUNX1, KRT5), in the induction of apoptosis (DAPK1), and in tumor angiogenesis, and extravasation (SPARC) (Gene Ontology – GO annotations, ref [15]). Primary epithelial cell cultures, in contrast to fibroblasts and rapidly growing cell lines, undergo rapid growth arrest in 10% fetal calf serum (FCS). This is why we, and others have propagated cultures of primary tumor epithelium in 0–5% FCS (1–9). Immortal cell lines, however, grow optimally in 10% FCS; lower concentrations retard growth. Therefore, to optimize growth conditions for both, 2% FCS was chosen for primary tumor cultures and 10% FCS for cell lines. It is conceivable that an increased concentration of FCS may account for differences in gene expression between primary tumor cultures and immortalized cell lines. In this case, one would expect increased proliferation in the primary tumor cultures at 10% FCS, when in fact, growth is severely inhibited by this approach. As summarized in Table 2, based on microarray expression data of 38,999 cDNA clones, the average correlation between matched tumor tissue and short-term tumor cultures (7 sets) was 0.41 (sd = 0.03) in contrast to 0.10 (sd = 0.09) between tumor tissue and immortal cell lines (16 pairs). These correlation coefficients differed significantly in a Mann-Whitney rank sum test (p = 0.007) demonstrating that the gene expression profile of tumor tissue was more consistent with that of the corresponding tumor culture than it was with any of the immortal cell lines tested. Table 2 Pair wise correlations between primary tumors, matched epithelial cultures, and immortal breast epithelial cell lines Matched Primary Tumor Pair Immortal Breast Epithelial Cell Lines Tissue Cell Culture ENUt7 SKBR3 BT20 T47D R correlation 1599T 1599TC 0.31 0.05 0.07 0.01 0.23 061T 061TC1 0.44 0.10 0.03 0.03 0.24 061TC2 0.43 066T 066TC1 0.44 0.16 0.02 0.03 0.20 066TC2 0.39 068T 068TC1 0.50 0.12 0.05 0.00 0.27 068TC2 0.54 Determinants of replicative arrest in primary breast tumor-derived cultures Towards the determination of specific molecular changes underlying the finite proliferative lifespan in tumor cultures, gene expression analysis, by QRT-PCR, was conducted on an expanded set of 39 samples comprised of multiple early passage epithelial cultures obtained from 16 primary breast cancers, 8 cases of normal breast epithelial organoids and, 12 immortal breast epithelial cell lines. As noted above, since genes in the proliferation cluster displayed minimal expression in primary tumor cultures, first we considered the possibility of growth arrest due to a lack of telomerase activity and subsequent telomeric attrition. The relative expression of hTERC and hTERT subunits of telomerase, encoding the structural RNA component, and the component with reverse transcriptase activity, respectively, was measured. While commonly used immortal cell lines (T47D, MDA231) displayed several-fold higher transcript levels for hTERT, undetectable to minimal levels were observed in 6/8 independent primary tumor cultures (1599T, 713T, 1569T, 1570T, 1617T, 1620T). The primary tumor culture with the highest relative expression of hTERT (257T) has developed into an immortal cell line (Figure 2A). Figure 2 A. QRT-PCR analysis of hTERT and hTERC in primary tumor cultures compared to levels in normal breast organoids, matched fibroblasts, and immortal breast epithelial cell lines (T47D, MDA231, and ENUt7). The Y-axis is minimized to display the range of relative gene expression. The highest hTERT expression level, denoted by the asterisk, was 22-fold (sample 257T). B. TRAP assay measurement of telomerase activity shown with, and without heat inactivation of cell lysates. Extracts equivalent to 1000 cells are displayed. IC – internal PCR control. For sample 054T, 2 independent fractions of the tumor are shown; SP – mechanically dissociated spillage, DIG – enzymatically digested tissue. To confirm the functional impact of hTERC and hTERT down regulation, telomerase activity was measured directly by the TRAP assay. As expected, primary cultures with detectable transcript levels, and immortal cell lines of cancerous and non-cancerous origin displayed significant telomerase activity, while those tumor cultures that did not display gene expression showed no activity. In the primary tumor sample, 257T, robust telomerase activity was found as early as passage 8. Similarly, telomerase activity was detectable in early passage epithelial cultures propagated from cells isolated by mechanical dissociation (SP – spillage), or enzymatic digestion (DIG) of the tumor sample 054T (Figure 2B). In the next step towards identifying the determinants of replicative arrest, primary tumor cultures were compared with immortal cell lines for relative expression of genes associated with the negative regulation of the cell cycle in general, and with epithelial cell proliferation in particular. This analysis included 9 candidate genes in 3 signaling pathways: (1) members of the CIP/KIP family of cyclin-dependent kinase inhibitors (CDKIs), p21CIP1/WAF1, p27KIP1, and p57KIP2 (2) members of the INK family of CDKIs, p15INK4B, and p16INK4A (3) members of the TGF-β family, TGFβI, TGFβII and the signaling receptors, TβRI, and TβRII. As illustrated in Figure 3A, we observed that in 10/12 breast cancer cell lines, p21CIP1/WAF1 levels were 2 to138 fold lower than steady state levels in normal breast epithelium. In contrast, 4/20 primary tumor culture samples showed this range of p21CIP1/WAF1 expression (p = 0.0003). For the CDKIs, p27KIP1, and p57KIP2, several fold decrease in gene expression was observed in all primary tumor cultures and most immortal cell lines as well (p = 0.04 and 0.69, respectively). Similarly, no significant differences were apparent for p15INK4B, and p16INK4A gene expression in the two groups (p = 0.07 and 0.39, respectively). For members of the TGF-β family, while significant differences were not observed in the expression of TGFβI and TβRI, a median increase of 2 fold and 4 fold were found in the expression of TGFβII and TβRII respectvely. In contrast, immortal cell lines, showed a median decrease of 7-fold for TGFβII and 4-fold for TβRII (p = 0.0035 and 0.0011, respectively). All p values were derived by the Mann-Whitney test. Figure 3 Comparative QRT-PCR analysis of genes encoding negative regulators of cell proliferation in primary tumor cultures and immortal cell lines. A – Expression levels of individual genes represented as fold increase or decrease over gene expression in normal breast organoids (average of 8 independent reduction mammoplasty cases). Data shown are averages of triplicate measurements. Dots represent immortal cell lines (red) and primary tumor cultures (black) shown in panels B and C. B – multivariate analysis of data in A displayed as a hierarchical clustering dendrogram. The scale shows the distance between groups comprised of normal breast, primary tumor cultures, and immortal cell lines. For samples 1569T, 1555T, 713T, and 054T, gene expression was analyzed in epithelial cells at 2 different passages in culture (passage number indicated as 3', 4', 5' etc.) C – a plot of 3 principal components (U1, U2, and U3) of 9-dimensional space, representing the 9 genes evaluated in samples in panels A and B. Based on its level of gene expression, a place is assigned to each cell sample in this space. Data points representing epithelial organoids from the normal breast (pink) appear to be tightly clustered, whereas those representing primary breast tumor cultures (green) and immortal cancer cell lines (blue) show considerable scatter. We used MANOVA to compare expression of the 9 above-mentioned genes in immortal cell lines, primary tumor cultures, and normal breast epithelium. It was apparent that the multivariate means for the 9 genes differed for each of the 3 groups above and that both immortal lines and primary tumor cultures differed from normal breast epithelium (p = 0.0001) as also depicted in the hierarchical clustering dendrogram of these samples (Figure 3B). A 3-D plot of the first three principal components, which together account for 83% of the total variation in expression in the 9-dimensional gene space, is shown in Figure 3C. This display format demonstrates that the three types of cell samples cluster in different parts of the three dimensional space and that primary tumor cultures and immortal cell lines are significantly different from normal breast and from each other in the expression of the negative growth regulators evaluated here (p = 0.0002). The relatively large Wilks' lamda (0.271) for immortal cell lines vs. primary tumor cultures is most likely due to the greater spread of these groups in the 9-dimensional gene space, while normal samples are tightly grouped together. This finding may be related to the heterogeneity between individual tumors. Overall, the genes in the array-based clusters, shown in Figure 1B and 1C, could be categorized as positive or negative regulators of proliferation respectively according to GO annotations. Genes such as, PCNA, CKS1B, TPX2, UBE2C, CDC6, confirmed by the statistically significant analysis of microarray data, SAM, were among the positive proliferation genes differentially expressed by immortal cell lines, and matched tumor tissue/cell culture samples (Figure 1E, also see Table S2 – http://genome-www.stanford.edu/breast_cancer/PTCC/, for full list). Expression levels of negative proliferation genes identified in the SAM data, such as, TβRII, and CDKN1A (p21CIP1/WAF1) were confirmed by QRT-PCR (Figure 3A) Discussion The cDNA microarray analysis of primary breast tumors and their epithelial counterparts propagated in cell culture has revealed close similarities in the expression of several hundred genes. Notably, increased expression of genes deemed to be 'growth limiting' by virtue of their consistent down regulation in immortal cell lines, was observed. The patterns of gene up regulation or down regulation were remarkably consistent in independent immortal lines (including those derived from non cancerous breast epithelial cells) as was the contrasting gene 'signature' in cultures derived from independent cases of breast carcinoma. Together, these observations have led us to conclude that the continuous selection of rapidly proliferating cells culminating in the immortalized phenotype favors the loss of several aspects of gene expression retained by early passage primary tumor cultures. Our data suggests that the limited growth potential of primary tumor cultures results from two major proliferative barriers, (a) telomerase inactivation, potentially leading to telomere attrition, and (b) negative growth signaling by upregulated TGFβ resulting in a significant increase in transcription of the CDKI, p21CIP1/WAF1, consistent with the findings of induction or stabilization of this gene in a variety of immortalized cells exposed to exogenous TGFβ [16,17]. Elevated levels of p21CIP1/WAF1 in turn appear to have a direct impact on telomerase regulation [18]. As expected of slow growing primary breast tumors, in vivo, p21CIP1/WAF1 positive cells are detected in the majority of cases [19]. Also pertinent in this regard is the fact that substrate induced changes in cell shape upregulate TGFβ transcription [20]. Since the promoter region of the TGFβ gene contains a shear stress response element [21,22], it seems likely that TGFβ induction occurs in response to unknown stresses in the in vitro environment and initiates a cascade of growth inhibitory events, including telomerase inactivation. While epithelial cells derived from most primary breast tumors rapidly revert to regulated growth dictated by environmental signals, immortal breast epithelial cells are insensitive to such cues, which may be the underlying basis for their continued selection in vitro. Notably, loss or functional inactivation of the cognate receptor often enables tumor cells in vivo to overcome the growth inhibitory effect of TGFβ early in tumorigenesis, however, during metastatic progression, autocrine TGFβ appears to play a tumor-promoting role, possibly enabling tumor cells to survive significant changes in microenvironment [23]. In this light, induction of TGFβ in response to the in vitro environment in primary breast tumor cultures portrays a critical phase of tumor progression. Additionally, towards the full manifestation of differentiated phenotypes in primary tumor cultures, cell propagation in a three-dimensional growth matrix, pioneered by Bissell and colleagues [24], is imperative. Such studies are currently ongoing in our laboratory. Tumor-derived immortal cell lines generally display robust proliferation and have thus filled an important need for functional cancer cell model systems. While immortal cell lines continue to provide molecular and biological insights regarding proliferation-related hallmarks of malignancy, their functional application as indicators of efficacy in cancer drug development is relevant mostly to rapidly proliferating high-grade tumors. Many breast tumors do not fall into this category, and are not necessarily indolent. Thus, additional targets in diverse gene clusters must be identified for novel drug designing. In fact, such targets could be applicable to tumors at early or late stages as recent studies suggest that genes conferring invasive and/or metastatic characteristics late in progression often become dysfunctional at earlier stages of tumorigenesis [25]. Moreover, since our data demonstrate that primary tumor cultures routinely derived from surgical discard tissue display phenotypic, and most likely functional aspects of breast cancer, they provide a strong rationale for the experimental manipulation of such cells towards revealing the causative role of genetic polymorphisms in cancer susceptibility, an important goal which is unlikely to be fulfilled with currently used model systems. Conclusions This microarray-based analysis demonstrates that epithelial cultures isolated from primary breast tumors retain phenotypes of the malignant tissue, which are eliminated during the selection of rapidly proliferating cell populations that comprise commonly used in vitro model systems. Thus the opportunity for basic and clinical application of functional cells derived from the full range of pathological breast tissue, instead of a few immortal cell lines should not be missed. Methods Clinical specimens and cell culture Pathologically confirmed tumor tissue and non malignant reduction mammoplasty samples were collected as fresh specimens under IRB approved guidelines at the California Pacific Medical Center, San Francisco, Stanford University, and the University of California, San Francisco between 1997 – 2000. Additional tumor samples were obtained from the NCI Cooperative Human Tissue Network. A portion of the tissue was snap frozen and cryopreserved for histological confirmation and nucleic acid isolation prior to cell culture. Tumor samples were processed as previously described [2,3]. A total of 21 independent cultured specimens were used for gene expression analysis. Primary tumor cultures and the non-tumorigenic, ENUt7 cell line were propagated in low calcium MCDB170 medium supplemented with 2% FCS. Breast cancer cell lines were cultured in the recommended growth media supplemented with 10%FCS; MCF7, BT20, MDA231, MDA157 in DME-H21; BT474, CAMA1, T47D, ZR75 in RPMI 1740; MDA435, MDA134, MDA361 in L15. To confirm the epithelial phenotype of primary tumor derived cells, cultures fixed with 50% ethanol: acetone were immunostained with anti pan-cytokeratin, as previously described [1]. RNA isolation, microarray methods and data analysis Frozen tissue was trimmed to yield >90% tumor cell enrichment. Total RNA was extracted with the RNAeasy Mini kit (Qiagen), amplified using an optimized T7 based protocol [26], labeled with Cy5, and hybridized to ~47,000 feature cDNA microarrays as previously described [26,27]. Hybridized arrays were scanned (Axon) and images were analyzed using GenePix® Pro 4.0 software (Axon Instruments). Spots were selected for analysis if signal intensities in both Cy3 and Cy5 channels were 2.5 times higher than background. The arrays were clustered using a hierarchical clustering algorithm [28], which groups genes and samples on the basis of their expression similarities. The results were visualized using TreeView software [29]. The clustering was performed on clones whose expression varied at least 3-fold from the mean in one or more samples and was measurable in over 80% of the samples. Significance Analysis of Microarrays [30,31], used for identifying genes whose expression differed significantly between groups, was performed on data from 38,999 cDNA clones. After the selection of spots 2.5 times over background, and the elimination of clone redundancy, data was retrieved on 930 clones, representing 681 unique genes. Quantitative Real Time PCR (QRT-PCR) RNA samples were treated with RNAse-free DNAse (Roche) to remove genomic DNA, and reverse transcribed. Fifty ng of cDNA was used as template for PCR amplification with specific oligonucleotide primers, (designed using Primer Express 1.5 software). Following denaturation and cycling reactions (40 cycles) the products were analyzed (Applied Biosystems 5700 Sequence Detection System). The cycle number at which the amount of amplified target reached a fixed threshold was designated as the threshold cycle (CT). The higher the initial amount of transcript template, the lower the CT value. For quantitation of gene expression, the target gene value normalized to the expression of an endogenous reference (β actin) was designated as ΔCT. Relative gene expression was calculated by the formula 2-ΔΔCT. ΔΔCT was obtained by subtracting the ΔCT of test sample from the ΔCT of normal breast epithelial fractions, called 'organoids', isolated from mechanically and enzymatically dissociated reduction mammoplasty tissue (average of 8 independent specimens). Telomerase activity Cell lysates prepared from primary tumor cultures, immortal cell lines, and normal breast organoids were analyzed by the telomerase repeat amplification protocol (TRAP) as per manufacturer recommendation (Intergen). Briefly, trypsinized cell pellets were resuspended in lysis buffer at 500 cells/microliter, incubated on ice for 30 minutes, centrifuged at 12,000 × g for 20 mins, and the telomerase containing supernatant used for PCR amplification. Reaction products were resolved in 10% PAGE gels and visualized with SYBR Green-1 (Molecular Probes). Heat inactivated controls were included for each sample. Linearity of the assay was determined with cell dilutions ranging from 100 to 10, 000 cells. Statistical methods We calculated Pearson correlations from the microarray data generated from 38,999 clones to measure similarities among 7 matched tumor tissue: cell culture sample pairs and among 16 tumor tissue: immortal cell line pairs. For QRT-PCR data, multivariate analysis of variance (MANOVA) was used to compare the expression levels of genes involved in negative growth regulation between immortal cell lines, primary tumor cultures, and non malignant breast epithelial cells. Tests for statistical significance were based on Wilks lamda criterion, a multivariate analog of the F-test for univariate analysis of variance (ANOVA), which tests the equality of means. Calculations were made in Data Desk, version 6.2. Principal components for all genes over all the data were computed and S-Plus was used to plot the data for the first 3 principal components. Authors' contributions SHD conceived the study, provided overall direction and coordination to the research, and drafted the manuscript. YJ carried out the microarray analysis. YB carried out QRT-PCR, and other molecular analyses. DHM performed the statistical analysis of data. ZM performed the pathology review and tissue dissection. SSJ participated in the design and analysis of microarray-based experiments and in editing portions of the manuscript. All authors read and approved the final manuscript. Acknowledgements This work was supported by the California Breast Cancer Research Program (8WB-0032). We thank Ms. Stacey Champion for technical assistance, and Ms Susan Overholser for creating web supplement. ==== Refs Dairkee SH Deng G Stampfer MR Waldman FM Smith HS Selective cell culture of primary breast carcinoma Cancer Research 1995 55 2516 2519 7780960 Dairkee SH Paulo EC Traquina P Moore DH Ljung B-M Smith HS Partial enzymatic degradation of stroma allows enrichment and expansion of primary breast tumor cells Cancer Research 1997 57 1590 1596 9108465 Li Z Bustos V Miner J Paulo E Meng Z Zlotnikov G Ljung B-M Dairkee SH Propagation of Genetically Altered Tumor Cells Derived from Fine Needle Aspirates of Primary Breast Carcinoma Cancer Research 1998 58 5271 5274 9850046 Band V Sager R Distinctive traits of normal and tumor-derived human mammary epithelial cells expressed in a medium that supports long-term growth of both cell types Proc Natl Acad Sci U S A 1989 86 1249 1253 2919173 Petersen OW van Deurs B Nielsen KV Madsen MW Laursen I Balslev I Briand P Differential tumorigenicity of two autologous human breast carcinoma cell lines, HMT-3909S1 and HMT-3909S8, established in serum-free medium Cancer Research 1990 50 1257 1270 2153455 Ethier SP Mahacek ML Gullick WJ Frank TS Weber BL Differential isolation of normal luminal mammary epithelial cells and breast cancer cells from primary and metastatic sites using selective media Cancer Research 1993 53 627 635 8425198 Sartor CI Dziubinski ML Yu CL Jove R Ethier SP Role of epidermal growth factor receptor and STAT-3 activation in autonomous proliferation of SUM-102PT human breast cancer cells Cancer Research 1997 57 978 987 9041204 Gazdar AF Kurvari V Virmani A Gollahon L Sakaguchi M Westerfield M Kodagoda D Stasny V Cunningham HT Wistuba II Tomlinson G Tonk V Ashfaq R Leitch AM Minna JD Shay JW Characterization of paired tumor and non-tumor cell lines established from patients with breast cancer Int J Cancer 1998 78 766 774 9833771 10.1002/(SICI)1097-0215(19981209)78:6<766::AID-IJC15>3.0.CO;2-L Speirs V Green AR Walton DS Kerin MJ Fox JN Carleton PJ Desai SB Atkin SL Short-term primary culture of epithelial cells derived from human breast tumours Br J Cancer 1998 78 1421 1429 9836473 Fournier DV Weber E Hoeffken W Growth rate of 147 mammary carcinomas Cancer (Phila) 1980 45 2198 2207 7370960 Yaswen P Stampfer MR Molecular changes accompanying senescence and immortalization of cultured human mammary epithelial cells Int J Biochem Cell Biol 2002 34 1382 1394 12200033 10.1016/S1357-2725(02)00047-X Wistuba II Behrens C Milchgrub S Syed S Ahmadian M Virmani AK Kurvari V Cunningham TH Ashfaq R Minna JD Gazdar AF Comparison of features of human breast cancer cell lines and their corresponding tumors Clin Cancer Res 1998 4 2931 2938 9865903 Li Z Meng Z Sayeed A Shalaby R Ljung B-M Dairkee SH Genome-wide allelotyping of a new in vitro model system reveals early events in breast cancer progression Cancer Research 2002 62 5980 5987 12384566 Ross DT Scherf U Eisen MB Perou CM Rees C Spellman P Iyer V Jeffrey SS Van de Rijn M Waltham M Pergamenschikov A Lee JC Lashkari D Shalon D Myers TG Weinstein JN Botstein D Brown PO Systematic variation in gene expression patterns in human cancer cell lines Nat Genet 2000 24 227 235 10700174 10.1038/73432 Ashburner M Ball CA Blake JA Botstein D Butler H Cherry JM Davis AP Dolinski K Dwight SS Eppig JT Harris MA Hill DP Issel-Tarver L Kasarskis A Lewis S Matese JC Richardson JE Ringwald M Rubin GM Sherlock G Gene ontology: tool for the unification of biology. The Gene Ontology Consortium Nat Genet 2000 25 25 29 10802651 10.1038/75556 Datto MB Li Y Panus JF Howe DJ Xiong Y Wang XF Transforming growth factor beta induces the cyclin-dependent kinase inhibitor p21 through a p53-independent mechanism Proc Natl Acad Sci U S A 1995 92 5545 5549 7777546 Gong J Ammanamanchi S Ko TC Brattain MG Transforming growth factor beta 1 increases the stability of p21/WAF1/CIP1 protein and inhibits CDK2 kinase activity in human colon carcinoma FET cells Cancer Research 2003 63 3340 3346 12810668 Kallassy M Martel N Damour O Yamasaki H Nakazawa H Growth arrest of immortalized human keratinocytes and suppression of telomerase activity by p21WAF1 gene expression Mol Carcinog 1998 21 26 36 9473769 10.1002/(SICI)1098-2744(199801)21:1<26::AID-MC5>3.3.CO;2-P Thor AD Liu S Moore DH 2ndShi Q Edgerton SM p21WAF1/CIP1 expression in breast cancers: associations with p53 and outcome Breast Cancer Res Treat 2000 61 33 43 10930088 10.1023/A:1006455526894 Gutierrez JA Perr HA Mechanical stretch modulates TGF-beta1 and alpha1 (I) collagen expression in fetal human intestinal smooth muscle cells Am J Physiol 1999 277 1074 1080 Kim SJ Glick A Sporn MB Roberts AB Characterization of the promoter region of the human transforming growth factor-beta 1 gene J Biol Chem 1989 264 402 408 2909528 Resnick N Collins T Atkinson W Bonthron DT Dewey CF JrGimbrone MA Jr Platelet-derived growth factor B chain promoter contains a cis-acting fluid shear-stress-responsive element Proc Natl Acad Sci U S A 1993 90 4591 4595 8506304 Derynck R Akhurst RJ Balmain A TGF-beta signaling in tumor suppression and cancer progression Nat Genet 2001 29 117 129 11586292 10.1038/ng1001-117 Petersen OW Ronnov-Jessen L Howlett AR Bissell MJ Interaction with basement membrane serves to rapidly distinguish growth and differentiation pattern of normal and malignant human breast epithelial cells Proc Natl Acad Sci U S A 1992 89 9064 9068 1384042 van 't Veer LJ Dai H van de Vijver MJ He YD Hart AAM Mao M Peterse HL van der Kooy K Marton MJ Witteveen AT Schreiber GJ Kerkhoven RM Roberts C Linsley PS Bernards R Friend SH Gene expression profiling predicts clinical outcome of breast cancer Nature 2002 415 530 536 11823860 10.1038/415530a Zhao H Hastie T Whitfield ML Borresen-Dale AL Jeffrey SS Optimization and evaluation of T7 based RNA linear amplification protocols for cDNA microarray analysis BMC Genomics 2002 3 31 46 12445333 10.1186/1471-2164-3-31 Shalon D Smith SJ Brown PO A DNA microarray system for analyzing complex DNA samples using two-color fluorescent probe hybridization Genome Res 1996 6 639 645 8796352 Eisen MB Spellman PT Brown PO Botstein D Cluster analysis and display of genome-wide expression patterns Proc Natl Acad Sci U S A 1998 95 14863 14868 9843981 10.1073/pnas.95.25.14863 TreeView software Tusher VG Tibshirani R Chu G Significance analysis of microarrays applied to the ionizing radiation response Proc Natl Acad Sci U S A 2001 98 5116 5121 11309499 10.1073/pnas.091062498 Significance Analysis of Microarrays

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==== Front BMC ImmunolBMC Immunology1471-2172BioMed Central London 1471-2172-5-151527474810.1186/1471-2172-5-15Research ArticleAge-associated alterations in CXCL1 chemokine expression by murine B cells Hu Lina 1lhu6@jhmi.eduDixit Vishwa Deep 1dixitvd@grc.nia.nih.govde Mello-Coelho Valeria 1coelhov@grc.nia.nih.govTaub Dennis D 1taubd@grc.nia.nih.gov1 Laboratory of Immunology, Gerontology Research Center, National Institute on Aging-Intramural Research Program, National Institutes of Health, 5600 Nathan Shock Drive, Baltimore, MD 21224, USA2004 26 7 2004 5 15 15 8 3 2004 26 7 2004 Copyright © 2004 Hu et al; licensee BioMed Central Ltd.2004Hu et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background The CXCL1 chemokines, macrophage inflammatory protein-2 (MIP-2) and cytokine-induced neutrophil chemoattractant (KC), have been shown to play a role in a number of pathophysiological disease states including endotoxin-induced inflammation and bacterial meningitis. While the expression of these chemokines has been identified in a variety of cell types in the mouse, little is known about their expression with murine B-lymphocytes. Results Here, we demonstrate that highly purified murine splenic B cells are capable of expressing both MIP-2 and KC protein and mRNA upon activation with lipopolysaccharide (LPS) but not in response to anti-μ and anti-CD40 in combination with interleukin-4 (IL-4) stimulation. Moreover, these chemokines are expressed at higher levels in B cells derived from young (4 m) compared to old (24–29 m) mice. Upon fractionation into distinct B-cell subsets, we found that the expression of MIP-2 and KC by aged follicular (FO) B cells is significantly decreased when compared to the same cells from younger mice, while only MIP-2 production was found to be diminished in aged marginal zone (MZ) B cells. Interestingly, MIP-2 and KC production by newly formed (NF) B cells did not significantly differ with age. Moreover, the potential relevance of these findings is supported by the poor ability of LPS-activated aged B cells to specifically mediate CXCL1-dependent leukocyte recruitment when compared to younger B cells. Conclusion Overall, the decreased expression of CXCL1 chemokines by aged B cells in response to LPS may have potential implications on the secondary recruitment of leukocytes to sites of microbial infections and inflammation possibly contributing to the increased susceptibility of older subjects to pathogen challenge. ChemokinesAgingLymphocytesB cellsimmunodeficiencyCXCL1 ==== Body Background Chemokines are a superfamily of small chemotactic proteins that have been classified into four major subfamilies, namely CXC, CC, C, and CX3C, based on the presence or absence and positional arrangement of N-terminal cysteine (C) residues [1-3]. One of the hallmarks of chemokine function is to facilitate trafficking and recirculation of immune cells from the circulation and tissues into secondary lymphatic organs and various peripheral tissues to maintain immune homeostasis in vivo [4]. These ligands also control the selective recruitment of specific leukocyte subsets to sites of inflammation and immune reactions. Besides migration, chemokines also induce the rapid activation of integrin molecules. The two CXC chemokines, macrophage inflammatory protein-2 (MIP-2) and cytokine-induced neutrophil chemoattractant (KC), are members of the CXCL1 subfamily containing a glutamate-leucine-arginine (ELR) motif that are well known for their ability to induce the activation and recruitment of neutrophils in vitro and in vivo [5-7]. These chemokines are also believed to be the murine structural and functional homologues of human CXCL8, IL-8 and chemokine growth-related oncogene (GRO) [8,9]. MIP-2 and KC display high affinity binding and signaling through the murine CXCR2, a 7-transmembrane G protein-coupled receptor [10]. It has been well established that endotoxin and various proinflammatory cytokines (e.g., TNF-α and IL-1) stimulate the expression of MIP-2 by macrophages, neutrophils and epithelial cells [11-13]. Numerous studies have also demonstrated a pathophysiological role for MIP-2 and KC in several inflammatory disease states including endotoxemia-induced lung injury [14], 1996), glomerulonephritis [15], bacterial meningitis [16] and herpes simplex virus type 1 (HSV-1) infection [17]. In mice, the cellular sources of MIP-2 have been confirmed to be macrophages [6], epithelial cells [12], bone marrow endothelial cells [18], astrocytes [19] and mast cells [20]. In humans, in addition to macrophages, monocytes, T, NK and B cells have also been shown to produce and respond to CXCL8 [21-24]. Despite all of these reports, few studies have focused on chemokine production by B cells and the relevance of such production in cell-mediated immune responses. Age-related dysfunction of the immune system has often been attributed to a variety of measurable changes in the functional activity of many immunomodulatory factors. This immune deterioration with age is believed to contribute to the morbidity and mortality in humans, possibly due to the greater incidence of infection, autoimmunity and cancer in the elderly. Dysregulation of lymphocyte function is thought to play a critical part in these processes. Many factors are believed to contribute to age-associated immunodeficiencies including defects in cellular signaling, stem cell and bone marrow defects, thymus involution, alterations in hormone and growth factor production, and replicative senescence. Chemokines are believed to play a pivotal role in the complex communication network between different cell types that enable the selective trafficking of many immune effector cells to the necessary sites at the appropriate times. Several reports have also demonstrated increased expression of inflammatory cytokines and chemokines in the circulation and by peripheral blood cells with age suggesting that uncontrolled inflammation may contribute to the increased susceptibility to infection and injury in certain aged cohorts. For example, IL-8 chemokine production by human T, NK and monocytes is altered with age in response to bacteria products [25-27]. Alterations in chemokine production and responsiveness may have a significant impact on the capacity of aged subjects to control or even mount an immune response. The objective of the current study is to explore both young and aged murine splenic B cells and B cell subsets for their ability to express the CXC chemokines, MIP-2 and KC, in response to LPS and other stimuli. Three B cell subpopulations were studied here including: (1) Marginal zone (MZ) B cells, which are uniquely positioned in the marginal sinus where they interact with efficient Ag trapping circulating cells and are thought to be involved in the early response against thymus-independent (TI) blood-borne Ags [28,29]; (2) Follicular (FO) B cells, which are long-lived recruiting B cells located at the border of the B cells follicle and the T cell containing PALS zone that facilitate responses to thymus-dependent (TD) Ags and give rise to both germinal center (GC) B cells and plasma cells [30]; and (3) Newly formed (NF) B cells, which correspond to the recently immigrated B cells from the bone marrow and have been described as immature/transitional B cells and the precursors of FO and MZ B cells [31]. We also investigated the effect of these B cell-derived chemokines on splenocyte migration and the influence of aging on this event. The relevance of these findings to the generation of humoral and cellular immune responses shall be discussed. Results and Discussion As expression of MIP-2 and KC by murine splenic B cells has not been previously defined, we initially examined whether murine B cells are capable of producing the CXCL1 chemokines, MIP-2 and KC, upon culture or post cellular activation with LPS, anti-IgM or CD40 mAb in combination with IL-4 for 24 h. Culture supernatants were subsequently examined for MIP-2 and KC expression using ELISA analysis. The results shown in Figure 1A demonstrate that while cultured non-stimulated splenic B cells failed to spontaneously produce detectable levels of MIP-2 and KC (<10 pg/ml), stimulation of B cells with LPS, but not anti-IgM or CD40 mAb in combination with IL-4, resulted in the significant increase in the expressions of both of these chemokines. Interestingly, the quantity of MIP-2 produced in response to LPS was significantly greater than KC. Fig. 1B shows representative images of MIP-2 expression patterns in the cytoplasm of LPS-stimulated splenic B cells. Visually, accumulation of cytoplasmic MIP-2 was observed in splenic B cells (IgM+) following 24 h incubation with LPS, but was less evident in non-stimulated splenic B cells. Similar results were also obtained examining cytoplasmic KC (data not shown). In agreement with the above findings, MIP-2 and KC mRNA was only detected in LPS- (Fig. 1C) but not anti-μ- or anti-CD40 mAb/IL-4-stimulated (data not shown) B cells. Consistent with protein expression, the mRNA levels for MIP-2 were expressed at a greater level than KC. As the engagement of the B cell receptor (BCR) initiates signaling pathways mediated through nonreceptor protein tyrosine kinases, including Fyn, Lyn, Syk, and Bruton's tyrosine kinase (BTK), while LPS activate B cells by stimulating signaling through toll-like receptors, more specifically TLR4. The CC chemokines, MIP-1α and MIP-1β, have been shown to be induced and secreted by human B cells in response to BCR signaling [22]. In contrast, the lack of CXCL1 chemokine induction in response to cross-linking of the BCR with soluble anti-IgM antibody here suggests that the BCR signal(s) may not be optimal and/or essential for MIP-2 and KC production. Perhaps additional costimulatory signals or activation pathways may be necessary for CXCL1 production in combination with BCR signaling. These data demonstrate that murine splenic B cells are capable of secreting the CXCL1 ligands upon activation with LPS but not via anti-μ or anti-CD40 stimulation. Figure 1 Splenic B cells produce MIP-2 and KC in response to LPS. (A) Purified splenic B cells (1 × 106 cells/ml) from 4 month-old C57BL/6 mice were stimulated with 10 μg/ml of LPS, anti-IgM or anti-CD40 plus IL-4 for 24 h. Then, cell-free supernatants were collected and assayed by ELISA for MIP-2 and KC secretion. Data are mean of triplicate ± SD of one representative of two experiments. The value was significantly different from non-stimulated control. (**, P < 0.01; ***, p < 0.005) (B) Immunofluorescence visualization of MIP-2 expression in the cytoplasm of 24 h LPS-stimulated splenic B cells. Cells were incubated with biotinylated goat anti-mouse MIP-2 antibody followed by SA-Oregon green-488 (green), PE-conjugated anti-IgM antibody (red) and the DNA dye DAPI (blue not shown) and subjected to cytospin (5 × 105 cells/microscope slide). Magnification: +100. (C) Total RNA was isolated from non- and LPS-stimulated cells and levels of MIP-2 and KC mRNA were examined by RT-PCR. The housekeeping gene β-actin was amplified as an internal control. The data are representative of two experiments. Several reports have demonstrated that the proliferative response of whole spleen cells to LPS declines with age [32,33]. The results in Figure 2A demonstrate that purified splenic B cells derived from aged mice also display a significantly diminished proliferative response when cultured with LPS for 72 h when compared to B cells derived from younger mice. However, no significant differences in cellular proliferation were observed between young and aged mice after 24 h of culture, which is in accordance with the previous report [34]. Figure 2 Effect of aging on LPS-induced B cell proliferation and MIP-2 and KC production by splenic B cells. (A) In vitro proliferation of splenic B cells stimulated with LPS. Purified splenic B cells (1.25 × 105/ml) were cultured with or without LPS. Proliferation was measured by [3H] thymidine uptake after 24 and 72 h of culture. Data are means ± SD of three mice in each group. The value was significantly different from that of aged mice. (** P < 0.01) (B) Splenic B cells from three to five young and aged mice were stimulated with 10 μg/ml of LPS for 4 and 24 h. After stimulation, cell-free supernatants were collected and assayed by ELISA for MIP-2 and KC secretion. One representative experiment out of three is shown. (C) 24 h LPS-stimulated splenic B cells were subjected to immunofluorescence staining with anti-MIP-2 and anti-KC antibodies and DNA dye DAPI as described in Figure 1. One representative experiment out of three is shown. Control anti-goat IgG staining in both young and aged B cells are shown as inserts in this panel. (D) After stimulation, cells were harvested, and RNA was prepared for MIP-2 and KC specific RT-PCR. The housekeeping gene β-actin was amplified as an internal control. Data shown are representative of two independent experiments. (E) MIP-2 and KC mRNA levels were measured by real time RT-PCR and normalized to threshold cycle (Ct) values of the co-amplified house-keeping gene GAPDH. Normalized values were calibrated to the value derived from non-stimulated controls and shown as fold change of mRNA expression. Data shown are representative of two independent experiments. Value were significantly different from those in aged mice (** P < 0.01; *** P < 0.005) Despite no significant differences in LPS proliferative responses between young an aged mice at 24 h, LPS-stimulated B cells derived from young mice demonstrated approximately 4 times greater levels of MIP-2 in the culture supernatants than aged B cells during this same time period. Similarly, reduced levels of KC expression were also detected in the 24 h culture supernatants LPS-stimulated B cells derived from aged mice when compared to younger animals (Fig. 2B). Moreover, as shown in Fig. 2C, splenic B cells from aged mice demonstrate significantly less expression of intracytoplasmic MIP-2 and KC upon stimulation with LPS when compared to younger B cells. These results were supported by conventional RT-PCR analysis where MIP-2 and KC mRNA signals were barely detectable in both freshly isolated and non-stimulated splenic B cells from young or aged mice. The mRNA levels of MIP-2 and KC chemokines in LPS-stimulated B cells from aged mice were dramatically lower (> 2-fold) than those in younger mice (Fig. 2D). Unlike MIP-2, the KC mRNA signal was only detected after 24 h of stimulation with LPS and demonstrated similar patterns of age-associated expression as MIP-2. Furthermore, real time RT-PCR analysis also demonstrated similar age-related alterations in B cell-derived MIP-2 and KC mRNA expression, albeit after 24 h of LPS stimulation (Fig. 2E). Similar results were obtained using an in vitro B cell culture system in which murine naïve B cells can be activated and induced to proliferate and differentiate into Ab-forming cells. The EL-4 system has been described as a potent in vitro culture system for B activation, proliferation and differentiation [35-37]. Naive B cells cultured in the EL-4 system differentiate to Ig-secreting cells expressing switched isotypes and a plasma cell phenotype (Fig. 5; [38,39]). The presence of both LPS-dependent and T cell-dependent stimulation (e.g., CD40-CD40L) contribute to the plasma cell differentiation in this model system. Here, splenic B cells derived from young and aged mice were co-cultured with irradiated EL-4 thymoma cells in presence of LPS and a macrophage-derived culture supernatant. MIP-2 and KC levels were assessed in the supernatants of those cultures via ELISA on days 3 or 5. As shown in Fig. 3A, splenic B cells cultured in this EL-4 culture system yielded similar results to those observed in Fig. 2. Briefly, a considerable reduction of MIP-2 production by aged splenic B cells was observed in comparison to B cells derived from younger animals. Interestingly, no KC expression was detected in any of the aged B cell cultures while significant KC production was observed in the 3 and 5-day culture supernatant of young B cells. Furthermore, real time RT-PCR also demonstrated a significant reduction in the mRNA expression of MIP-2 and KC in LPS-activated aged B cells when compared to younger B cell cultures (Fig. 3B). Moreover, given our data in Figure 1 demonstrating that cross-linking of CD40 by anti-CD40 antibody and IL-4 failed to elicit CXCL1 chemokine secretion by B cells, the B cell-derived MIP-2/KC secretion in EL-4 system may be attributed to the effect of LPS-dependent signals rather than CD40 cross-linking signals and/or other cytokines/lymphokines presented in the culture. Taken together, these results demonstrate that MIP-2 and KC expression by murine splenic B cells is significantly altered with increasing age. Figure 3 Effect of aging on MIP-2 and KC production by splenic B cells co-cultured with irradiated EL-4 cells. (A) Decreased amounts of MIP-2 and KC proteins in supernatants of splenic B cells cultured in EL-4 culture system. Splenic B cells (3 × 104/well) from three to five young and aged mice were cultured with irradiated EL-4 thymoma cells in the presence of LPS and macrophage supernatant for 3 or 5 days. Culture supernatants were collected and analyzed by ELISA for MIP-2 and KC secretion. These values were significantly different from those in aged mice (** P < 0.01). (B) Real-time RT-PCR analysis of MIP-2 and KC mRNA expression in activated splenic B cells from young and aged mice. After 3 days of culture, total RNA was isolated from cultured cells and levels of MIP-2 and KC mRNA were measured by real time RT-PCR and normalized to threshold cycle (Ct) values of the co-amplified housekeeping gene GAPDH. Normalized values were calibrated to the value derived from EL-4 only controls and expressed as fold induction of mRNA. One representative experiment out of two is shown. Splenic B cells derived from adult mice are comprised of several distinctive subpopulations based on their surface marker expression [40]. To assess if the CXCL1 ligand expression differences observed between young and aged mice are due to differences in B cell subsets, MZ, FO, and NF B cells as well as total IgM+ B cells were sorted by FACS based on their surface IgM, CD21, and CD23 markers (Fig. 4A). Sorted individual B cell subpopulations were co-cultured with EL-4 cells for 5 days. Similar to our above results, total IgM+ splenic B cells derived from aged mice expressed significantly reduced levels of MIP-2 compared to young B cells. Moreover, although MIP-2 secretion by NF B cells derived from aged mice did not significantly differ from young NF B cells, the levels of MIP-2 expressed by aged FO B cells were substantially diminished in comparison to B cells derived from their younger counterparts. Furthermore, unlike MZ B cells derived from young mice, MIP-2 production was almost undetectable in MZ B cells obtained from aged mice (Fig. 4B). In support of these data, MIP-2 mRNA expression was significantly reduced in aged FO and MZ B cells but not in aged NF B cells when compared to B cells derived from younger mice (Fig. 4C). Similar results were observed on day 3 (data not shown). Unfortunately, in several repeated subset studies, we were unable to detect KC in the culture supernatants of B cell subsets derived from young and aged mice. We believe this may be due to the low level of KC produced by the splenic B cell subsets compared to non-sorted, non-fractionated splenic B cells, which were also quite low albeit detectable. B cells stimulated with EL-4 T cells behave differently than LPS-stimulated primary B cells. B cells co-cultured with EL-4 cells demonstrate better viability and more plasmocytic differentiation than LPS alone. Thus, B cells are in different states of activation in these two culture systems and may account for the differences in KC expression. Figure 4 Ability of distinct splenic B cell subpopulations from young and aged mice to produce MIP-2 and KC chemokines. (A) Spleen cells were isolated from three young and aged mice, and then stained with anti-IgM, anti-CD23 and anti-CD21 Abs. Subsequently, NF, FO and MZ B cell subpopulations were sorted from IgM+ gated cell population. (B) Amounts of MIP-2 protein in supernatants of total IgM+ B cells and distinct splenic B cell subpopulations cultured in EL-4 system. NF, FO and MZ B cells within the respective gates shown were directly sorted into individual wells of 96 well plates (1,000 cells/well). Each well had 200 μl of medium containing irradiated EL-4 cells, LPS and macrophage supernatant. After 5 days of culture, supernatants were collected and analyzed by ELISA for MIP-2 and KC secretion. These values were significantly different from those in aged mice (* P < 0.05; ** P < 0.01; *** P < 0.005). (C) Real time RT-PCR analysis of MIP-2 and KC mRNA expression in 5 days-cultured B cells from young and aged mice. MIP-2 and KC mRNA levels in total IgM+, NF, FO and MZ B cells were measured by real time RT-PCR and normalized to threshold cycle (Ct) values of the co-amplified housekeeping gene GAPDH. Normalized values were calibrated to the value derived from EL-4 only controls and expressed as fold induction of mRNA. One representative experiment out of two is shown. These values were significantly different from those in aged mice (* P < 0.05; ** P < 0.01; *** P < 0.005). Given the possibility that the reduced MIP-2 and KC expression by aged B cells in these EL-4 cultures might reflect a diminished capacity of these cells to proliferate and/or differentiate, we examined the proliferative response as well as the generation of class switched B cells in the culture of those B cells. By culturing MZ, FO and NF B cell subpopulations as well as IgM+ B cells on EL-4, no defect in the cell proliferations was found among those distinct B cell subsets in aged mice on day 3 (Fig. 5A) and day 5 (data not shown) of culture. It should be noted that the EL-4 cells utilized in these assays were thymidine kinase deficient [41] and thus, the background thymidine incorporation was quite low (<200 cpm). On the other hand, analysis of both percentages (Fig. 5B) and the absolute number of IgG1+ B cells (Fig. 5C) revealed that the frequency of IgG1+ B cells presented in the aged B cell culture were comparable to those generated in the young B cell culture in response to LPS. Furthermore, ELISA analysis of Ig levels in culture supernatants demonstrated no difference in the level of IgG produced by young and aged splenic B cells in response to LPS (Fig. 5D). These studies suggest that the reduced MIP-2 and KC production observed in EL-4 B cell subset cultures are not due to significant alterations in cellular proliferation and/or differentiation. Figure 5 Similar proliferation and differentiation between young and aged splenic B cells cultured in EL-4. FACS-sorted distinct B cell subsets (1000/well) from three young and aged mice were cultured in EL-4 culture system. Proliferation was measured by [3H] thymidine uptake after 3 days culture. Data represent the mean and variations (SD) from triplicate cultures. The data presented are representative of two independent experiments (A). Purified splenic B cells (4 × 104/well) from three young and aged mice were cultured with irradiated EL-4 thymoma cells in the presence of LPS and macrophage supernatant for 3 and 5 days. The cultured cells were stained with anti-IgG1 and anti IgM Abs. Percentages of IgG1+ IgM+ B cells are indicated (B). Absolute numbers of IgG1+ B cells in culture. Total numbers of IgG1+ B cells per well were calculated from a mixture of 20 wells in each group (C). Culture supernatants were measured by ELISA for IgG production. Data are representative of two independent experiments (D). To assess the potential functional relevance of MIP-2 and KC expression by LPS-stimulated splenic B cells, splenocytes derived from young mice were labeled with Hoechst and examined for their ability to migrate in response to culture supernatants derived from LPS-stimulated young and aged cells. The results in Fig. 6A show that culture supernatants of LPS-stimulated splenic B cells from either young and aged mice induced significant responder cell migration, as compared with non stimulated B cells-derived supernatants. More importantly, the chemotactic activity of culture supernatants derived from LPS-activated younger B cells was significantly higher than the activity observed in response to supernatants derived from LPS-stimulated aged B cells. Interestingly, the addition of anti-MIP-2 Ab to the B cell cultures resulted in an approximate 5% reduction of the migratory capacity of the young responder cells to migrate in response to the LPS-derived supernatants of young B cells but this antibody addition failed to exhibit any significant inhibition of migration induced by aged B cell supernatants (Fig. 6B). Neutralization of responder cell migration was also significantly blocked with anti-KC Ab (~20%) in the young but not aged B cell supernatants. Additional neutralization studies using a panel of anti-chemokine antibodies revealed that several CC chemokines are also being made by B cells and are playing a role in the remaining chemotaxis observed using these young responder cell populations (data not shown). Overall, these results suggest that B cell-derived MIP-2 and KC may play a possible role in leukocyte trafficking and that the MIP-2 and KC derived from these B cell cultures are biologically active. Figure 6 B cell-derived MIP-2 and KC induce splenocyte migration. (A). Purified splenic B cells (1.5 × 106/ml) from three young and aged mice were added to the lower chamber of Transwell plates and stimulated with and without LPS. 24 hr after LPS stimulation, spleen cells from 4 month old C57BL/6 mice were preincubated with Hoechst and subjected to chemotaxis through 5-μm pore size Transwell filters (upper chamber) to the supernatants in the lower chambers. Hoechst fluorescence of accumulated cells in the lower chamber was measured. Data are the mean of triplicate cultures ± SD of one representative of two experiments. The value was significantly different from that of control. (* P < 0.05; ** P < 0.01) (B). For the neutralization, Abs against MIP-2 and KC were added to the supernatants in the lower chambers at the beginning of culture. The percent inhibition was calculated as follows: 100 - 100 × (chemotaxis with neutralizing Ab/chemotaxis without neutralizing Ab). Data are the mean of triplicate cultures ± SD of one representative of two experiments. The value was significantly different from that of control (* P < 0.05; ** P < 0.01). In the current study, we report that endotoxin-activated murine B cells express and secrete the CXC chemokines, MIP-2 and KC. These results are in accordance with the previous studies, which demonstrate that activated human B cells express and secrete CXCL8 [21-23]. We also demonstrate that the expression of CXCL1 chemokines, MIP-2 and KC, decline with age in murine splenocytes and B cells, particularly evident in MZ and FO B cell subsets (Fig. 2, 3 and 4). This could not be attributed to impaired numbers of MZ and FO B cells as judged by flow cytometric analysis as young and aged B cells demonstrated comparable numbers of these populations (data not shown). In addition, these differences could also not be attributed to the alterations in proliferation (Fig. 2A and 5A; [34]) or terminal differentiation of these cells to IgG plasma cells (Fig. 5B,5C and 5D). Thus, the downregulation of MIP-2/KC chemokine production in response to LPS by MZ and FO B cells from aged in relation to young mice appears to be due to an age-dependent signaling difference in response to LPS. In this respect, the expression and function of the LPS receptor TLR4 has been shown impaired in aged animals [42]. In addition, aging can affect gene regulation and some transcription factors, such as nuclear factor-kappa B (NF-kappa B) are required for induction by LPS of MIP-2/KC expression through TLR4 [43]. Thus, further studies will be necessary to elucidate the relevance of age-related alterations in TLR4 expression and/or function as well as NFκB-dependent transcriptional control in the age-related decline of CXCL1 expression in murine B cells. The accumulation of MIP-2 and KC in tissues is known as an important event in early host defense against bacteria infection. Moreover, evidence indicates the MZ B cells are involved in the early stages of immune response against TI type 2 (TI-2) Ags derived from a number of encapsulated bacteria, including Streptococcus pneumoniae, Neisseria meningitides, and Haemophilus influenzae [44,45]. MZ B cells generate an early IgM producing plasma response after in vivo stimulation with TI antigen [29]. The remarkable correlation between the ability of MZ B cells to mount an immune response against bacterial-associated antigens and our observation showing that these cells produce neutrophil-attracting chemokines MIP-2/KC in response to LPS indicate a potential dual role for MZ B cells in preventing host from bacterial infection. Of particular significance for the functionality of MZ B cells, we found that MZ B cell-derived MIP-2 and KC expression was impaired in aged mice. Although TI-2-specific Ab immune responses were not found to be significantly altered with age [46], the diminished capacity of aging immune system to mount an optimal antibody response to encapsulated microbes could be attributed, at least in part, to the diminished capacity of lymphocytes to express inflammatory cytokines and chemokines, such as MIP-2 and KC. Alterations in CXCL1 chemokine production by aged B cells may also have implications in the secondary recruitment of granulocytes to local immune responses at peripheral sites or even within secondary lymphatic organs such as the mucosal immune system in the aged host. Murine MIP-2 and KC exhibit similar expression patterns and functional activities to that of human IL-8 in inflammatory response. For example, it has been previously shown that a significant increase of IL-8 or MIP-2 in human and mice, respectively, occurs in the grain dust-induced inflammation of the lower respiratory tract [47]. Although age-related alterations in IL-8 production by human B cells have not yet been described, diminished expression of IL-8 has been observed in cultured IL-2-stimulated NK cells [25] and LPS-stimulated monocytes [27] derived from elderly subjects. These data suggest that an age-related MIP-2 or IL-8 production could be consequence of a defective functional activity of B cells in aging. It should also be noticed that human IL-8 has been shown to be a potent chemoattractant for human B cells [23,24]. In the present study, we demonstrate that chemotactic activity of culture supernatant from young B cells was dramatically higher than that from aged B cells (Fig. 6A). Neutralization of these chemokines effects with addition of anti-MIP-2 and anti-KC Abs to the cultures resulted in a significant reduction of the migratory capacity of spleen cells to the culture supernatant from young, but not from aged B cells (Fig. 6B). This may be due to the low levels of MIP-2 and KC present in the culture supernatants of aged B cells that were not sufficient to induce significant migration of spleen cells to them. In addition, antibodies specific to KC and MIP-2 partially blocked the young splenic B cell-derived chemotactic activity toward splenocytes for approximately 20% and 5%, respectively, although high level of MIP-2 was present in the culture supernatants. The low ability of neutralizing anti-MIP-2 Ab to alter splenocyte migration suggests that MIP-2 produced by B cells may be a weaker migratory factor for murine splenocytes in relation to KC. As MZ B cells in spleen produce both MIP-2 and KC, one could hypothesize that these chemokines may facilitate B cell migration into and within the MZ area and/or amplify their activity and thus contributing to host defense. Conclusion In summary, we demonstrate for the first time that murine splenic B cells are highly efficient in producing ELR-positive CXC inflammatory chemokines, in particular MIP-2, upon activation by LPS stimulation. Moreover, MIP-2 production, particularly by MZ B cells, was found to decline with age. Our finding suggests a possible linkage between functional activity of MZ B cells in production of neutrophil-attracting inflammatory chemokines and host defense. However, detailed and well-controlled in vivo studies will be necessary to assess these various possibilities and the significance of this CXCL1 production defect by aged B cells. Methods Mice Specific pathogen-free 3–5 months (young) and 24–29 months (aged) C57BL/6 mice were purchased through the Office of Biological Resources and Resource Development of the National Institute on Aging (Bethesda, MD). All mice were maintained in an AAALAC-certified barrier facility and were acclimated for 2 weeks prior to use. All mice were fed autoclaved food and water ad libitum. All mice with evidence of disease (e.g., enlarged spleen, gross tumors) were not utilized in these studies. Preparation of splenic B cells Splenic B cells were negatively selected via depletion of non-B lineage cells from spleen cells using a MACS system. Briefly, spleen cells were incubated with magnetic microbeads coated with anti-CD43 antibody and anti-CD11b antibody (Miltenyi Biotec, Bergisch Gladbach, Germany) at 4°C for 15 min, after which the cells were passed over a MACS apparatus. The purity of splenic B cells was consistently >95% as routinely checked by FACS analysis. ELISA analysis Supernatants were collected from cultures and were then frozen at -80°C. The frozen supernatants were thawed at room temperature and chemokine levels were measured with commercial ELISA assay kits for MIP-2 and KC (R and D Systems, Minneapolis, MN) and immunoglobulins (Igs) (Bethyl, Montgomery, TX) according to the manufacturers' instructions. Immunofluorescence staining Purified splenic B cells derived from young and aged C57BL/6 mice were cultured in the presence of absence of LPS (10 μg/ml) for 24 h at 37°C in 5% CO2. After culture, the cells were harvested, washed, fixed and permeabilized using 3.7% paraformaldehyde and 0.1% Triton X-100 for 15 min. After thoroughly washing these cells, non-specific binding sites were blocked using a 2% BSA solution containing 1% goat, rabbit serum and normal mouse IgG for 15 min at room temperature. Post incubation, these cells were incubated overnight at 4°C in presence of biotinylated mouse anti-MIP-2 and -KC antibodies (1 μg/ml) (R & D Biosystems, Minneapolis, MN). Streptavidin-conjugated Oregon green-488 (Molecular Probes, Eugene, OR) was utilized to label these cells the following day at a concentration of 1:250 for a period of 45 min at room temperature. After washing, cells were then labeled with PE-conjugated anti-IgM antibody (331,12; PharMingen) for 30 min., followed by the stains of cellular nuclei with DAPI (Molecular Probes, Eugene, OR) at concentration of 1 μg/ml for 10 min. These cells were subsequently placed into cytospin funnels and spun onto glass slides using a cytospin centrifuge (Shandon, Pittsburgh, PA) at 1200 rpm for 5 minutes. After being mounted in Immuno Fluor medium (ICN Biomedicals, Aurora, OH), images were acquired by Spot Advanced software on a Zeiss Axiovert S100 microscope under 100X objective (Carl Zeiss, Thornwood, NY). RT-PCR analysis For conventional RT-PCR analysis, total RNA was extracted from cells using the RNeasy Mini kit (Qiagen, Valencia, CA) and cDNA was prepared from 1 μg of total RNA transcribed by the SuperScript First-strand Synthesis system for the RT-PCR procedure (Invitrogen, Carlsbad, CA) according to the manufacture's instructions. The mouse MIP-2 and KC primers (Sigma Genosys, Woodlands, TX) utilized in these studies were: MIP-2 sense 5'-TGCCGGCTCCTCAGTGCTG-3' and MIP-2 antisense 5'-AAACTTTTTGACCGCCCTTGA-3'; KC sense 5'-CGCTCGCTTCTCTGTGCA-3'and KC antisense 5'-ATTTTCTGAACCAAGGGAGCT-3' as described previously [48]. The cycling conditions for PCR were 95°C for 4 min for denaturation, followed by 30 cycles at 95°C for 30 s, annealing at 57°C for 45 s plus extension at 72°C for 45 s and a final 10 min at 72°C. After 30 cycles of the PCR, 10 μl of the PCR products were separated on a 1.8% agarose gel, stained with ethidium bromide, and photographs were taken. Their densities were quantified by using the image-analysis system FluorChem (Alpha Innotech Corporation, San Leandro, CA) and normalized using β-Actin housekeeping gene in the same sample. Real-time PCR analysis Approximately 1 μg of total RNA was reverse transcribed by using SuperScript First-strand Synthesis system (Invitrogen, Carlsbad, CA) as described above. Real-time primers for murine MIP-2 and KC were designed using Primer Express software (Applied Biosystems) using the sequences from GenBank (MIP-2, accession no. X53798; KC, accession no. J04596; and GAPDH, accession no. NM_008084). Primers were constructed as follows: MIP-2 (forward primer, AGTGAACTGCGCTGTCAATGC; reverse primer, AGGCAAACTTTTTGACCGCC), KC (forward primer, TGCACCCAAACCGAAGTCAT; reverse primer, TTGTCAGAAGCCAGCGTTCAC), and GAPDH (forward primer, TGCATGGCCGTTCTTAGTTG; reverse primer, AGTTAGCATGCCAGAGTCTCGTT). Reverse-transcribed cDNA was amplified with primer sets for murine MIP-2, KC and GAPDH as indicated above using SYBR Green PCR core reagents and the GeneAmp 5700 Sequence Detection System (PE Applied Biosystems) following the manufacturer's instructions. No PCR products were generated from genomic versus cDNA template. Fold induction of mRNA was determined from the threshold cycle (Ct) values normalized for GAPDH expression and then normalized to the value derived from controls. EL-4-based B cell culture The splenic B cell culture was performed using the EL-4-based B cell culture system as previously described [38]. Briefly, individual wells of 96-well flat-bottom plates were loaded with 5 × 104 irradiated (5,000 cGy) murine EL-4 thymoma cells (clone B5) in 200 μl of RPMI 1640 medium supplemented with 10% FCS, 10-5 M 2-mercaptoethanol (2-ME), 25 mM HEPES buffer, penicillin (100 U/ml), streptomycin (100 μg/ml), 10 μg/ml LPS, and 10% supernatant from culture of J774A.1 macrophage cells (no. TIB-67; American Type Culture Collection, Manassas, VA). MACS purified splenic B cells or FACS sorted B cells were seeded directly onto a feeder layer of irradiated EL-4 cells and cultured at 37°C in 5% CO2. Moreover, we have previously shown that approximately 97% of wells contained sorted single cells using the same outfitted FACStar Plus. These results were verified based on the resulting sequencing histograms demonstrating evidence of only one V6 light chain sequence in the amplified cDNA [38]. Therefore, any differences in the levels of CXCL1 chemokine secretion among B cell subsets and age should not be a consequence of unequal number of cells sorted in the culture plates. The culture supernatants were collected on day 3 or day 5 and tested for chemokine secretion by ELISA. These time points were selected based on optimal cell viabilities and time to permit cellular activation and proliferation. Flow cytometric analysis and cell sorting The monoclonal Abs utilized for the cell surface staining were FITC-anti-CD21 (clone 7G6; PharMingen, San Diego, CA), -anti-IgM (331,12; PharMingen), PE-anti-CD23 (PharMingen), APC-anti-IgM (clone II/41; PharMingen), and/or biotinylated anti-IgG1 (PharMingen). Biotin-labeled antibody binding was visualized using UltraAvidin-R-Phycoerythrin (Linco Technologies, St. Louis, MO). For each staining, 106 cells were pre-incubated with the blocking antibodies, the anti-Fc receptor (24G2), for 30 minutes on ice and then incubated with a mixture of mAbs for an additional 15 min on ice. Post washing, the cells were subsequently incubated with PE-streptavidin for 15 min on ice after which the cells were washed with 5% FCS/HBSS. These stained cells were subsequently analyzed on a Becton Dickinson FACScan flow cytometer using CellQuest software. The B cell subsets, NF, FO and MZ, were isolated through the use of cell sorting using the combination of anti-IgM-APC, anti-CD23-FITC and anti-CD21-PE mAbs. Single spleen cell suspensions were stained with the aforementioned Abs and the MZ, FO and NF B cells within the gate of IgM+ cell population were sorted based on their differential expression of CD21 and CD23 using a FACStar Plus (Becton Dickinson, San Jose, CA). The purity of each sorted population was consistently >95%. Proliferation assay MACS-purified splenic B cells (1.25 × 105/well) were cultured with 10 μg/ml of LPS for 1 and 3 days or FACS-sorted distinctive B cell subpopulations (1000/well) were cultured in EL-4 culture system for 3 and 5 days at 37°C in a 5% CO2. Cultures were pulsed with 1 μCi [3H] thymidine (NEN, Boston, MA) for the final 18 h. Cells were harvested on fiberglass paper. [3H] thymidine uptake was measured in a liquid scintillation counter (Beckman, Fullerton, CA). Chemotaxis assay In the lower chambers of Transwell plates (Costar, Cambridge, MA), 1.5 × 106/ml purified splenic B cells derived from young and aged mice suspended in 600 μl of RPMI 1640 medium supplemented with 2% FCS, 10-5 M 2-mercaptoethanol (2-ME), penicillin (100 U/ml), streptomycin (100 μg/ml) were cultured in the presence and in the absence of LPS (10 μg/ml) and incubated at 37°C in 5% in CO2 for 24 hr. After incubation, the cells and supernatants in the lower chambers were assessed for chemotactic activity using young splenocyte responder cells. These splenocytes were isolated from 4 month old C57Bl/6 mice after which they were preincubated with 10 μM Hoechst 33342 (Molecular Probes, Eugene, OR) in RPMI 1640 supplemented with 10% FCS for 30 min at 37°C. Subsequently, the Hoechst-stained splenocytes (1 × 106) were washed with RPMI 1640 supplemented with 2% FCS, resuspended in 100 mL of medium, and then added to the upper chamber, containing a 6.5-mm diameter polycarbonate Transwell culture insert with 5 μm size pore. Each expected group was performed in duplicates with supernatants in the lower chambers for 8 to 10 h at 37°C. In certain assays, neutralizing antibodies specific for MIP-2 and KC at (1 μg/ml) were added to the low chamber containing the LPS-stimulated B cell supernatants. The transmigration of the Hoechst-labeled cells into the lower chamber were measured in a fluorescent spectrophotometer at 350 nm (excitation)/460 nm (emission). The results are expressed as fluorescent units or as the percentage inhibition of Hoechst-labeled splenocyte migration. Statistical analysis Statistical evaluation of significance between the experimental groups was determined by Student's t test. List of abbreviations Ag, antigen; MIP-2, Macrophage inflammatory protein-2; ELR, glutamate-leucine-arginine; GRO, growth-related oncogene; HSV-1, herpes simplex virus type 1; KC, cytokine-induced neutrophil chemoattractant; MZ, marginal zone; FO, follicular; NF, newly formed; TI, Thymus-independent; TD, Thymus-dependent Authors' contributions LH, VMC, and VDD performed the experiments. LH and DDT prepared the figures and wrote the paper. DDT also supervised the work and edited the manuscript. All authors have read and approved the final manuscript. Acknowledgments We thank Drs. Ashani Weeraratna and Eric Schaffer for helpful discussions and for critical review of the manuscript, Bob Pyle and Ana Lustig for their technical assistances, and GRC Flow Cytometry Facility for their excellent cell sorting services. ==== Refs Premack BA Schall TJ Chemokine receptors: gateways to inflammation and infection Nat Med 1996 2 1174 78 8898734 Rollins BJ Chemokines Blood 1997 90 909 28 9242519 Zlotnik A Yoshie O Chemokines: a new classification system and their role in immunity Immunity 2000 12 121 27 10714678 10.1016/S1074-7613(00)80165-X Baggiolini M Chemokines and leukocyte traffic Nature 1998 392 565 68 9560152 10.1038/33340 Oquendo P Alberta J Wen DZ Graycar JL Derynck R Stiles CD The platelet-derived growth factor-inducible KC gene encodes a secretory protein related to platelet alpha-granule proteins J Biol Chem 1989 264 4133 37 2917992 Wolpe SD Sherry B Juers D Davatelis G Yurt RW Cerami A Identification and characterization of macrophage inflammatory protein 2 Proc Natl Acad Sci USA 1989 86 612 16 2643119 Bacon KB Oppenheim JJ Chemokines in disease models and pathogenesis Cytokine Growth Factor Rev 1998 9 167 73 9754710 10.1016/S1359-6101(98)00005-7 Tekamp-Olson P Gallegos C Bauer D McClain J Sherry B Fabre M van Deventer S Cerami A Cloning and characterization of cDNAs for murine macrophage inflammatory protein 2 and its human homologues J Exp Med 1990 172 911 19 2201751 10.1084/jem.172.3.911 Cochran BH Reffel AC Stiles CD Molecular cloning of gene sequences regulated by platelet-derived growth factor Cell 1983 33 939 47 6872001 10.1016/0092-8674(83)90037-5 Bozic CR Gerard NP von Uexkull-Guldenband C Kolakowski LF Conklyn MJ Breslow R Showell HJ Gerard C The murine interleukin 8 type B receptor homologue and its ligands. 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==== Front BMC PharmacolBMC Pharmacology1471-2210BioMed Central London 1471-2210-4-131527968010.1186/1471-2210-4-13Research Article8-Cl-Adenosine enhances 1,25-dihydroxyvitamin D3-induced growth inhibition without affecting 1,25-dihydroxyvitamin D3-stimulated differentiation of primary mouse epidermal keratinocytes Bollag Wendy B 123wbollag@mail.mcg.eduZhong Xiaofeng 3frank_zhong@hotmail.comJosephson Sarah 3sarahjosephson03@yahoo.com1 Department of Medicine (Dermatology), Medical College of Georgia, Augusta, GA 30912 USA2 Cell Biology and Anatomy, Medical College of Georgia, Augusta, GA 30912 USA3 Institute of Molecular Medicine & Genetics, Medical College of Georgia, Augusta, GA 30912 USA2004 27 7 2004 4 13 13 15 4 2004 27 7 2004 Copyright © 2004 Bollag et al; licensee BioMed Central Ltd.2004Bollag et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background Epidermal keratinocytes continuously proliferate and differentiate to form the mechanical and water permeability barrier that makes terrestrial life possible. In certain skin diseases, these processes become dysregulated, resulting in abnormal barrier formation. In particular, skin diseases such as psoriasis, actinic keratosis and basal and squamous cell carcinomas are characterized by hyperproliferation and aberrant or absent differentiation of epidermal keratinocytes. We previously demonstrated that 8-Cl-adenosine (8-Cl-Ado) can induce keratinocyte growth arrest without inducing differentiation. Results To determine if this agent might be useful in treating hyperproliferative skin disorders, we investigated whether 8-Cl-Ado could enhance the ability of 1,25-dihydroxyvitamin D3 [1,25(OH)2D3], a known keratinocyte differentiating agent and a clinical treatment for psoriasis, to inhibit keratinocyte growth. We found that low concentrations of 8-Cl-Ado and 1,25(OH)2D3 appeared to act additively to reduce proliferation of primary mouse epidermal keratinocytes. However, another agent (transforming growth factor-beta) that triggers growth arrest without inducing differentiation also coincidentally inhibits differentiation elicited by other agents; inhibition of differentiation is suboptimal for treating skin disorders, as differentiation is often already reduced. Thus, we determined whether 8-Cl-Ado also decreased keratinocyte differentiation induced by 1,25(OH)2D3, as measured using the early and late differentiation markers, keratin 1 protein levels and transglutaminase activity, respectively. 8-Cl-Ado did not affect 1,25(OH)2D3-stimulated keratin 1 protein expression or transglutaminase activity. Conclusions Our results suggest that 8-Cl-Ado might be useful in combination with differentiating agents for the treatment of hyperproliferative disorders of the skin. ==== Body Background The epidermis of the skin serves as a mechanical and water permeability barrier essential for terrestrial life (reviewed in [1]) and is composed primarily of epidermal keratinocytes. These keratinocytes stratify to form several layers. The deepest layer, the stratum basalis or basal layer comprises proliferating cells that continuously divide to regenerate cells lost to the environment. As the cells migrate upward into the first differentiated layer, the stratum spinousum or spinous layer, they cease proliferating and begin to express the intermediate filament proteins, the mature keratins 1 and 10. This early differentiation is followed by a late differentiation program in the stratum granulosum or granular layer, which is marked by the expression of other structural proteins, such as filaggrin and loricrin, and by increased activity of the enzyme, transglutaminase, which forms highly durable γ-glutamyl-ε-lysyl bonds to cross-link the proteins into a tough and resistant shell underneath the plasma membrane. At the boundary of the granular layer and the outermost stratum corneum, or cornified layer, the keratinocytes terminally differentiate, degrading their nuclei and other organelles and releasing lamellar bodies, the lipid contents of which form a water-impermeant barrier. The squames, the flattened remnants of the keratinocytes, and the lipids from the lamellar bodies form a sort of brick and mortar, to prevent water loss, microbial invasion and/or other mechanical insults (reviewed in [2-4]). 1,25-Dihydroxyvitamin D3 [1,25(OH)2D3] is a known regulator of this process of keratinocyte growth and differentiation (reviewed in [2,5]). In vitro, 1,25(OH)2D3 inhibits keratinocyte proliferation and stimulates the expression of numerous keratinocyte differentiation markers (reviewed in [2,6]). In vivo a physiologic role for 1,25(OH)2D3 in regulating keratinocyte differentiation is suggested by several lines of evidence: (1) keratinocytes express both the 25-hydroxylase and the 1α-hydroxylase which converts inactive vitamin D3 to its active 1,25-dihydroxy metabolite (reviewed in [2,6]); (2) receptors for 1,25(OH)2D3 are present in the skin and in epidermal keratinocytes in vitro [7-11]; and (3) Vitamin D receptor null mice exhibit altered skin function, characterized by abnormal hair follicles and reduced expression of several keratinocyte differentiation markers [12]. Furthermore, 1,25(OH)2D3 and its structural analogs have been used as effective treatments for psoriasis, a human skin disease characterized by inflammation and by hyperproliferation and abnormal differentiation of keratinocytes (reviewed in [13,14]). 8-Chloro-cyclic-adenosine monophosphate (8-Cl-cAMP) is known to inhibit growth and to induce apoptosis in a variety of cancer cells [15-18], suggesting its potential utility as an anti-cancer drug. Indeed, phase I trials with 8-Cl-cAMP have been performed ([19,20] and reviewed in [21]) and phase II trials are in progress [22]. However, the mechanisms by which this agent acts are incompletely understood, and several investigators have proposed that an 8-Cl-cAMP metabolite, 8-chloro-adenosine (8-Cl-Ado) is the active anti-proliferative compound [16,23]. Indeed, 8-Cl-Ado has been shown to inhibit growth in a variety of cell types [24-28]. Previously, we demonstrated that 8-Cl-Ado arrests the growth of primary mouse epidermal keratinocytes without triggering differentiation [29]. Thus, 8-Cl-Ado functions in an analogous fashion to transforming growth factor-β (TGF-β), which also triggers growth arrest, but not differentiation,, of keratinocytes (reviewed in [30]). In contrast with a polypeptide such as TGF-β, 8-Cl-Ado, as a small molecule rather than a protein, could potentially be taken orally or applied topically to skin. Thus, 8-Cl-Ado may represent a novel therapy for treatment of skin disorders, such as psoriasis, actinic keratoses and basal and squamous cell carcinomas, characterized by hyperproliferation of keratinocytes. One potential problem, however, is that TGF-β also inhibits the expression of differentiation markers elicited by other differentiating agents [31]. Since another characteristic typical of hyperproliferative skin diseases such as psoriasis is impaired differentiation [32], a therapy that inhibits both proliferation and differentiation would be less than ideal. To determine whether 8-Cl-Ado, as a potent keratinocyte growth arrestor, could potentially be used to treat hyperproliferative skin diseases in combination with a current treatment, we investigated the effect of 8-Cl-Ado on 1,25(OH)2D3-induced inhibition of keratinocyte proliferation and stimulation of keratinocyte differentiation. We found that low concentrations of 8-Cl-Ado acted additively with 1,25(OH)2D3 to inhibit DNA synthesis, without affecting the ability of 1,25(OH)2D3 to enhance keratin 1 expression, a marker of early differentiation, or transglutaminase activity, a marker of late differentiation. Thus, our results suggest that a combination therapy with 1,25(OH)2D3 and 8-Cl-Ado could potentially be an effective treatment for hyperproliferative skin disorders including psoriasis, actinic keratosis and non-melanoma skin cancers. Results and discussion To determine if 8-Cl-Ado could function with the growth inhibiting agent 1,25(OH)2D3 to enhance its antiproliferative effect, we incubated primary epidermal keratinocytes for 24 hours with various concentrations of 8-Cl-Ado in the presence and absence of low concentrations of 1,25(OH)2D3 prior to assessing effects on de novo DNA synthesis as measured by [3H]thymidine incorporation into DNA. As shown in Figure 1A, 8-Cl-Ado inhibited [3H]thymidine incorporation at concentrations of 5–25 μM with an estimated half-maximal inhibitory concentration (IC50) of 5 μM. This value agrees well with our previously determined IC50 of 7.5 μM [29]. In agreement with previous reports [33,34], 1,25(OH)2D3 also inhibited DNA synthesis at concentrations of 1 to 100 nM with an estimated IC50 of approximately 4 nM (Figure 1B). As shown in Figure 2, when the two agents were combined, their effect on DNA synthesis appeared to be additive, as evidenced by the comparable slopes of the [3H]thymidine incorporation curves at the three different concentrations of 0 (a portion of which is replotted from Figure 1), 1 and 10 nM 1,25(OH)2D3. The combination of 1 or 5 μM 8-Cl-Ado with 10 nM 1,25(OH)2D3 yielded a greater inhibition than 8-Cl-Ado alone, and conversely, the combined effect of 5 and 10 μM 8-Cl-Ado with 1 nM 1,25(OH) 2D3 was significantly larger than 1 nM 1,25(OH)2D3 alone. Importantly, the combination of 10 nM 1,25(OH)2D3 with 10 μM 8-Cl-Ado produced an inhibition of [3H]thymidine incorporation that was significantly greater than that elicited by either agent alone. Indeed, the inhibition elicited by 10 μM 8-Cl-Ado and 10 nM 1,25(OH)2D3 was comparable to the inhibition produced by 100 nM 1,25(OH)2D3 alone (compare Figures 1B and 2). Thus, our results suggest that not only does 8-Cl-Ado not prevent the growth inhibitory action of 1,25(OH)2D3, but, in fact, the two agents seem to act in an additive fashion to more effectively inhibit keratinocyte proliferation. Figure 1 8-Cl-Ado and 1,25(OH)2D3 Inhibit Keratinocyte Proliferation. Near-confluent primary mouse epidermal keratinocytes were treated with the indicated concentrations of (A) 8-Cl-Ado or (B) 1,25(OH)2D3 for 24 hours, and [3H]thymidine incorporation was determined as indicated in Materials and Methods. Data represent the mean ± SEM of five experimentsperformed in triplicate; *p < 0.05, **p < 0.01 versus the control value. Figure 2 8-Cl-Ado and 1,25(OH)2D3 Act Additively to Inhibit Keratinocyte Proliferation. Near-confluent primary mouse epidermal keratinocytes were treated with the indicated concentrations of 8-Cl-Ado in the presence of no (closed circles), 1 nM (open squares) or 10 nM (open triangles) 1,25(OH)2D3 for 24 hours, and [3H]thymidine incorporation was determined as indicated in Materials and Methods. Data represent the mean ± SEM of five experiments performed in triplicate; *p < 0.05, **p < 0.01 versus the control value, †p < 0.01 versus the corresponding concentration of 1,25(OH)2D3 alone, §p < 0.01 versus the corresponding concentration of 8-Cl-Ado alone. TGF-β, another agent that, like 8-Cl-Ado, induces growth arrest but not differentiation of keratinocytes ([31] and reviewed in [30]), can inhibit the ability of differentiating agents to elicit keratinocyte differentiation [31]. However, for an agent to have therapeutic potential as a treatment for hyperproliferative skin disorders, such an inhibition of differentiation would be counterproductive to its efficacy as a medication. To determine if 8-Cl-Ado also inhibited keratinocyte differentiation, we investigated whether 8-Cl-Ado inhibited the ability of 1,25(OH)2D3 to induce the late differentiation marker, transglutaminase activity. For this experiment we chose the concentrations of 8-Cl-Ado (10 μM) and 1,25(OH)2D3 (10 nM) shown in Figure 2 to produce a greater growth inhibition than either agent alone. As illustrated in Figure 3, 10 μM 8-Cl-Ado alone had little or no effect on transglutaminase activity, as reported previously [29]. On the other hand, 10 nM 1,25(OH)2D3 significantly elevated transglutaminase activity by approximately 75%. The combination of 8-Cl-Ado and 1,25(OH)2D3was not significantly different from 1,25(OH)2D3 alone, with a significant approximate 60% increase relative to the control value. Thus, our results indicate that 8-Cl-Ado did not prevent the differentiative effect of 1,25(OH)2D3, suggesting that these two agents might be combined to treat keratinocyte hyperproliferative disorders, such as psoriasis. Figure 3 8-Cl-Ado Has No Effect on 1,25(OH)2D3-Stimulated Transglutaminase Activity. Near-confluent primary mouse epidermal keratinocytes were treated with and without 10 μM 8-Cl-Ado in the presence and absence of 10 nM 1,25(OH)2D3 for 24 hours, and transglutaminase activity was determined as indicated in Materials and Methods. Data represent the mean ± SEM of four experiments performed in triplicate; *p < 0.01 versus the control value. Transglutaminase activity is a marker of late keratinocyte differentiation. We also examined the effect of 8-Cl-Ado on a marker of early keratinocyte differentiation, namely keratin 1 protein expression, using an even higher concentration of 8-Cl-Ado (25 μM). Western analysis demonstrated that 1,25(OH)2D3 induced an approximate 45% increase in keratin 1 protein levels with the combination of 1,25(OH)2D3 and 8-Cl-Ado producing a comparable 46% increase (Figure 4). Thus, early differentiation in response to 1,25(OH)2D3 also was not affected by 8-Cl-Ado. Interestingly, however, in contrast to previous results [29], in these experiments 8-Cl-Ado alone elicited a small but significant increase in keratin 1 protein expression (32%). The reason for this disparity is unclear but may result from differences in the lot of anti-keratin 1 antibody used in the western analysis and/or the increased sensitivity of the method used for detecting and quantifying immunoreactive protein in this work. Figure 4 8-Cl-Ado Has No Effect on the 1,25(OH)2D3-Induced Increase in Keratin 1 Protein Levels. Near-confluent keratinocytes were incubated for 24 hours with and without 25 μM 8-Cl-Ado in the presence and absence of 20 nM 1,25(OH)2D3 and were then processed for western analysis. (A) A representative immunoblot is shown. (B) Keratin 1 levels were quantified, corrected for background and normalized for loading, as described in Materials and Methods. Data represent the mean ± SEM of four experiments performed in duplicate; *p < 0.05 versus the control value. Most current treatments for psoriasis suffer from one or more disadvantages including lack of efficacy, contraindications due to deleterious side effects and/or aesthetic deficiencies ([35] and reviewed in [36]). Indeed, monotherapies tend to be less efficacious than combination therapies with two or more agents used concurrently, sequentially or in a rotational fashion (reviewed in [36]). Treatment with 1,25(OH)2D3 and its analogs has proven successful, although the possibility of toxicity as the result of 1,25(OH)2D3's ability to affect calcium metabolism has led to the search for topically effective analogs with little or no effect on serum calcium levels (reviewed in [32]). If the amount of 1,25(OH)2D3 (or its analog) required for treatment could be reduced, this decrease in dosage would presumably minimize systemic effects on calcium, which is the primary dose-limiting factor in the use of 1,25(OH)2D3 analogs in the treatment of psoriasis [32]. Thus, our results indicating that 8-Cl-Ado enhances the growth inhibitory effect of 1,25(OH)2D3, a known keratinocyte differentiating agent and possible treatment for psoriasis [32], suggests the potential for combination therapy. Moreover, the fact that 8-Cl-Ado does not interfere with the promotion of differentiation by 1,25(OH)2D3 further supports the possible combined use of these two agents for treatment of hyperproliferative skin disorders. Several lines of evidence suggest that 8-Cl-Ado is not simply acting through cyototoxicity to inhibit keratinocyte growth. First, we have previously shown that 8-Cl-Ado growth arrests keratinocytes in the G0/G1 phase of the cell cycle with no increase in the sub-G0/G1 (apoptotic) population of cells [29]. Second, we also showed that the effect of 8-Cl-Ado to inhibit proliferation is reversible in that washout of the compound returned DNA synthesis essentially to basal (untreated) levels [29]. Finally, in this report we demonstrate that 8-Cl-Ado did not inhibit the 1,25(OH)2D3-stimulated increase in transglutaminase activity (Figure 3) or keratin 1 protein expression (Figure 4). Together, these results indicate that 8-Cl-Ado is acting in a specific manner to decrease keratinocyte proliferation. Nevertheless, the mechanism by which 8-Cl-Ado exerts its growth inhibitory effects in keratinocytes is not clear. Our previous results indicate that 8-Cl-Ado must enter the cells to trigger growth arrest, since inhibiting uptake with an adenosine transporter, NBTI, prevented the arrest in the G0/G1 phase of the cell cycle [29]. We also reported in a prior publication that 8-Cl-Ado induced the expression of the cyclin-dependent kinase inhibitor, p21 [29], which is known to contribute to growth arrest in keratinocytes and other cell types ([37] and reviewed in [30]). However, other investigators have reported 8-Cl-Ado-mediated inhibitory effects on RNA synthesis and the levels of cellular ATP [16]. Clearly, further research is necessary to define the pathways used by 8-Cl-Ado to regulate keratinocyte proliferation. Conclusions In summary, our data show that 8-Cl-Ado functions with the keratinocyte-differentiating agent 1,25(OH)2D3 to inhibit keratinocyte proliferation without altering the ability of 1,25(OH)2D3 to induce differentiation. Thus, our results support the possibility of using 8-Cl-Ado alone or in combination with differentiating agents such as 1,25(OH)2D3 or its analogs to treat hyperproliferative keratinocyte disorders including psoriasis. Methods Materials Tissue culture reagents were obtained from standard suppliers as indicated in a previous publication [29]. 1,25(OH)2D3 was a generous gift of Dr. Maurice Pechet (Research Institute for Medicine and Chemistry, Cambridge, MA). 8-Cl-Ado was obtained from Biolog (La Jolla, CA). [3H]Thymidine and [3H]putrescine were purchased from Dupont/NEN (Boston, MA). Dimethylated casein was obtained from Sigma (St. Louis, MO). All other reagents were from standard suppliers. Keratinocyte culture Primary cultures of mouse epidermal keratinocytes were prepared from neonatal ICR CD-1 mice and cultivated in a 25 μM calcium-containing serum-free keratinocyte medium as in [29]. Measurement of DNA synthesis For measurement of [3H]thymidine incorporation into DNA, as in [29], near-confluent cultures were refed with SFKM containing various concentrations of 8-Cl-Ado with or without different concentrations of 1,25(OH)2D3. After 24 hours, cells were labeled with 1 μCi/ml [3H]thymidine for an additional hour in the continued presence of 8-Cl-Ado and/or 1,25(OH)2D3. Cultures were washed twice with phosphate-buffered saline without calcium or magnesium (PBS-) and macromolecules were precipitated using ice-cold 5% trichloroacetic acid (TCA). After additional washing with 5% TCA and distilled water, cells were solubilized in 0.3 M NaOH, and the amount of [3H]thymidine incorporated into DNA was determined by liquid scintillation counting. Measurement of transglutaminase activity Transglutaminase activity was assessed essentially as described in [33]. Briefly, near-confluent keratinocytes were incubated for 24 hours with the indicated agents in SFKM. The cells were scraped into homogenization buffer (0.1 M Tris-acetate, pH 7.8, 2 μg/ml aprotinin, 2 μM leupeptin, 1 μM pepstatin A, 0.2 mM EDTA and 0.2 mM PMSF), collected by centrifugation and subjected to one freeze-thaw cycle prior to disruption by sonication. Aliquots of the homogenate were removed for determination of protein content and transglutaminase activity. Transglutaminase activity was measured as the [3H]putrescine radioactivity incorporated into casein after an overnight incubation at 37°C. Casein was precipitated with TCA, collected onto glass fiber filters and counted by liquid scintillation spectrometry. The cellular protein content of the samples was determined using the Bio-Rad DC protein assay system (Bio-Rad, Hercules, CA), with BSA as standard, and transglutaminase activity was expressed as cpm/μg protein. Western analysis of keratin 1 protein levels Keratinocytes were treated and solubilized in sample buffer (31.2 mM Tris, pH 6.8, 1% SDS, 12.5% glycerol). Equal sample volumes were separated by SDS polyacrylamide gel electrophoresis on an 8% gel and transferred to Immobilon PVDF membrane (Millipore, Billerica, MA). Membranes were blocked with Odyssey blocking buffer (Licor Biosciences, Lincoln, NE), probed with a rabbit polyclonal anti-keratin 1 antibody (Covance, Princeton, NJ) and a mouse monoclonal anti-actin antibody (Sigma, St. Loius, MO). Immunoreactive proteins were visualized with IRDye800-coupled donkey anti-rabbit IgG (Rockland Immunochemicals, Gilbertsville, PA) or IR Alexa Fluor 680-coupled goat anti-mouse IgG (Molecular Probes, Eugene, OR) on a Licor Odyssey Infrared Imaging System. Keratin-1 protein levels were corrected for background and normalized using background-corrected actin levels. Statistical analysis Significance of differences was determined with the computer program InStat (Graphpad Software, San Diego, CA) using ANOVA with a Student-Newman-Keuls post-hoc test. Abbreviations 1,25(OH)2D3, 1,25-dihydroxyvitamin D3; 8-Cl-Ado, 8-chloro-adenosine; 8-Cl-cAMP, 8-chloro-cyclic-adenosine monophosphate; IC50, half-maximal inhibitory concentration; TGFβ, transforming growth factor-beta Authors' contributions WBB conceived of the study, planned the experiments, analyzed the data and drafted the manuscript; XZ and SJ planned, conducted and analyzed the keratin 1 expression experiments. Acknowledgements The authors gratefully acknowledge Dr. Maurice Pechet for his generous gift of 1,25(OH)2D3. The authors also thank Ms. Sagarika Ray and Mr. Brian Shapiro for their expert technical assistance. ==== Refs Madison KC Sando GN Howard EJ True CA Gilbert D Swartzendruber DC Wertz PW Lamellar granule biogenesis: A role for ceramide glucosyltransferase, lysosomal enzyme transport, and the Golgi J Invest Dermatol Symp Proc 1998 3 80 86 Bikle DD Pillai S Vitamin D, calcium and epidermal differentiation Endocrine Rev 1993 14 3 19 8491153 10.1210/er.14.1.3 Yuspa SH Hennings H Tucker RW Jaken S Kilkenny AE Roop DR Signal transduction for proliferation and differentiation in keratinocytes Ann NY Acad Sci 1988 82 191 196 2470295 Yuspa SH Punnonen K Lee E Hennings H Strickland JE Cheng C Glick A Dlugosz A Alterations in the biology and biochemistry of keratinocytes induced by the ras oncogene Prog Clin Biol Res 1992 376 103 115 1528916 Bollag WB Bollag RJ Protein kinase C, phospholipase D, vitamin D and keratinocyte differentiation Mol Cell Endocrinol 2001 177 173 182 11377832 10.1016/S0303-7207(01)00440-3 Bikle DD Ng D Tu C-L Oda Y Xie Z Calcium-and vitamin D-regulated keratinocyte differentiation Mol Cell Endocrinol 2001 177 161 171 11377831 10.1016/S0303-7207(01)00452-X Stumpf WE Sar M Reid FA Tanaka Y DeLuca HF Target cells for 1,25-dihydroxyvitamin D3 in intestinal tract, kidney, skin, pituitary, and parathyroid Science 1979 206 1188 1190 505004 Colston K Hirst M Feldman D Organ distribution of the cytoplasmic 1,25-dihyroxycholecalciferol receptor in various mouse tissues Endocrinology 1980 107 1916 1922 6253281 Berger U Wilson P McClelland RA Colston K Haussler MR Pike JW Coombes RC Immunocytochemical detection of 1,25-dihydroxyvitamin D receptors in normal human tissues J Clin Endocrinol Metab 1988 67 607 613 2842365 Feldman D Chen T Hirst M Colston K Karasek M Cone C Demonstration of 1,25-dihydroxyvitamin D3 receptors in human skin biopsies J Clin Endocrinol Metab 1980 51 1463 1465 6255007 Milde P Hauser U Simon T Mall G Ernst V Haussler MR Frosch P Rauterberg EW Expression of 1,25-dihydroxyvitamin D3 Receptors in normal and psoriatic skin J Invest Dermatol 1991 97 230 239 1649228 10.1111/1523-1747.ep12480255 Xie Z Komuves L Yu QC Elalieh H Ng DC Leary C Chang S Crumrine D Yoshizawa T Kato S Bikle DD Lack of the vitamin D receptor is associated with reduced epidermal differentiation and hair follicle growth J Invest Dermatol 2002 118 11 16 11851870 10.1046/j.1523-1747.2002.01644.x Berth-Jones J Hutchinson PE Vitamin D analogues and psoriasis Br J Dermatol 1992 127 71 78 1390159 Kragballe K Treatment of psoriasis with calcipotriol and other vitamin D analogues J Am Acad Dermatol 1992 27 1001 1008 1479078 Halgren RG Traynor AE Pillay S Zell JL Heller KF Krett NL Rosen ST 8Cl-cAMP cytotoxicity in both steroid sensitive and insensitive multiple myeloma cell lines is mediated by 8Cl-adenosine Blood 2001 92 2893 2898 9763575 Gandhi V Ayres M Halgren RG Krett NL Newman RA Rosen ST 8-Chloro-cAMP and 8-chloro-adenosine act by the same mechanism in multiple myeloma cells Cancer Res 2001 61 5474 5479 11454694 Grbovic O Jovic V Ruzdijic S Pejanovic V Rakic L Kanazir S 8-Cl-cAMP affects glioma cell-cycle kinetics and selectively induces apoptosis Cancer Invest 2002 20 972 982 12449730 10.1081/CNV-120005913 Kim SN Kim SG Park JH Lee MA Park SD Cho-Chung YS Hong SH Dual anticancer activity of 8-Cl-cAMP: inhibition of cell proliferation and induction of apoptotic cell death Biochem Biophys Res Commun 2000 273 404 410 10873618 10.1006/bbrc.2000.2949 Tortora G Ciardello F Pepe S Tagliaferri P Ruggiero A Bianco C Guarrasi R Miki K Bianco AR Phase I clinical study with 8-Cl-cAMP and evaluation of immunological effects in cancer patients Clin Cancer Res 1995 1 377 384 9815994 Propper DJ Saunders MP Salisbury AJ Long L O'Byrne KJ Braybrooke JP Dowsett M Taylor M Talbot DC Ganesan TS Harris AL Phase I study of the novel cyclic AMP (cAMP) analogue 8-chloro-cAMP in patients with cancer: toxicity, hormonal, and immunological effects Clin Cancer Res 1999 5 1682 1689 10430069 Tortora G Ciardiello F Protein kinase A as target for novel integrated strategies of cancer therapy Ann N Y Acad Sci 2002 968 139 147 12119273 McDaid HM Johnston PG Synergistic interaction between paclitaxel and 8-chloro-adenosine 3',5'-monophosphate in human ovarian carcinoma cell lines Clin Cancer Res 1999 5 215 220 9918222 Lamb D Steinberg RA Anti-proliferative effects of 8-chloro-cAMP and other cAMP analogs are unrelated to their effects on protein kinase A regulatory subunit expression J Cell Physiol 2002 192 216 224 12115728 10.1002/jcp.10131 Han Z Chatterjee D Wyche JH Proliferation of nontransformed cells is inhibited by adenosine metabolite of but not by parental 8-Cl-cyclic AMP J Pharmacol Exp Ther 1993 265 790 794 8388460 Noguchi K Murata T Cho-Chung YS 8-Chloroadenosine 3',5'-monophosphate (8-Cl-cAMP) selectively eliminates protein kinase A type I to induce growth inhibition in c-ras-transformed fibroblasts Eur J Cancer 1998 34 1260 1267 9849489 10.1016/S0959-8049(98)00051-3 Van Lookeren Campagne MM Villalba Diaz F Jastorff B Kessin RH 8-Chloroadenosine 3',5'-monophosphate inhibits the growth of chinese hamster ovary and molt-4 cells through its adenosine metabolite Cancer Res 1991 51 1600 1605 1998950 Carlson CC Burnham LB Shanks RA Dransfield DT 8-Cl-adenosine induces differentiation in LS174T cells Dig Dis Sci 2001 46 757 764 11330409 10.1023/A:1010740015072 Carlson CC Chinery R Burnham LB Dransfield DT 8-Cl-adenosine-induced inhibition of colorectal cancer growth in vitro and in vivo Neoplasia 2000 2 441 448 11191111 10.1038/sj.neo.7900106 Dransfield DT Griner RD Ray S Keskintepe M Bollag WB 8-Cl-adenosine induces growth arrest without differentiation of primary mouse epidermal keratinocytes J Invest Dermatol 2001 117 1588 1593 11886527 10.1046/j.0022-202x.2001.01572.x Hu PP-C Datto MB Wang X-F Molecular mechanisms of transforming growth factor-β signaling Endocr Rev 1998 19 349 363 9626558 10.1210/er.19.3.349 Dahler AL Cavanagh LL Saunders NA Suppression of keratinocyte growth and differentiation by transforming growth factor β1 involves multiple signaling pathways J Invest Dermatol 2001 116 266 274 11180003 10.1046/j.1523-1747.2001.01243.x Fogh K Kragballe K Vitamin D3 analogues Clin Dermatol 1997 15 705 713 9313969 10.1016/S0738-081X(97)00021-7 Griner RD Qin F Jung EM Sue-Ling CK Crawford KB Mann-Blakeney R Bollag RJ Bollag WB 1,25-Dihydroxyvitamin D3 induces phospholipase D-1 expression in primary mouse epidermal keratinocytes J Biol Chem 1999 274 4663 4670 9988703 10.1074/jbc.274.8.4663 Bollag WB Ducote J Harmon CS Biphasic effect of 1,25-dihydroxyvitamin D3 on primary mouse epidermal keratinocyte proliferation J Cell Physiol 1995 163 248 256 7706369 Bollag WB Dodd ME Shapiro BA Protein kinase D and keratinocyte proliferation Drug News Persp 17 117 126 Lebwohl M Menter A Koo J Feldman SR Combination therapy to treat moderate to severe psoriasis J Am Acad Dermatol 2004 50 416 430 14988684 10.1016/j.jaad.2002.12.002 Missero C Calautti E Eckner R Chin J Tsai LH Livingston DM Dotto GP Involvement of the cell-cycle inhibitor Cip1/WAF1 and the E1A-associated p300 protein in terminal differentiation Proc Natl Acad Sci USA 1995 92 5451 5455 7777529

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==== Front BMC Cardiovasc DisordBMC Cardiovascular Disorders1471-2261BioMed Central London 1471-2261-4-121528387110.1186/1471-2261-4-12Study ProtocolA randomised controlled trial and cost effectiveness study of systematic screening (targeted and total population screening) versus routine practice for the detection of atrial fibrillation in the over 65s: (SAFE) [ISRCTN19633732] Swancutt Dawn 1d.r.swancutt@bham.ac.ukHobbs Richard 1f.d.r.hobbs@bham.ac.ukFitzmaurice David 1d.a.fitzmaurice@bham.ac.ukMant Jonathan 1j.w.mant@bham.ac.ukMurray Ellen 1e.t.murray@bham.ac.ukJowett Sue 1s.jowett@bham.ac.ukRaftery James 2j.p.raftery@bham.ac.ukBryan Stirling 2s.bryan@bham.ac.ukDavies Michael 3michael.davies@uhb.nhs.ukLip Gregory 4G.Y.H.Lip@bham.ac.uk1 Department of Primary Care and General Practice, The University of Birmingham, Birmingham, UK2 Health Economics Facility, The University of Birmingham, Birmingham, UK3 Department of Cardiology, Selly Oak Hospital, Birmingham, UK4 University Department of Medicine, City Hospital, Birmingham, UK2004 29 7 2004 4 12 12 3 3 2004 29 7 2004 Copyright © 2004 Swancutt et al; licensee BioMed Central Ltd.2004Swancutt et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background Atrial fibrillation (AF) has been recognised as an important independent risk factor for thromboembolic disease, particularly stroke for which it provides a five-fold increase in risk. This study aimed to determine the baseline prevalence and the incidence of AF based on a variety of screening strategies and in doing so to evaluate the incremental cost-effectiveness of different screening strategies, including targeted or whole population screening, compared with routine clinical practice, for detection of AF in people aged 65 and over. The value of clinical assessment and echocardiography as additional methods of risk stratification for thromboembolic disease in patients with AF were also evaluated. Methods The study design was a multi-centre randomised controlled trial with a study population of patients aged 65 and over from 50 General Practices in the West Midlands. These purposefully selected general practices were randomly allocated to 25 intervention practices and 25 control practices. GPs and practice nurses within the intervention practices received education on the importance of AF detection and ECG interpretation. Patients in the intervention practices were randomly allocated to systematic (n = 5000) or opportunistic screening (n = 5000). Prospective identification of pre-existing risk factors for AF within the screened population enabled comparison between high risk targeted screening and total population screening. AF detection rates in systematically screened and opportunistically screened populations in the intervention practices were compared to AF detection rate in 5,000 patients in the control practices. ==== Body Background Atrial fibrillation (AF) has been recognised as an important independent risk factor for thromboembolic disease, particularly stroke with which it is associated with a five fold increase in risk [1]. There are few data on the prevalence of AF in the United Kingdom. Local data derived from the Echocardiographic Heart of England Screening (ECHOES) study suggested a prevalence of AF in people over the age of 65 of 3.8% (95% CI: 2.5–5.1) [2]. A review of four large community based studies of AF suggested that the overall community prevalence in the United States is 0.89% [3]. In these studies, the prevalence increased sharply with age: 2.3% of people aged 40 or over; 5.9% of people aged over 65 (higher than the local estimate), and 10% of those over 80. The vast majority (84%) of people with AF are over the age of 65. AF is a particularly important risk factor for stroke in the elderly – while 15% of all strokes are associated with the arrhythmia, it is associated with 36% of strokes in people over the age of 80. The incidence of new cases of AF in people over the age of 65 is of the order of 1% per annum [4]. Screening for AF in the elderly fulfils many of the Wilson-Jungner criteria for a screening programme [5]. It is a common and important condition which can be diagnosed by means of a simple test, and the risk of serious sequelae such as stroke can be dramatically reduced by treatment. One UK study has compared systematic nurse-led screening with prompted opportunistic case finding for AF in primary care [6]. This small scale study (four practices, n = 3001) demonstrated that systematic nurse-led screening detected more cases than opportunistic case finding, however most of those cases detected were already diagnosed. Two further single practice based studies have investigated the role of practice nurses in the screening process [7], and whole population screening [8]. 5% of total NHS expenditure can be attributed to stroke, and there would be expected to be about 1,000 new cases of stroke per annum in a typical health authority of a half million population. Therefore, any programme that might lead to an important reduction in stroke incidence needs serious consideration, both because of the potential for health gain, and the potential for reduced overall NHS expenditure. Screening for AF might be one such programme since, in population terms, AF is an important risk factor for stroke and anticoagulation provides a highly effective treatment to reduce this risk. A meta-analysis of randomised controlled trials has shown a 68% relative risk reduction in patients' with AF receiving oral anticoagulation [9]. It has been estimated that optimal treatment of AF in the population might reduce the overall incidence of stroke by 10%. However, before implementing screening programmes, unresolved questions over how the screening should be conducted must be answered. The appropriate screening strategy to be employed Opportunistic screening The simplest strategy was opportunistic case finding, where a health care professional took the opportunity to feel a patient's pulse during a consultation. If the pulse is irregular, they might make a clinical diagnosis of AF, or request/perform an electrocardiogram (ECG) as a confirmatory test. However, opportunistic case finding is likely to miss a significant proportion of people who would otherwise have benefited from treatment. For example, detection of hypertension in general practice was traditionally detected in an opportunistic way until the introduction of health checks with the 1990 GP contract. The Health Survey for England shows that in 1991, 42% of the population over the age of 75 had hypertension for which they were not taking any medication [10]. This figure had fallen to 31% by 1994, after the GP contract had taken effect. Targeted screening One possible approach was to screen patients who are at higher risk of AF – a targeted screening programme. Cardiac failure, hypertension and rheumatic heart disease are important precursors of AF [7]. AF is more common in people with a history of myocardial infarction, angina, diabetes mellitus, hyperthyroidism, stroke or transient ischaemic attack (than in people without these conditions) [11]. Most general practices were computerised, and some have disease registers. A targeted screening programme could exploit these to identify such high risk patients, either through disease registers, or through prescribing information on the computerised records. Whole population screening Another approach was to screen everyone 65 and over (65+) for AF – a whole population screening programme. A modelling exercise using decision analysis to inform on the methodology for this study indicated that there were not sufficient primary data available to recommend which of these (targeted or whole population) would be the optimum policy The most appropriate screening test for AF 12-lead ECG is recognised as the gold standard test, but this test is time consuming (taking at least 15 minutes to perform in an outpatient setting). Therefore, it is important to consider simpler tests. This study assessed simpler methods compared to the gold standard, both in terms of accuracy, time taken and patient acceptability. These include taking the pulse, and simpler ECGs. Interpreting the ECG Cardiologists offer the most accurate readings of ECGs, but can satisfactory interpretations be obtained by the GP, the practice nurse, or computerised diagnostic software? This study assessed the accuracy of these different approaches to interpreting the ECG. The value of echocardiography The main treatment options to reduce risk of stroke in patients' with AF are currently warfarin or aspirin. Aspirin is much less effective than warfarin – it achieves a barely significant 21% reduction in stroke risk [9]. However, it is safer to use, since it confers a lower risk of serious haemorrhage. Therefore, in practice, the clinical decision as to which treatment to use depends upon the balance of risks and benefits for the individual patient. Thromboembolic risk is currently determined primarily on clinical criteria. Data from the SPAF study [12] suggested that echocardiography (Echo) may inform on risk stratification, assisting in therapeutic decision making. The role of routine Echo for patients with AF identified in the community remains to be proven. Data also needs to be quantified regarding the cost effectiveness of Echo versus clinical impression alone. Studies have suggested that the clinical utility in people aged over 74 is poor [13,14]. Therefore this study focused on patients aged 65–74. Once somebody has been identified as having AF, should they also receive an echocardiogram to assess their risk of stroke, or is clinical assessment of risk adequate? Optimum strategy This study, by providing answers to these questions, allowed the optimum strategy for introducing a screening programme for AF in the over 65s to be determined. However, before a decision is made as to whether to institute a screening programme, not only must the question of the best strategy be considered, but also, the question of whether any screening programme at all should be introduced. This study provided data to assist in answering this fundamental question by providing: i) An accurate estimate of the community prevalence and incidence of AF in over 65s; ii) An assessment of the health economic implications of screening for AF; iii) An assessment of the service provision implications of implementing such a programme; iv) An assessment of the impact on patient quality of life and anxiety after various screening methodologies. Health economics of screening Although the cost effectiveness of different approaches to screening is often put in terms of the average cost per case detected, such an approach ignores the sensitivity and specificity of the screening test. This is because average cost per case detected focuses entirely on true positives, paying no attention to false positives, false negatives and true negatives. False positives and false negatives impose costs on patients and health services which would be neglected if the focus was confined to true positives [15]. An undue emphasis on the average cost per case detected could justify opportunistic screening of a small number of high risk patients who present, with no consideration of the number of cases missed. This study compared the incremental cost per case detected for different methods of AF screening. This refers not to the average cost but rather approximates the incremental cost per case detected in moving from one of the screening options to another. Use of incremental cost per case detected by option shows how the cost per additional case detected is likely to increase as the intensity of screening increases. This method has been used to deal with similar uncertainties about the cost effectiveness of screening for other diseases, including breast and colorectal cancer and has been recommended by the US guidelines [16]. Objectives Primary objective • To determine baseline prevalence and the incidence of AF based on a variety of screening strategies and in doing so to evaluate the incremental cost-effectiveness, in terms of cost per case identified, of the different screening strategies (targeted or whole population screening) compared with routine clinical practice for detection of AF in people aged 65 and over. Secondary objectives • To evaluate the relative cost-effectiveness of screening methods for AF diagnosis, comparing 12 lead ECG (gold standard) with pulse taking, lead II rhythm strip from standard ECG limb leads alone and single lead thoracic placement ECG. • To evaluate the most cost-effective method of test interpretation, comparing cardiologist (gold standard), with GP, practice nurse, or computerised diagnostic software. • To assess the differing combinations of screening strategies and procedures in terms of patient acceptability and impact on patient quality of life, including any psychological effects of screening. • To determine the community prevalence of AF in people 65+. • To evaluate the value of clinical assessment and echocardiography as additional methods of risk stratification for thromboembolic disease in patients with AF. • To evaluate the service provision implications should screening for AF become a national programme, and identify the optimum screening algorithm for identification of patients with AF. Outcome measures Primary outcome • The incidence of AF according to a variety of screening strategies • The associated costs providing an incremental cost per case detected. The cost data was collected from an NHS and patient perspective. It has focused on resources required to establish screening, time taken to complete screening and the cost of the equipment. Secondary outcomes • Cost effectiveness of 4 different methods of screening for AF. The cost data focused on the difference in the cost of the equipment and the time taken for each of the different methods of screening to be completed. This was from both an NHS and patient perspective. • Cost effectiveness of 4 different methods of ECG interpretation. The cost data focused on the difference in the cost of the grade of staff interpreting the ECG and the accuracy of their interpretation. • Overall community prevalence and incidence of AF • Patient acceptability to AF screening was measured using an adapted version of the screening specific questionnaire used in the Colorectal Screening Programme [18]. Patient uptake of screening was also monitored. The impact on quality of life was assessed using EQ-5D [24,25]. Patient anxiety was measured using the Spielberger 6 item Anxiety Questionnaire [17]. • Modelling techniques were used to identify the implications of AF screening on health service provision nationally. This included the effect on echocardiography and anti-coagulation clinic provision. Methods This was a multi-centre randomised controlled trial. The study schema is shown in figure 1. Figure 1 Study schema for the multi-centre randomised controlled trial. 50 computerised general practices within the West Midlands were recruited through MidReC (Midlands Research Practices Consortium). This was undertaken by writing to all practices in the West Midlands and surrounding counties explaining the study and asking whether they were interested in participating. Practices showing an interest were given further information about the study and invited to attend an investigators meeting. Following the investigator meetings sixty practices interested in participating in the project were randomised (stratified based on Townsend score and practice list size): 25 as intervention, 25 as control practices with 10 reserve practices. A computerised list of all patients aged 65+ was obtained from each practice, and from this a random sample of 10,000 patients from the intervention practices (representing approximately 1/3rd of the total population of patients 65+ in this group), and 5000 from the control practices (representing approx. 1/6th of the total population of patients 65+ in this group) were identified. Patients from intervention practices were randomised, by patient, to opportunistic or systematic groups. All patients within the systematic screening arm, including those with a history of AF, were invited by post to attend a screening clinic. For patients in the opportunistic arm, their notes were flagged within the practice to encourage practice staff to undertake pulse recording. Patients with an irregular pulse were invited to attend a screening clinic. Once this process had been undertaken, the flag was removed from the notes and returned to the research team. The screening clinic was run by practice nurses. Patients gave informed consent. Data collected was baseline information, past medical history (including any previous diagnosis of AF), radial pulse and a 12 lead ECG. The 12 lead ECG was performed using an electronic ECG machine which allowed print-out of single lead thoracic placement ECG and a rhythm strip of lead 2 using limb leads from standard ECG. All 12 lead ECGs were sent to two cardiologists for reporting (GL, MD). Where there was disagreement over the diagnosis a third cardiologist was used to decide. The cardiologists were asked to state whether the ECG showed AF or not, and to state whether there were any other significant abnormalities. Patients were informed of the result within two weeks. Patients with normal ECGs were informed of this, patients with any abnormality were asked to make an appointment with their GP. At the GP appointment patients with AF aged 65 – 74 were offered echocardiography. GPs were asked to make a clinical decision as to thromboprophylaxis both before and after the echocardiogram. Patients with other ECG abnormalities were managed as clinically indicated. At the end of the screening process, GPs and Practice Nurses from both intervention practices (who had received education on ECG interpretation) and control practices (who had received no education) were sent ECGs to interpret for the presence or absence of AF. All ECGs recorded within the study were printed off as either 12 lead, single lead thoracic placement or limb lead recordings. Allocation to ECG type was random and resulted in three equal ECG groups. In order for each interpreter to read all three types of ECG, batches of ECGs were collated with the same numbers of each type of ECG. Allocation to a batch was also random. In total, there were 25 batches of ECGs to match the number of practices in each arm. The GP and Practice Nurse from the same practice read the same batch of ECGs and each batch was read by one control practice and one intervention practice. Therefore each ECG was read by two GPs and two Practice Nurses. All ECGs were anonymised, and practices did not receive any ECGs from their own practice. The interpreters were given a sheet to fill in to indicate for each ECG the presence or absence of AF. All ECGs (as 12 lead) were also analysed by the specific software package accompanying the electronic ECG and results recorded. Patient acceptability and quality of life for different screening strategies were established using EuroQol (EQ-5D) combined together with the Speilberger 6-item Anxiety Questionnaire. EQ-5D allowed the measurement of broad aspects of quality of life. The shortened Speilberger anxiety questionnaire also has proven validity and is more specific to anxiety than is the SF-12 [17]. An adapted version of the screening-specific tool used in the Colorectal Screening Programme [18] was used to assess the acceptability of the screening process. A random sample of 750 patients (375 screened patients and 375 opportunistically screened patients) were sent postal versions of the psychological instruments (EQ-5D and Spielberger) on entry to the study (i.e. before the intervention group has received their invitation to attend for screening). One reminder was sent a month later to non-responders. The same questionnaires were sent to the same groups plus those patients who had screened postive at the end of the screening period, approximately 17 months later. This allowed a non-randomised comparison between the effects on quality of life and anxiety in screen positive and screen negative patients. In addition, all patients who were screened were asked to complete the acceptability and Spielberger questionnaire immediately after screening. The patient acceptability questionnaire was also administered to all patients who proceeded for echo. The value of clinical assessment and echocardiography in risk stratification were determined in patients aged 65–74. This compared GP assessment based on the Birmingham guidelines for thromboprophylaxis in AF with any changes in recommendations for treatment once echocardiography results were available to the GP. Sample size and power calculations The assumptions for the power calculations were that patients aged 65 and over represent 17% of the total population; that 40% of study population will be in the high risk group. Also assuming that: 1. Minimum worthwhile change in detection rate was 1% for targeted screening versus routine practice. It is estimated that this change would equate to £10,000 per life year gained. This is based on the following assumptions: a) 60% of new cases of identified AF would be suitable candidates for warfarin b) Annual risk of stroke in this population was 5%, reduced by 60% to 2% if treated c) Costs: £25 to screen a patient; £100 to treat with warfarin pa; £6,000 NHS costs to treat a stroke 2. 50% of patients with AF will be already known to their general practitioner (estimates range from 30% [19] to 76% [20]) 3. Community prevalence of AF in this population was 6% [2] See figure 1. It was assumed that the baseline prevalence of AF known to the practice (A1) would be 3% (i.e. half of real prevalence of 6%) and that the prevalence of known AF in the control practices would remain constant over the screening period. Thus, the change in the prevalence of known AF in the control practices between baseline to follow up (C2-C1) should be approximately 0%. The change in the GP educated arm (B2-A1) should be marginally higher and is assumed to be between 0 and 1%. The change in the systematic screening arm should, on average, be between 0 and 3% and was assumed to be approximately 2% for the total screening arm (A3-A1) and in the high risk arm (A2-A1) was approximately 3%. All sample size calculations were for 90% power and 5% significance levels unless otherwise stated. a) To detect a 1% difference in detection rate between intervention (GP educated) and control practices (B2-A1) vs (C2-C1). This requires 1,236 patients. However, since this is a difference based at the practice level of randomisation, it needed to be inflated by the design factor. Based on AF prevalence data from the EcHoES (Echocardiographic Heart of England Screening) Study [2], the between practice variance is 3.7 and the within practice variance is 246. This gave an intra-cluster correlation coefficient of 0.015. The most efficient design in this circumstance would be a cluster size of 200, which gives a design factor of 4. Therefore, 5,000 patients would be needed in 25 practices in both intervention (GP educated) and control groups. b) To detect a 1% difference in detection rate between intervention (Systematic screening total arm) and control practices (A3-A1) vs (C2-C1). This requires 1,236 patients but when scaled by the design factor of 4 required 5,000 patients. c) To detect a 1.8% difference in detection rate between intervention (Systematic screening high risk arm) and control practices (A2-A1) vs (C2-C1). This requires 684 patients. However, since this is a difference based at the practice level of randomisation, it also needed to be inflated by the design factor. This meant that 2,736 patients would be needed in each arm. Since the ratio of patients in the two arms is 2:5 this means that 1,916 patients would be needed in the high risk arm and 4,789 in the control arm. With the 2,000 patients expected to be at high risk in this arm – resulting from the 5,000 needed for the previous comparison there were more than enough patients to detect the required difference. Although comparison b) required fewer patients to detect the expected difference (2%) stated in the assumptions, it would be possible to detect differences as low as 1%, should the detection rate not be as high as expected. The a), b) and c) comparisons are all at practice level randomisation. d) To detect a 1% difference in detection rate between high risk screening strategy and routine practice prompted by education (opportunistic arm) (A2-A1) vs (B2-A1).This requires 1,236 patients in both the high risk systematic screening and the GP educated (opportunistic) screening arms of the intervention practices assuming the high risk screening detects a 1% increase and opportunistic screening detects 0% increase. Should the increased detection rates be higher in each arm (1.7% in the high risk arm and 0.7% in the opportunistic arm) then this could require 2,686 patients in each arm. However, since there is a ratio of 2:5 patients in these arms there will be sufficient patients as only 1,880 are needed in the high risk arm and 4,700 in the opportunistic arm to be able to detect this 1% difference. e) To detect a 1% difference in detection rate between total screening strategy and routine practice prompted by education (opportunistic arm) (A3-A1) vs (B2-A1).This requires 3,300 patients in both the total screening and the GP educated (opportunistic) screening arms of the intervention practices. f) To detect a relative risk (RR) of 2 (1% detection rate difference) between total population and high risk screening (A3 vs A2).It was assumed that 40% of the study population fall into the high risk group, and the prevalence of undetected AF is 3%. This meant that 1,434 patients would be needed in each of the two risk groups to detect a two fold difference in risk (i.e. RR of AF in high risk as compared to low risk group is 2). This RR of 2 equates to an increase in AF detection rate from 3% in the total population arm to 4% in the high risk arm. Since there was a 40:60 split in the two risk groups unequal sample size calculations only require a minimum of 1,200 patients in the high risk group and 1,800 in the moderate/low risk group. This was achievable with a screening arm of 5,000 patients, as there would actually be 1,320 in the high risk group and 1,980 in the moderate risk group if a 66% screening acceptance rate was assumed. Sample size for quality of life assessment Although some of the variances are from North American populations we have no reason to suspect that the variation will be different in a British population since data from the ECHOES study on the SF36 gives variations very similar to the North American norms. Spielberger The shortened (6-item) version of the Spielberger state anxiety questionnaire has been validated and used in populations different from that under consideration in SAFE, namely it tends to have been used in young and mostly female populations [17,21,22]. The variance obtained from these papers appears to be approximately 144 for Marteau [17] but higher for the Ubhi [22] paper. However, the women in the latter paper were being informed of major illness outcomes (either benign or malignant breast cancer). A full Spielberger on people undergoing physiological tests also gave a variance of the order of 144 [23]. The full version of the Spielberger state anxiety when used with an elderly population also seems to give a variance that is not too far from the previously mentioned papers being 188.8 [23]. Taking this latter value as being the nearest to our population we can detect a 4 point difference in the mean values obtained with 249 patients in each arm. EQ5D The VAS scale The VAS variance as reported for an elderly population aged 75 and over was 365 [24] but for a group of recovered stroke patients (ages not given) it was approximately 100 [25]. Taking the former value as a worst case this means it will be possible to detect a 6% difference between groups on the VAS with 213 patients within each group. The Utility index This was reported in different ways in the Johnson [24] and Dorman [25] papers. Using the utility values from the Dorman et al paper the variance is approximately 0.066 and this allows us to detect a 0.1 difference with 139. Using the Johnson paper the variance is approximately 576 and using this means that we can detect a mean change of 7 with 247 patients in each arm. Statistical analysis Intention to treat analysis will be used. Any previously known Atrial Fibrillation cases will be subtracted from the totals obtained at the end of the study to ensure there is no double counting in the incidence figures. Chi-squared, independent t-tests and log-linear models will be used to describe demographic data. If there are differences between the groups this may need to be adjusted for in later analyses. Primary objective: to determine baseline prevalence and incidence of AF on a variety of screening strategies Proportions and rates will be used as the measures of prevalence and incidence. The independent t-test and ANOVA with random effects (as appropriate) will be used to examine the detection rate differences between the intervention and control screening strategies. Should the data be strongly non-normal a non-parametric equivalent will be used. Secondary objectives a) to assess patient acceptability and impact on QoL of different screening strategies The independent and related t-test and ANOVA will be used to examine the differences between the intervention screening strategies on the Spielberger and EuroQol EQ5D. Should the data be strongly non-normal a non-parametric equivalent will be used. Chi squared tests will be used on the screening tool. b) to assess the value of echocardiography in risk stratification for thromboembolic disease in patients with AF McNemar's test will be used to see whether there is any significant change in the doctor opinion on risk of CVA and treatment decision before and after echo screening. c) to evaluate the most cost effective method of test interpretation The cost effectiveness will be covered in the economic section. However, the use of sensitivity, specificity, Cohen's κ and conditional logistic modelling will allow for comparison of the various methods for detecting AF between the GPs, nurses and consultants. d) to evaluate the most cost effective method of screening This will be covered in the economic analysis section. Multivariate and logistic modelling analyses will be undertaken in order to determine which markers might be the best predictors of the presence of AF. This will act as confirmatory analysis for the risk factors used in the screening strategy to define a high risk patient. Economic analysis Framework for the economic analysis This trial evaluated a large number of alternative screening scenarios for identifying atrial fibrillation (2 screening strategies i.e. target v population; 6 screening methods i.e. pulse plus 3 types of ECG if pulse abnormal, and 3 types of ECG regardless of pulse; and 4 screening test interpretations, making 2*6*4 = 48 plus control and opportunistic screening = 50). The study has been powered to detect a difference in the targeted versus population arms, and in systematic screening versus routine clinical practice. However, the economic analysis will compare the cost-effectiveness of all alternative screening approaches using a modelling framework, whereby data will be drawn from the trial (where appropriate and available) and from external sources. The use of a modelling approach allows the timescale for the economic analysis to be extended beyond the follow-up period allowed for in the trial. The use of such extrapolation will enable estimation of the incremental cost-effectiveness ratios (ICERs) for each approach: Incremental cost per case detected Incremental cost per life year gained Incremental cost per quality-adjusted life year (QALY) gained Data on consequences The use of EQ-5D allows the measurement of broad aspects of quality of life. EQ-5D allows changes in health status to be measured but also valued, using the University of York Measurement & Valuation of Health general population survey tariff [27]. Cost data The cost analysis adopted a broad perspective to include costs incurred within the health sector and by patients and carers. Data collection was undertaken on all trial patients in order to allow a stochastic cost analysis to be conducted. The focus of the data collection will be upon the key cost drivers which will include: a) the resources required to establish screening (invitation to patient, follow ups, communication of results), b) the time taken to carry out the various tests, and c) the cost of the equipment (expressed as cost per test). a), b) and c) will be based on data collected in the study. The analysis adopted an incremental approach such that data collection concentrated on resource use differences between alternative screening scenarios. The process of collecting data on resource use was undertaken separately from data collection on unit costs. Resource use data on the screening process was principally collected within the trial. Unit costs were collected from published sources and a representative sample of NHS providers in order to increase generalisability. The methods used in collecting data will include patient questionnaires (see above) and review of patient records (both GP and hospital). Data on private costs were collected from a survey of a sub-cohort of the trial population. Cost effectiveness analysis The plan for the analysis is: 1. Report a cost consequence analysis, which will involve providing a full description of all important results relating to costs and consequences. 2. Conduct both a cost-effectiveness analysis and a cost utility analysis (using data on true positive cases detected as the measure of effect and data on EQ-5D to estimate QALYs). An incremental approach will be used in order to compare the large number of alternative screening strategies. We are interested in comparing the mean costs per patient since our concern is with predicting overall programme costs. However, the data on costs are likely to have a skewed distribution. Therefore, the plan for the analysis of costs is: 1. To explore the nature of the distribution of costs 2. If required, to use non-parametric comparison of means (e.g. bootstrapping) 3. If the distribution of the data is approximately normal, parametric methods will be used. This approach is in line with recent recommendations [26]. If missing data are a problem at the economic analysis stage, then imputation techniques will be employed. Longer term costs and consequences will be explored by extrapolating beyond the end of the trial using a modelling framework using data from a range of trial and non-trial sources. The precise form of modelling is yet to be determined, but is likely to be either Markov or Discrete Event Simulation, depending upon the extent to which the Markov assumptions are justified. An advantage of using such an approach is that it will allow the additional costs of increasing survival to be explicitly incorporated into the analysis. In particular, modelling will provide estimates of the optimal frequency of screening for AF, based on the estimates of incidence and prevalence from the trial. Identifying untreated patients with AF will have implications for service provision. These will depend upon the prevalence of atrial fibrillation, the screening mechanism employed, the use made of echocardiography, and the additional requirements for anticoagulation monitoring. The separate parallel study, BAFTA, will provide empirical data that will allow such implications for service provision to be assessed. The modelling exercise, which will draw on both SAFE and later BAFTA results, will combine best estimates of both screening and anticoagulation options. The robustness of the results of the economic analysis will be explored using sensitivity analysis [27]. This will explore uncertainties in the trial based data itself, the methods employed to analyse the data and the generalisability of the results to other settings. Uncertainty in the confidence to be placed on the results of the economic analysis will be explored by estimating cost-effectiveness acceptability curves. These plot the probability that the intervention is cost-effective against threshold values for cost-effectiveness. Inclusion and exclusion criteria Inclusion criteria Patients aged 65 years or over (65+). Exclusion criteria Patients who were terminally ill. Randomisation Randomisation of practices and patients was performed by statisticians from the Department of Primary Care and General Practice at The University of Birmingham. Cluster randomisation of practices to intervention or control was stratified by Townsend quartiles and practice size. Computer searches were carried out to identify cases of known AF, within the sample of patients identified above, using a published strategy [15]. The randomisation of patients within the intervention practices ensured that the study patients in each practice were divided equally between systematic and opportunistic screening arms and also that there was an even distribution of patients with known AF between the two arms. Patients within the systematic screening arm were identified by computerised record searching as either being at high risk (target population) or moderate risk (non-target population) of AF by recognised criteria [28,11]. Cleaning of lists post randomisation Following initial sampling of the total population the list of patients from each practice were returned to the practices who were asked to remove any patients who had died, moved or were terminally ill. Patients removed following this process were replaced with patients from a reserve list, which had been randomised at the same time as those on the initial lists. Patient information and consent Patients aged 65+ who were selected to the systematic screening arm received an information sheet with an invitation letter to attend the ECG clinic. Entry to the trial was discussed with the practice nurse at the clinic. The practice nurse then obtained written consent from those patients who were willing to participate. Study patients found opportunistically to have an irregular pulse were given an information sheet and invited to attend the screening clinic. Practice staff education and ECG training GPs and other members of the primary health care team in the intervention practices attended investigator days at which they were given educational materials informing them of the importance of detection of AF, and the treatment options that are available. The materials encouraged them to consider opportunistic screening of patients. Members of the primary health care team in control practices received no educational input from the research staff. Practice nurses attended an ECG training day prior to starting the ECG screening clinics. Training included how to perform an ECG (using the Biolog) to ensure a standardised high quality tracing and basic ECG interpretation (specifically how to identify AF). Computerised and note searches of GP records Prevalence and incidence data Computer searches were carried out to identify cases of probable AF in the 15,000 study patients using a published strategy [15]. Searches were tailored towards the information that is held on computer in each practice. If practices hold AF registers, or use READ diagnosis coding, then these were used. In addition, a search was carried out to identify prescriptions of digoxin, a beta-blocker, a class 1,3 or 4 anti-arrhythmic agent, aspirin or warfarin. This information was recorded into computerised case report forms. Case notes of patients identified as 'known' or 'probable' AF in any of these computer searches were reviewed for mention of a diagnosis of AF. AF diagnosis were drawn from hospital letters stating the existence of the condition or ECG recordings from the last 5 years. An additional 5% random sample of case notes of patients not identified as 'known' or 'probable' AF by computer searching were reviewed (750 in all) to estimate how many other patients who are known to have AF were not identified by the computer searches. If this had revealed a significant number of extra cases of known AF, then the sample size for manual searching would have been increased to allow a precise estimate of the baseline rate of known AF. Unidentified extra AF cases were not found to be significant so no additional note search was required. The same computer searches on both intervention and control practice patients notes were performed prior to, and 12 months after, commencement of screening. Screening clinics All patients in the systematic screening arm and those found to have an irregular pulse in the opportunistic screening arm of the study were invited to attend an ECG screening clinic. At the clinic the practice nurse explained the aims of the study and answered any questions about the study. Written informed consent to participation in the study was obtained from the patient. The nurse then recorded baseline information on age, sex, present smoking and alcohol status and past medical history, including previous diagnosis of AF, and any treatment the patient may be receiving for AF. Radial pulse rate, and whether regular or irregular, was noted. A 12 lead ECG, the gold standard by which other traces were compared, was then recorded using the Biolog machine, which was also able to produce a trace corresponding to the single lead thoracic placement and a rhythm strip of lead II. Finally, the patient was asked to complete an acceptability questionnaire. Discussion This study will identify the most cost-effective strategy for identifying atrial fibrillation in patients aged 65 and over. The policy implications will be dependent on the findings and one of the strengths of the current study is the utilisation of modelling techniques to investigate the implications of different screening strategies and frequency of screening within different health care environments. The initial draft of the report has been submitted to the Department of Health and publication of the results should be expected later this year (2004). Competing interests None declared. Authors' contributions RH and DF were principal investigators. EM and SJ were project managers. DS collected data and prepared the first draft of the paper. JM, EM, JR, SB, MD and GL all contributed to the project design. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here: Acknowledgements Funding: NHS R&D HTA programme, Grant number: 96/22/11 DA Fitzmaurice is funded by an NHS Career Scientist Award ET Murray is funded by an MRC Health Services Research Fellowship ==== Refs Wolf PA Abbott RD Kannel WB Atrial fibrillation as an independent risk factor for stroke: the Framingham Study Stroke 1991 22 983 8 1866765 Davies RC Hobbs FDR Kenkre JE Roalfe AK Hare R Lancashire RJ Davies MK Prevalence of left ventricular systolic dysfunction and heart failure in high risk patients: community based epidemiological study BMJ 2002 325 1156 1161 12433768 10.1136/bmj.325.7373.1156 Feinberg WM Blackshear JL Laupacis A Kronmal R Hart RG Prevalence, age distribution, and gender of patients with atrial fibrillation Arch Int Med 1995 155 469 473 7864703 10.1001/archinte.155.5.469 Wolf PA Abbott RD Kannel WB Atrial fibrillation: a major contributor to stroke in the elderly – the Framingham study Arch Int Med 1987 147 1561 64 3632164 10.1001/archinte.147.9.1561 Wilson JMG Jungner G The principles and practice of screening for disease WHO Public Health papers 1968 34 World Health Organization, Geneva Morgan S Mant D Randomised trial of two approaches to screening for atrial fibrillation in UK general practice BJGP 2002 52 373 380 Somerville S Somerville J Croft P Lewis M Atrial fibrillation: a comparison of methods to identify cases in general practice BJGP 2000 50 727 729 Wheeldon NM Tayler DI Anagnostou E Cook D Wales C Oakley GDG Screening for atrial fibrillation in primary care Heart 1998 79 50 55 9505919 Atrial fibrillation investigators The efficacy of aspirin in patients with atrial fibrillation: analysis of pooled data from 3 randomised trials Arch Int Med 1997 157 1237 1240 9183235 10.1001/archinte.157.11.1237 Colhoun H Prescott-Clarke P eds Health Survey for England 1994: findings London: HMSO 1996 1 Langenburg M Hellemons BSP van Ree JW Atrial fibrillation in elderly patients: prevalence and comorbidity in general practice BMJ 1996 313 1534 8978233 SPAF Investigators Predictors of thromboembolism in atrial fibrillation Ann Int Med 1992 116 6 12 1727097 Kalra L Perez I Melbourn A Risk assessment and anticoagulation for primary stroke prevention in atrial fibrillation Stroke 1999 30 1218 1222 10356103 Sudlow M Thomson R Thwaites B Rodgers H Kenny RA Prevalence of atrial fibrillation and eligibility for anticoagulation in the community The Lancet 1998 352 1167 1171 9777832 10.1016/S0140-6736(98)01401-9 Cairns J Shackley P 'Sometimes sensitive, seldom specific: a review of the economics of screening Health Economics 1993 2 43 55 8269046 Gold MR Cost effectiveness analysis in medicine and health OUP 1996 Marteau T Bekker H The development of a six-item short form of the state scale of the Speilberger State-Trait Anxiety Inventory (STAI) British Journal of Clinical Psychology 1992 31 301 306 1393159 Marjoram J Strachan R Allan A Allan E Screening for colorectal cancer a general practice based study BJGP 1996 46 283 286 Hobbs FDR Should all patients with atrial fibrillation be assessed by a cardiologist? Plenary session, Proceedings from Consensus Conference on the management of atrial fibrillation RCP Edinburgh, Edinburgh 1998 Sudlow M Rodgers H Kenny RA Thomson R Population based study of use of anticoagulants among patients with atrial fibrillation in the community BMJ 1997 314 1529 30 9183202 Rose P Humm E Hey K Jones L Huson SM Family history taking and genetic counselling in primary care Family Practice 1999 16 78 83 10321401 10.1093/fampra/16.1.78 Ubhi SS Wright S Clarke L Black S Shaw P Stotter P Windle R Anxiety in patients with symptomatic breast disease: effects of immediate versus delayed communication of results Annals of the Royal College of Surgeons, England 1996 78 466 469 Fraser J Kerr JR Psychophysiological effects of back massage on elderly institutionalized patients Journal of Advanced Nursing 1993 18 238 245 8436714 10.1046/j.1365-2648.1993.18020238.x Johnson JA Pickard AS Comparison of the EQ-5D and SF-12 Health Surveys in a General Population Survey in Alberta, Canada Medical Care 2000 38 115 121 10630726 10.1097/00005650-200001000-00013 Dorman P Dennis M Sandercock P Are the modified "simple questions" a valid and reliable measure of health related quality of life after stroke? Journal of Neurosurgery and Psychiatry 2000 69 487 493 10.1136/jnnp.69.4.487 Thompson SG Barber JA How should cost data in pragmatic trials be analysed? BMJ 2000 320 1197 2000 10784550 10.1136/bmj.320.7243.1197 Briggs A Gray A Handling uncertainty when performing economic evaluation of healthcare interventions Health Technology Assessment 1999 3 Kannel WB Abbott RD Savage DD McNamara PM Epidemiological features of chronic atrial fibrillation: The Framingham Study N Eng J Med 1982 306 1018 22

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10.1186/1471-2261-4-12

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==== Front BMC Fam PractBMC Family Practice1471-2296BioMed Central London 1471-2296-5-151526876410.1186/1471-2296-5-15Research ArticlePatients' perspectives on taking warfarin: qualitative study in family practice Dantas Guilherme Coelho 1gui.dantas@utoronto.caThompson Barbara V 2thompson.barb@sympatico.caManson Judith A 2judith.manson@sw.caTracy C Shawn 1shawn.tracy@sw.caUpshur Ross EG 123rupshur@idirect.com1 Primary Care Research Unit, Sunnybrook and Women's College Health Sciences Centre, 2075 Bayview Avenue, Room E3-49, Toronto, ON M4N 3M5 Canada2 Department of Family and Community Medicine, Sunnybrook and Women's College Health Sciences Centre, 2075 Bayview Avenue, Toronto, ON M4N 3M5 Canada3 Department of Public Health Sciences, University of Toronto, McMurrich Building, 12 Queen's Park Crescent W., Toronto, ON M5S 1A8 Canada2004 21 7 2004 5 15 15 3 12 2003 21 7 2004 Copyright © 2004 Dantas et al; licensee BioMed Central Ltd.2004Dantas et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background Despite the well-documented benefits of using warfarin to prevent stroke, physicians remain reluctant to initiate therapy, and especially so with the elderly owing to the higher risk of hemorrhage. Prior research suggests that patients are more accepting of the risk of bleeding than are physicians, although there have been few qualitative studies. The aim of this study was to employ qualitative methods to investigate the experience and perspective of individuals taking warfarin. Methods We conducted face-to-face interviews with 21 older patients (12 male, 9 female) who had been taking warfarin for a minimum of six months. Participants were patients at a family practice clinic situated in a large, tertiary care teaching hospital. We used a semistructured interview guide with four main thematic areas: decision-making, knowledge/education, impact, and satisfaction. Data were analysed according to the principles of content analysis. Results and Discussion Participants tended to have minimal input into the decision to initiate warfarin therapy, instead relying in great part on physicians' expertise. There appeared to be low retention of information received regarding the therapy; half the patients in our sample possessed only a superficial level of understanding of the risks and benefits. This notwithstanding, participants reported a high level of satisfaction with the care provided and a low level of impact on their day-to-day lives. Conclusions Minimal patient involvement in the initial decision and modest knowledge did not appear to diminish satisfaction with warfarin management. At the same time, care providers exert a tremendous influence on the initiation of warfarin therapy and should strive to incorporate patient preferences and expectations into the decision-making process. AnticoagulationFamily PracticePatient PreferencePrimary CareQualitative Research ==== Body Background Warfarin therapy is an effective anticoagulant indicated for the prophylaxis and/or treatment of venous thrombosis and atrial fibrillation (AF), the most common cardiac arrhythmia in older individuals [1]. Oral anticoagulation with warfarin is known to reduce the risk of disabling stroke; indeed, the benefits of oral anticoagulation have been demonstrated in a number of systematic reviews, providing high evidential support for prophylaxis [2,3]. Published guidelines on the management of AF emphasize the importance of warfarin therapy for the prevention of stroke [4]. Likewise, there is convincing evidence that long-term warfarin therapy is a highly effective method of preventing recurrent venous thromboembolism [5]. Despite the strong evidence base and the endorsement of warfarin therapy by authoritative guidelines, current prescribing patterns of warfarin remain something of a puzzle. Bungard and associates have described the 'real world' use of warfarin therapy as "sub-optimal" [6] and have estimated that only 15% to 44% of patients eligible for anticoagulation are actually prescribed warfarin [7]. Hart concurs that the use of warfarin is poor, noting that "it is often given to patients who benefit minimally, while those patients who would benefit most are not treated" [8]. Bungard and his colleagues recently conducted a systematic review of the reasons for the underuse of warfarin, identifying patient, provider, and system factors as well as identifying limitations in research studies and arguing for further research into these factors [6]. Studies employing trade-off methods to determine the risk/benefits threshold where therapy becomes acceptable have demonstrated that patients are more willing to assume risk when better informed about the medication [9]. Physicians, however, are reluctant to prescribe warfarin to elderly patients owing to concerns regarding compliance, a perceived risk of falls, and the lack of randomized controlled trial evidence in this patient population [7]. A recent study reporting the findings of interviews with individuals with a history of AF indicated that patients' health beliefs and attitudes toward death play an important role in their decision-making [10]. Clearly, the decision to initiate warfarin therapy is a complex interaction of many variables, involving patient, provider, and system factors. Most studies examining anticoagulation practices in primary care have used surveys or other forms of quantitative methods; however, given the inherent complexity of this subject matter, it is likely that qualitative research methods could provide significant additional insight. A comprehensive literature search failed to find a qualitative investigation of patient perspectives and experiences taking warfarin. The aim of this study, therefore, was to employ qualitative methods to examine the experience and perspective of individuals on long-term warfarin therapy for atrial fibrillation as a means to assess the extent to which the physician-identified barriers reported by Bungard [6] are in concordance with the unique views of patients. Methods Participants and setting This research was undertaken in a family practice clinic situated in a large, tertiary care teaching hospital. The clinic employs 12 physician full-time equivalents working in three teams; each four-physician team is supported by two registered nurses. The practice, which serves a medium-high socioeconomic status population, has a large proportion of elderly patients and the prevalence of AF is higher than reported elsewhere [1]. The prevalence of atrial fibrillation in our population as a whole is 3.9 percent. When considering different age groups, the prevalence rises as high as 18.2 percent and 18.5 percent for patients aged 80–89 and 90–99 years, respectively. A recent chart audit study found that the majority of eligible AF patients in the clinic (78%) are being treated with warfarin for stroke prevention [11]. Comprehensive anticoagulation services are provided and the clinic offers access to physicians on-call 24 hours a day. The nurses maintain an historical record of International Normalized Ratio (INR) results and warfarin dosage changes for each individual patient and, in consultation with the physicians, inform patients of prescribed warfarin dosage changes in a timely fashion, usually on the same day as the INR reading. Potential participants were identified by the clinic nursing staff. The inclusion criteria stated that the patient must currently be on warfarin therapy and have been so for a minimum period of six consecutive months. Patients were excluded from the study if a significant co-morbidity prevented their participation, if they were unable to converse in English, or if they were unwilling/unable to provide informed consent. From a pool of approximately 60 eligible candidates, the nurses purposively sampled in order to achieve an even gender split as well as an equivalent number of patients who were both normally in-range and out-of-range on their INR tests. A total of 24 patients were invited to participate in the study. Three patients declined to take part, two of whom expected to be unavailable during the interview phase, whereas the third declined due to lack of interest. All participants signed informed consent forms in advance of their participation in the study, which was approved by the Research Ethics Board of the host institution. A demographic profile of the sample is presented in Table 1. The mean age of participants was 74 years; there were 12 males, 9 females. The majority were both married (86%) and retired (86%). The mean length of time participants had been on warfarin therapy was 4.6 years (range = 1 year to 10 years). Table 1 Demographic profile of participants Code Age (years) Sex Marital Status Employment Status Years on Warfarin INR in Range? P1 67 F Widowed Retired 5 Yes P2 73 M Married Retired 10 Yes P3 84 M Widowed Retired 5 Yes P4 83 F Married Retired 4 No P5 81 F Married Retired 1 Yes P6 76 F Married Retired 3 Yes P7 75 M Divorced Retired 2 No P8 60 M Married Working 3 No P9 79 F Married Retired 5 No P10 67 F Married Retired 2 No P11 76 M Married Retired 5 No P12 80 M Married Retired 2 No P13 53 M Married Working 8 No P14 71 M Married Retired 3 Yes P15 69 M Married Retired 4 Yes P16 77 F Married Retired 5 Yes P17 78 M Married Retired 1 No P18 80 M Married Retired 10 Yes P19 71 M Married Working 7 No P20 71 F Married Retired 6 No P21 82 F Married Retired 5 Yes Data collection and analysis We utilized a semi-structured interview guide that was developed on the basis of salient issues identified in the scientific literature, specifically the various barriers to the prescription of warfarin for atrial fibrillation as reported by Bungard et al [6]. Interviewees were asked to share their experiences with warfarin in relation to four specific content areas or themes: decision-making, knowledge and education, impact on daily life, and patient satisfaction. Throughout the course of the interview, participants were provided several opportunities to raise issues or to describe experiences that had not been specifically addressed. Standard demographic information was also collected. Three of the authors (GCD, JM, and BT) shared the task of conducting the interviews. The protocol for assignment of each individual participant to an interviewing author ensured that there had been no previous clinical contact between the two parties; moreover, interviewers were blind to interviewees' INR status. The interviews lasted an average of 45 minutes and took place either in the clinic (n = 13) or in participants' homes (n = 8), in accordance with each participant's preference. Data collection ceased when, in the consensus of the research team, saturation had been reached; that is, no new ideas or perspectives were emerging. All interviews were audiotaped and transcribed verbatim. Given the pre-determined nature of the themes, as described above, we employed a content analysis approach to the analysis of the interview data. Whereas grounded theory is used to develop data-induced themes or hypotheses, content analysis is the better-suited approach in those instances where the codes, categories, or themes of interest to the investigators have been previously discovered and described [12], as is the case in the present study. Precise criteria were developed for each of the four pre-determined themes in the codebook, namely decision-making, knowledge/education, impact on daily life, and patient satisfaction. The 21 transcripts were then coded according to these criteria. Each transcript was coded by at least two members of the research team using a standardized coding form. Tests for inter-coder reliability indicated a high level of agreement among the coders; instances of disagreement were resolved through a process of discussion and negotiation that included both the fourth author and the principal investigator (CST & REGU). This process yielded a unit-by-variable matrix that allowed for substantive analysis of the data. In order to strengthen the validity of the findings, the analytic processes of coding and interpretation were reviewed by an independent external reader (DG). Results Decision-making The great majority of participants reported that the decision to initiate warfarin therapy had been made by "the doctor" – a term that was used to refer not only to family physicians and general practitioners, but also to specialists and attending physicians in urgent care settings. Typically, there was little or no patient involvement in the decision-making process (Table 2A). In most cases, this unilateral decision-making appeared to be related to the high level of trust that patients place in the medical expertise of physicians; indeed, the phrase "doctor knows best" was commonly-used in these accounts (Table 2B). For a smaller number of participants, the specific circumstances surrounding the initial decision to commence therapy served to preclude any degree of significant involvement on their part (Table 2C). Table 2 Quotations: Decision-making A. Minimal patient involvement My decision [to take warfarin]? It was the doctor's decision. (P5) I had nothing to say [regarding decision to initiate warfarin]. If the doctor tells me something, I do it. (P17) Q: What influenced your decision to take the drug? A: Well, because I was told to. Q: The main reason is that it was the physician's recommendation? A: Yes. (P20) I don't recall him [the physician] saying anything much. He said a lot of things when he examined me first, and he put me up in the ward overnight, then he started with the medications. That's all there was to it...Not really, no [no much discussion on reasons to start warfarin]. He just said that, "This is what medication we're going to put you on for the myopathy." That was it. (P11) B. Trust of physicians I just figured the doctor knows best... (P1) A: No [trouble to decide to take warfarin], because I knew nothing about it. My doctor, as far as I know, is very competent so... Q: So you are taking it basically because the doctor told you to? A: That's right. (P6) I'm at this hospital and it's got a very good reputation... Doctor knows best, I guess. They know exactly what you have to do for it, and they did it. (P14) I can recall that I had no objection. I said, "You are the experts, you are the doctors. If I get any help, I mostly will appreciate it.".... I don't think I would trust myself that much [to make the right decision]. (P15) C. Constraining effect of circumstances When I went into the [clinic] to see my doctor, they admitted me to the cardiac emergency, and they kept me there all day ... I was in for just about a week. ... and when I was discharged the doctors explained that they were putting me on to certain medications, and Coumadin was one of them. (P10) I had congestive heart failure, that's what I was in hospital for. I don't know what I was on when I was in hospital, but when I came out I had a whole slew of medications and Coumadin was one of them. (P5) I had lymphoma, and then I had a bone marrow transplant for lymphoma, and I had my spleen taken out, and I started getting deep vein thrombosis. Then I had a pulmonary embolism at one point and they started me on it [warfarin] then... I had just about every complication in the book, and this [thrombosis] was one of them. I think it was around that time, or within a year after the thromboses started, they gave me warfarin. (P13) The surgeon said I had to take it, basically. I don't like taking pills, so when I went in to get my one valve replaced, they gave me – they persuaded me – and I agreed to trying out something new that had just been approved. The reason for doing that was that I would not have to take Coumadin... Unfortunately, however, one of my other valves blew when I was in there [during surgery], so I got two for the price of one, and then there was no question I had to go on a blood thinner. (P19) Knowledge and education The level of knowledge and understanding of the benefits and risks associated with warfarin therapy tended to vary with age. Elderly patients (aged 75+) demonstrated poorer knowledge than their younger counterparts; indeed, the knowledge level among older participants appeared to be quite superficial and scattered (Table 3A). Whereas elderly patients could not explain with any degree of exactitude the rationale for taking warfarin and the associated risks, for a subset of participants, most of whom were less than 75 years old, the knowledge level was higher and, for a small number, considerably higher (Table 3B). Overall, less than half of our sample was able to name one specific benefit, risk, and lifestyle change/concern associated with warfarin therapy. Table 3 Quotations: Knowledge and education A. Superficial level of knowledge I don't really know what these different pills do for me. (P3) I'm assuming these people know what they're doing. They're not doing this for nothing. They must have good reasons, and they tell me, "Hang on there, you're doing all right. Keep it up." So I do. I don't question them. Very little, if any. I probably wouldn't know what they were talking about if they started to explain it all, and what's the point of that? (P12) Q: What do you think Coumadin is doing for you and your health? A: It makes the blood sticky, I believe, or thins it. I really don't know. Q: Do you know why they added the Coumadin? A: No idea. Q: It doesn't much matter to you? A: It doesn't matter to me. Q: Everyone's different. Some people like to know all the details. A: Oh, I couldn't care less, just as long as it keeps me alive. (P17) I hope it's [warfarin] keeping everything under control... Well, the stroke that I had, I don't feel sick, I don't have any pain, or anything. (P21) B. Superior knowledge of risks and benefits A 72-year-old male has a 30 percent chance of having a stroke regardless, but if I didn't take the Coumadin, it would be a 70 percent chance of having one. So I'm taking medication to avoid the stroke. (P14) Nobody really explained to me in full what Coumadin is all about, but I did some reading about it. I know it's a blood thinner, an anti-coagulant... helps with the atrial fibrillation that I have, because apparently blood stays longer than it should in the atrium, and if it thickens it can go to your brain and you can have a stroke. (P8) C. Patient education Q: When you started on the Coumadin, did you receive any education about the medication? A: Just that the doctor said to me that it's not 100 %, like anything else, but there's less chance [of stroke]. (P16) I said to the nurses once, "Supposing I stop taking it." They said, "Oh, I wouldn't advise it, you know, because within a month, you'd have the most severe stroke, or it would kill you, one or the other." That scared me.(P3) Q: Do you remember if you received any educational material about Coumadin? A: No. Q: Or any talk about how it works, the benefits? A: Not that I can remember. I cannot recall that, no. Q: Any pamphlets, any coloured paper, anything? A: No. Q: You don't recall? A: If I did have, I read it, then I dismissed it... I have an appetite, I can eat and drink, I can sleep, and I still can work. Anything else, to me, is not quite important. It's probably wrong. I should read them and pay more attention. (P15) Then he [physician] said, "If you go off the Coumadin for your operation, you could get a stroke. You've got a choice: you can either go off the Coumadin or you can stay on it and bleed to death." Not to death, he didn't say that. You'd bleed. The other way, you could have a stroke. That's all he said. So I presume that it could happen. (P9) Q: Is there any sort of educational material that you would like to see on warfarin? A: No. I've got a pile of books to read now, and as soon as I start to read, I fall asleep. The pamphlets would fare worse than the books. I don't think that would help. (P12) Q: Did you have many questions about it at the time [when warfarin was initiated]? A: No. You see, the darn trouble was that my wife would be sitting there, and I'd say, "She knows what it's all about; tell her." ... When you have a sit-in nurse, you know, I don't worry about that stuff [getting education on the therapy]. (P3) According to participants' accounts, educational efforts aimed at informing patients about warfarin were minimal and insufficient (Table 3C). Those who were able to recall some form of education typically referred to a "booklet" or "sheet" supplied by either the clinic or a pharmacy. In several cases, spouses were more knowledgeable than patients and appeared to play an important role in monitoring the regime. A number of participants lauded the availability of clinic staff to answer questions; however, two others reported the use of "scare tactics" by health care professionals with regard to the need to take warfarin. Impact of warfarin regime While there is tremendous range in the perceived impact of warfarin therapy on the lives of these patients, the vast majority reported that they have not experienced complications (e.g., hemorrhage, drug interactions). Typically, the decision to start taking warfarin did not precipitate significant changes in their day-to-day lives; many participants reported experiencing only minor inconveniences (Table 4A). For these individuals, warfarin is just another pill to be taken everyday; many reported the use of some reminder strategy, such as calendars, dosettes (pill boxes), or taking the pill right before some regular activity, in order to avoid missing a dose. On the other hand, a sizeable proportion (25%) of interviewees reported that adhering to the warfarin regime does impact upon their day-to-day lives. From the perspective of these patients, who were more likely to have multiple co-morbid illnesses and/or were taking multiple medications, the warfarin regime presents a considerable struggle to be managed, particularly when dosages needed to be adjusted. Regular visits to the clinic, restrictions on diet and alcohol intake, and anxiety regarding bleeding and potential drug interactions counted among the most commonly cited impacts (Table 4B). Only a small number of participants reported experiencing significant complications related to the warfarin regime, with one case involving repeated gastro-intestinal bleeding. These patients demonstrated a very high level of commitment towards their warfarin management and have placed the ritual of taking the medication at the centre of their daily routine (Table 4C). Table 4 Quotations: Impact of warfarin regime A. Minor impact Coumadin, it's just a matter of taking the pills each day and coming for a blood test and adjusting the dose. That's all. No other impact, as far as I'm concerned. (P13) I had the test [INR] done before I went to Europe. I arranged it so that two days before we flew to Europe, I had it tested, and it was 2.3, I think... The nurse said: "You might keep it this same way, and enjoy." And as soon as I got back, I came in and had it checked. (P15) It's inconvenient having to come in every week, but on the other hand, I understand. (P20) B. Moderate impact I will only drink one glass of wine a day. I like a glass of wine. They say just go easy on the single malt, and stuff like that...There wasn't any special [instructions regarding diet]. We like good food, and we eat a good, balanced diet. I like seafood, and I love fish, and I like the odd steak. I try to stay off butter. I'm taking Becel® just now, which I don't really like, but I try to stay off the butter and cooking with all the white sauce, and butter sauce, and stuff like that. (P10) I come here every 4 or 5 weeks to have the bloodwork done for Coumadin. Whenever I have this done, the nurse calls me that afternoon and says, "Stay on with the same milligrams" or "Change to that and that." But I feel fine [with this routine]... The only disadvantage of the Coumadin is the bruising and bleeding on just the slightest touch... but if that's the worst that happens, I'm not worrying about it. (P11) I'm extremely careful with my alcohol intake, although as I said before, I'm not an everyday drinker. Other than that, the only other thing is I started noticing I have experienced some hair loss. (P8) C. Major impact Three years ago, I had two very serious stomach bleeds and I do not know, to this day, whether I should attribute it to Coumadin. Once I spent a couple of days in intensive care and then three months later, again a couple more days, this time in critical care. (P11) It isn't worth it to risk a stroke by going off the Coumadin to have the hernia fixed. So Coumadin has played a major part in my life, because this hernia is a daily fact I have to live with... The fact that I'm taking Coumadin means that if I want to be operated on, I have to be careful... They [the Hernia Clinic] don't take guys like me that require a bit of time and skill and more facilities than they have. But what do guys like me do? (P14) The thing is, the last 558 times I've taken it, which is right here [referring to the records he keeps], I went through this last night, and I found only three miscues the entire time I've been taking it. That works out to 0.005 percent. It's a very, very low percentage of goofing taking it. I've never forgotten. For at least two of these incidents, I took it at 10:00 or 10:45, instead of at 6:00. That's four hours late. I consider that a goof. Another time I took it in the morning instead of at night, which is a goof. (P14) Patient satisfaction The vast majority of interviewees reported a high level of satisfaction with the care they receive from the nurses and physicians in the clinic (Table 5A). Most participants were also satisfied with the warfarin regime itself (Table 5B). Only a very small number of participants expressed significant dissatisfaction. The sources of dissatisfaction, which tended to be highly localized to specific concerns, included the cost and inconvenience of attending the clinic for regular INR tests, a lack of information provided to patients, and insufficient awareness of patient history on the part of clinic staff (Table 5C). Table 5 Quotations: Patient satisfaction A. Satisfaction with clinic staff Oh, I am more than pleased. I'm absolutely more than pleased. I think they're wonderful. The nurses are wonderful – you know, taking my blood, and phoning me, and giving me instructions. (P1) I think they've been 100 percent. From my cardiologist to the family physician and to the pharmacists, because they're just amazing. (P10) My doctor thought my blood was, I guess, too thick. They did an INR and recommended the Coumadin, which I didn't want to get on, because I knew it was warfarin and you associate that with rat poisoning. Anyway, she took the time and very patiently explained what the purpose of it was, and highly recommended it. I really like her. I like everybody there. They're very caring, supportive people. They're just dear. (P4) B. Satisfaction with warfarin regime This is a pill that keeps your blood thin, and you have to check it out [INR level]. I just do as I'm told and I'm thrilled that they keep me at 2-point-something....I go every week, or every other week, or once a month, depending on my stability. It doesn't bother me going. (P1) It's worked out well [the regime]. I know it has to be done, and I'm lucky in the fact that it has regulated it. It has totally regulated itself – I'm taking 4 mg a day now. I'm only coming in once a month. (P18) Oh, yes [happy with warfarin regime]. They let me know what the status is each week, whether it's going to level out, and whether I'm going to be able to stay on the same dosage and then stop going up there every week. I started going every week, and now it's been levelled to every two weeks. (P7) I really couldn't say anything bad about it [warfarin regime]. Apparently I've been outstanding in how steady I would go with it, and I've been going – normally, for years, I've been going once a month, pretty well. A couple of times it would go up and I'd come back in two weeks, or something. (P2) C. Sources of dissatisfaction Nobody tells me anything. That's one of my problems with this whole bloody business. Nobody tells me how I'm doing. All I know is that I'm supposed to be between 2 and 3 [INR levels]. (P7) I just more or less come when I'm ordered to. From home it's almost an hour on the bus each way, and the parking around here, the cost is wild. They must be financing the place with the parking. No, I would prefer not to come at all. I would prefer to forget the whole deal, but that doesn't seem to be in the offing at the moment. (P12) I haven't been coming here that long, about two years I think... but I wouldn't say they're fully aware of my history and really understand the depth of it... Considering my history, I think they should know more. They certainly don't have my files. (P13) Discussion The findings of this study provide significant and original insight into the perception and experience of patients taking warfarin. The data indicate that patients tend to have minimal input into the decision to initiate warfarin therapy; many have only a superficial level of understanding of the risks and benefits of warfarin; and the majority retain little from the education they received regarding warfarin therapy. This outcome is balanced, however, by the finding that for these patients there was both a high level of satisfaction with the care provided in the family practice setting and a low level of impact on their day-to-day lives. The principal strength of this study is the insight into the lived experience of warfarin therapy as gleaned from the unique perspective of family practice patients currently taking warfarin. We view this as a significant and novel contribution to the literature as we could find no other such study. It is important to note, however, that our sample was drawn from the patient population of an academic primary care practice that is both well-educated and of medium-high socioeconomic status. The applicability of these findings in other patient populations may therefore be limited. Interviewees revealed clear detachment from participation in the decision-making process around initiating warfarin therapy. In some cases, this detachment appeared to stem from the particular circumstances at the time; for instance, if the patient was involved in a medical emergency or was admitted to hospital and had several medications initiated. For others, there was a general belief or understanding that warfarin is a medication without which the patient faced imminent risk of death – it is therefore not a matter to be discussed or negotiated. This finding may be a function of the age of our participants. As a group, elderly patients tend to prefer a directed rather than shared consultation. Prior research indicates that seniors are more likely to be accepting of medical advice without much questioning, rather than assuming a more active role in the decision-making process [13]. This attitude was reflected in participants' comments that "doctor know best" and "it's the doctor's decision." Patient knowledge of risks, benefits, and issues related to diet and alcohol intake was low, although younger patients demonstrated greater levels of understanding than did those over age 75. This finding is consistent with previous investigations. Lip and colleagues have detected lower levels of knowledge among elderly patients; moreover, longer duration of anticoagulation does not appear to ameliorate patient understanding significantly [14,15]. For the most part, we found that retention of instructions pertaining to the warfarin regime was poor. Many participants reported that they simply follow the nurses' directions and have little interest in learning anything more. The limited knowledge and seemingly low level of interest to learn more could be attributable to the great deal of trust invested in the expertise of the clinic staff as discussed above. The fact that several spouses exhibited greater understanding of the risks and benefits associated with warfarin therapy has implications for educational interventions recognizing the importance of the spousal or care giver role in the monitoring of therapy. With regard to the impact of warfarin therapy on daily life, our results indicate that warfarin is for the most part well tolerated and does not pose heavy additional burdens or lifestyle changes. The majority of participants were already taking several medications and visiting more than one doctor on a regular basis. This sample also had a low incidence of complications and previous studies have shown that the potential for complication does not on its own result in a significant impact [16,17]. That is, the mere possibility of an adverse side-effect does not bring about substantial anxiety unless the complication is actually experienced. These results do not, however, capture the experiences of individuals who have tried and ceased taking warfarin for whatever reasons. This population represents a high priority for future study. Additional support may be required for individuals with multiple medical problems. Continuity of care and a strong relationship and identification with the primary care team that provides anticoagulation services can overcome potential miscommunication and misunderstanding regarding side effects and drug interaction. The importance of the association between patient satisfaction and adherence has been established in prior research on anticoagulation. In a case-control study, Arnsten and colleagues [18] found that, among patients with a regular physician, the non-adherent cases were those who expressed dissatisfaction. In our sample, the level of patient satisfaction was high, both with the clinic staff and the warfarin regime itself. Based on participants' testimonies, the coordination and continuity of care by a trustworthy team of doctors and nurses were key contributing factors to the high satisfaction ratings. In an evaluation of a telephone-based anticoagulation service, Waterman found that patient satisfaction with warfarin management was associated with the timeliness of receiving blood test results from the service provider [19]. The high level of patient satisfaction observed in the present study may also be due in part to the low rate of complications (e.g., hemorrhage, drug interactions), which may serve to reinforce patients' trust both in the therapy and in the health care team. Increasingly, theoretical models of the physician-patient encounter advocate the inclusion of patients in the decision-making process [20]. Of course, shared decision-making presupposes an understanding of the benefits and risks on the part of patients. With regard to warfarin therapy, patient preferences would be expected to vary according to expected benefits or awareness of risks of suffering a stroke. Man-Son-Hing et al have demonstrated that the minimal clinically important difference of warfarin therapy is often considerably smaller for patients than that identified by clinicians [21]. Protheroe and colleagues, in an observational study of patient-based decision analysis, noted marked disagreement between patient preferences and guideline recommendations [22]. A patient decision aid was shown to improve knowledge and understanding of the risks and benefits of warfarin for patients with atrial fibrillation, and aided in therapeutic choice [23]. Given the low level of patient knowledge observed in the present study and elsewhere, the vision of shared decision-making [24] remains an as yet unachieved, but laudable goal; indeed, the present results highlight the challenges of shared decision-making and increased autonomy in patients with complex chronic diseases. Conclusions In summary, the results of this study suggest that patients tend to have limited input into the decision to initiate warfarin therapy. Moreover, a majority appear to lack a comprehensive understanding of the risks and benefits associated with treatment. These findings, however, were balanced by the minimal impact of warfarin on daily life and the high level of patient satisfaction. Further research is required to assess whether these findings are similar in other patient groups, with different demographic and socioeconomic characteristics, including multi-cultural communities [14]. Investigation of physician views of the underutilization of warfarin therapy would allow for a comparison of the patient and provider perspectives. Clearly, there is a pressing need for innovative methods of continuing patient education in order to communicate the risks and benefits of warfarin therapy in a friendly, non-threatening manner. Also, these results highlight the tremendous influence that care providers exert on the decision-making of patients. The development of decision aids for anticoagulation may help patients make more informed decisions [23,25], but only if care providers know of their existence and take the time to use them, assuming that such tools are feasible in a busy clinical setting. Competing interests None declared. Author's contributions REGU conceived and initiated the study and will act as guarantor. GCD, JM, and BT conducted the interviews. CST co-ordinated the data analysis process. All authors participated in the analysis of the data and the writing of successive drafts of the manuscript and all have read and approved the final draft. Pre-publication history The pre-publication history for this paper can be accessed here: Acknowledgements We are indebted to our three peer reviewers - Drs. Malcom Man-Son-Hing, Maggie Somerset, and David Armstrong- for their comments and suggestions on an earlier draft of this paper. This study was funded by research grants from Physicians' Services Foundation Incorporated and Samcor/Sunnybrook Primary Care Research Trust. Dr. Upshur is supported by a New Investigator Award from the Canadian Institutes of Health Research and a Research Scholar Award from the Department of Family and Community Medicine, University of Toronto. The authors would like to thank the 21 patients who volunteered to take part in this study and share their experiences with us. We would like to acknowledge the contribution of the nurses in the Family Practice Unit who referred the participants, and that of Dr. Denise Gastaldo who acted as an independent external reader. Special thanks also to Jennie Jones for transcribing the interviews and to Shari Gruman for formatting the paper. ==== Refs Go A Hylek E Phillips K Chang Y Henault L Selby J Prevalence of diagnosed atrial fibrillation in adults: national implications for rhythm management and stroke prevention: the AnTicoagulation and Risk factors In Atrial fibrillation (ATRIA) Study JAMA 2001 285 2370 2375 11343485 10.1001/jama.285.18.2370 Petersen P Boysen G Godfredsen J Andersen E Andersen B Placebo-controlled, randomised trial of warfarin and aspirin for prevention of thromboembolic complications in chronic atrial fibrillation: the Copenhagen AFASAK Study Lancet 1989 177 175 179 2563096 10.1016/S0140-6736(89)91200-2 EAFL (European Atrial Fibrillation Trials Study Group) Secondary prevention in non-rheumatic atrial fibrillation after transient ischaemic attack or minor stroke Lancet 1993 342 1255 1262 7901582 Hirsh J Dalen J Guyatt G The sixth (2000) ACCP guidelines for antithrombotic therapy for prevention and treatment of thrombosis. American College of Chest Physicians Chest 2001 119 1S 2S 11157638 10.1378/chest.119.1_suppl.1S Ridker P Goldhaber S Danielson E Rosenberg Y Eby C Deitcher S Cushman M Moll S Kessler C Elliott C Paulson R Wong T Bauer K Schwartz B Miletich J Bounameaux H Glynn R PREVENT investigators Long-term, low-intensity warfarin therapy for the prevention of recurrent venous thromboembolism N Engl J Med 2003 348 1425 1434 12601075 10.1056/NEJMoa035029 Bungard T Ghali W McAlister F Buchan A Cave A Hamilton P Mitchell L Shuaib A Teo K Tsuyuki R The relative importance of barriers to the prescription of warfarin for nonvalvular atrial fibrillation Can J Cardiol 2003 19 280 284 12677283 Bungard T Ghali W Teo K McAlister F Tsuyuki R Why do patients with atrial fibrillation not receive warfarin? Arch Int Med 2000 160 41 46 10632303 10.1001/archinte.160.1.41 Hart R Anticoagulation therapy for patients with atrial fibrillation CMAJ 2000 163 956 957 11068566 Devereaux P Anderson D Gardner M Putnam W Flowerdew G Brownell B Nagpal S Cox J Differences between perspectives of physicians and patients on anticoagulation in patients with atrial fibrillation: observational study BMJ 2001 323 1218 1222 11719412 10.1136/bmj.323.7323.1218 Howitt A Armstrong D Implementing evidence based medicine in general practice: audit and qualitative study of antithrombotic treatment for atrial fibrillation BMJ 1999 318 1324 1327 10323820 Ceresne L Upshur R Atrial fibrillation in a primary care practice: prevalence and management BMC Family Pract 2002 3 11 10.1186/1471-2296-3-11 Denzin N Lincoln Y eds Handbook of Qualitative Research 2000 Thousand Oaks, CA: Sage McKinstry B Do patients wish to be involved in decision making in the consultation? A cross sectional survey with video vignettes BMJ 2000 321 867 871 11021866 10.1136/bmj.321.7265.867 Lip GY Kamath S Jafri M Mohammed A Bareford D Ethnic differences in patient perceptions of atrial fibrillation and anticoagulation therapy: The West Birmingham atrial fibrillation project Stroke 2002 33 238 244 11779916 10.1161/hs0102.101817 Nadar S Begum N Kaur B Sandhu S Lip G Patients' understanding of anticoagulant therapy in a multiethnic population J R Soc Med 2003 96 175 179 12668704 10.1258/jrsm.96.4.175 Lancaster T Singer D Sheehan M Oertel L Maraventano S Hughes R Kistler J The impact of along-term warfarin therapy on quality of life. Evidence from a randomized trial. Boston Area Anticoagulation Trial for Atrial Fibrillation Investigators Arch Intern Med 1991 151 1944 1949 1929681 10.1001/archinte.151.10.1944 Sweeney K Gray D Steele R Evans P Use of warfarin in non-rheumatic atrial fibrillation: a commentary from general practice Br J Gen Pract 1995 45 153 158 7772394 Arnsten J Gelfand J Singer D Determinants of compliance with anticoagulation: a case-control study Am J Med 1997 103 11 17 9236480 Waterman A Banet G Milligan P Frazier A Verzino E Walton B Gage B Patient and physician satisfaction with a telephone-based anticoagulation service J Gen Intern Med 2001 16 460 563 11520383 10.1046/j.1525-1497.2001.016007460.x Gafni A Charles C Whelan T The physician-patient encounter: the physician as a perfect agent for the patient versus the informed treatment decision-making model Soc Sci Med 1998 47 347 354 9681904 10.1016/S0277-9536(98)00091-4 Man-Son-Hing M Laupacis A O'Connor A Wells G Lemelin J Wood W Dermer M Warfarin for atrial fibrillation: the patient's perspective Arch Intern Med 1996 156 1841 1848 8790079 10.1001/archinte.156.16.1841 Protheroe J Fahey T Montgomery A Peters T The impact of patients' preferences on the treatment of atrial fibrillation: observational study of patient based decision analysis BMJ 2000 320 1380 1384 10818030 10.1136/bmj.320.7246.1380 Man-Son-Hing M Laupacis A O'Connor AM Biggs J Brake E Yetesir E Hart RG A patient decision aid regarding antithrombotic therapy for stroke prevention in atrial fibrillation: a randomized controlled trial JAMA 1999 282 737 743 10463708 10.1001/jama.282.8.737 Elwyn G Edwards A Kinnersley P Shared decision making in primary care: the neglected second half of the consultation Br J Gen Pract 1999 49 477 482 10562751 Thomson R Parkin D Eccles M Sudlow M Robinson A Decision analysis and guidelines for anticoagulant therapy to prevent stroke in patients with atrial fibrillation Lancet 2000 355 956 962 10768433 10.1016/S0140-6736(00)90012-6

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==== Front BMC GeriatrBMC Geriatrics1471-2318BioMed Central London 1471-2318-4-71528578310.1186/1471-2318-4-7Study ProtocolChronic pain self-management for older adults: a randomized controlled trial [ISRCTN11899548] Ersek Mary 12mary.ersek@swedish.orgTurner Judith A 3jturner@u.washington.eduCain Kevin C 45cain@u.washington.eduKemp Carol A 1carola.kemp@swedish.org1 Pain Research Department, Swedish Medical Center, 550 16th Ave, Providence Professional Building Suite 405, Seattle, WA 98122-5699, USA2 Department of Biobehavioral Nursing and Health Systems, University of Washington School of Nursing, Box 357266, Seattle, WA 98195-1406, USA3 Department of Psychiatry and Behavioral Sciences and Department of Rehabilitation Medicine, University of Washington School of Medicine, Box 356560, Seattle, WA 98195-6560, USA4 Office for Nursing Research, University of Washington School of Nursing, Box 357265, Seattle, WA 98195-7265, USA5 Department of Biostatistics, University of Washington School of Public Health and Community Medicine, Box 357232, Seattle, WA 98195-7232, USA2004 30 7 2004 4 7 7 25 6 2004 30 7 2004 Copyright © 2004 Ersek et al; licensee BioMed Central Ltd.2004Ersek et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background Chronic pain is a common and frequently disabling problem in older adults. Clinical guidelines emphasize the need to use multimodal therapies to manage persistent pain in this population. Pain self-management training is a multimodal therapy that has been found to be effective in young to middle-aged adult samples. This training includes education about pain as well as instruction and practice in several management techniques, including relaxation, physical exercise, modification of negative thoughts, and goal setting. Few studies have examined the effectiveness of this therapy in older adult samples. Methods/Design This is a randomized, controlled trial to assess the effectiveness of a pain self-management training group intervention, as compared with an education-only control condition. Participants are recruited from retirement communities in the Pacific Northwest of the United States and must be 65 years or older and experience persistent, noncancer pain that limits their activities. The primary outcome is physical disability, as measured by the Roland-Morris Disability Questionnaire. Secondary outcomes are depression (Geriatric Depression Scale), pain intensity (Brief Pain Inventory), and pain-related interference with activities (Brief Pain Inventory). Randomization occurs by facility to minimize cross-contamination between groups. The target sample size is 273 enrolled, which assuming a 20% attrition rate at 12 months, will provide us with 84% power to detect a moderate effect size of .50 for the primary outcome. Discussion Few studies have investigated the effects of multimodal pain self-management training among older adults. This randomized controlled trial is designed to assess the efficacy of a pain self-management program that incorporates physical and psychosocial pain coping skills among adults in the mid-old to old-old range. ==== Body Background The problem of chronic pain in the elderly Chronic pain is a common problem in the elderly, and is often associated with significant physical disability and psychosocial problems [1]. Estimates of the prevalence of chronic pain problems among community-dwelling older adults range from 58–70% [1]. The most common painful conditions among older adults are musculoskeletal conditions such as osteoarthritis, low back pain, and previous fracture sites [2]. Chronic pain often results in depression, sleep disturbance, decreased mobility, increased health care utilization, and physical and social role dysfunction [1]. Despite its high prevalence, pain in the elderly often is inadequately assessed and treated [1]. As the United States population grows older, the public health problem of chronic pain and its sequelae will worsen. Projections show dramatic increases in this age group; approximately 25% of the population will be age 65 years or older in 2050. Moreover, by 2030 there will be an estimated 8 million people who are 85 years or older [3]. Thus, there is an urgent and growing need for interventions that are effective in decreasing pain, suffering, and pain-related disability in this group. The role of self-management in the treatment of chronic painful conditions There is substantial empirical evidence that attention to cognitive and behavioral factors, in addition to physiological factors, is necessary for the successful treatment of chronic nonmalignant pain [4,5]. Empirically supported multimodal therapies that incorporate cognitive and behavioral strategies now exist for many chronic pain conditions, including rheumatoid arthritis, osteoarthritis, fibromyalgia, and low back pain [6-10]. These therapies aim to enhance the ability of patients to successfully self-manage their pain, using a variety of techniques. Related approaches and strategies are described under the rubrics "cognitive-behavioral therapy" (CBT), "psycho-educational" or "educational," and "self-management" or "self-help." Although there are variations among these approaches, they share some or all of the following components: education about pain, instruction in the identification and modification of negative thoughts, exercise, communication skills, relaxation training, and physical therapies. The goal of the therapies is to enhance function, improve mood, and decrease pain intensity by changing the emotional, cognitive, and behavioral responses to pain. Despite their documented efficacy in young to middle-aged samples [9-12], cognitive-behavioral and self-management pain therapies have been little-studied in elderly populations. In one of the first examinations of CBT for elderly patients with pain, 69 outpatients with chronic pain were randomly assigned either to immediate treatment or delayed (wait list) treatment [13]. Approximately half of the sample was over 60 years of age, and age was unrelated to outcome. The intervention resulted in significant decreases in pain interference with daily activities and increases in participants' self-reported ability to cope with pain. Limitations of this study included the fairly small sample size and the lack of intent-to-treat analysis. Keefe and colleagues [14] evaluated the efficacy of a pain coping skills training (CST) intervention as compared with arthritis education and standard care in decreasing pain and physical and psychological disability among 99 middle-aged to older outpatients with osteoarthritic knee pain. The CST consisted of 10 weekly group sessions focusing on identifying and reducing irrational thoughts, diverting attention away from the pain, and changing activity patterns to manage pain. The CST group showed significantly less pain and psychological disability following treatment as compared with the other two groups. At 6-month follow-up, the CST group showed significantly less physical and psychological disability as compared with the education group and marginally less psychological disability as compared with the standard care group [15]. Although this study provides evidence for the benefits of cognitive-behavioral therapy for older adults, it focused on arthritis patients and not older adults per se. Moreover, the average subject age was 64 years. It is not clear whether these findings would generalize to mid-old (i.e., 75–85 years) and old-old (85 years and older) adults. These groups have been shown to differ from their younger counterparts (i.e., those 65–74 years) in several dimensions, including pain prevalence, physical and cognitive function, involvement in recreational and social activities, and social support [16-19], that potentially could affect the pain experience and response to pain therapies. One study that examined a cognitive-behavioral therapy in old-old adults (mean age 77.2 years) evaluated the efficacy of a 10-week CBT intervention (n = 11) versus an attention/support (AS) condition (n = 10) for nursing home residents [20]. The CBT condition incorporated pain education, progressive relaxation, imagery, coping skills training, cognitive restructuring, and attention diversion. CBT participants reported significantly less pain and pain-related disability following the intervention, as compared to the AS group. These significant differences were maintained at the 4-month follow-up. This study provides important evidence that CBT can be successfully applied to old-old adults; however, the results need to be replicated in other, larger samples, including non-institutionalized elderly. Retirement communities as a study setting As the U.S. population continues to age, retirement communities have gained popularity. A retirement community allows older adults with varying lifestyles and physical abilities to live in an environment that encourages independence while providing needed access to health and social resources [21]. Although most residents of these communities live independently (some facilities also include assisted living apartments and skilled nursing facilities), the retirement community, on average, represents a mid-old to old-old population that is vulnerable to physical disability, health problems, and social isolation [22]. The growing population in retirement communities, then, is one in which self-management group therapies for chronic pain may hold great promise. Adoption of regular wellness-oriented pain management strategies may contribute to enhanced functioning and prolonged independence. Study purpose and specific aims The primary goal of this study is to evaluate the efficacy of a pain self-management group intervention (SMG), as compared with a control condition (BOOK), in decreasing physical disability, pain, pain-related interference with activities, and depression in older retirement community residents with chronic pain. In addition, we wish to determine the extent to which SMG participation is associated with changes in specific pain-related beliefs and coping strategies, and the extent to which changes in these process variables are associated with changes in outcomes (physical disability, pain intensity, pain-related interference with activities, and depression). We plan to test the following hypotheses: 1. At post-treatment and each follow-up, participants assigned to SMG, as compared with participants assigned to BOOK, will report less physical disability (primary outcome), and lower pain intensity, pain-related interference with activities, and depressive symptom severity (secondary outcomes). 2. Participants assigned to SMG, as compared with participants assigned to BOOK, will show greater pre- to post-treatment increases in self-efficacy and use of adaptive pain coping strategies and greater decreases in catastrophizing. Significant differences between SMG and BOOK groups in pain-related beliefs and coping strategies will be maintained at 6-month and 1-year follow-ups. 3. Pre- to post-treatment changes in specific pain-related beliefs (catastrophizing, self-efficacy) and coping strategies (Chronic Pain Coping Inventory subscales) will be associated significantly with changes in physical and social functioning, pain intensity, and depression over the same period among SMG participants. These changes in beliefs and coping strategies will be maintained at 6-month and 1-year follow-ups. Figure 1 depicts the hypothesized relationships among study variables. Figure 1 Hypothesized relationships among study variables Methods/Design Design This is a currently ongoing randomized controlled trial. The study procedures and measures have been approved by the Swedish Medical Center institutional review board. Figure 2 outlines study procedures and follow-up. Figure 2 Study flowchart Participants Participants (targeted enrollment n = 273) are recruited from residents living in one of the 34 participating retirement communities in Seattle, Washington and the surrounding area. Study inclusion criteria are: (1) 65 years of age or older, (2) pain > 3 months duration that interferes with regular activities; and (3) ability to read and complete study questionnaires in English. Exclusion criteria are: (1) current, active cancer and (2) surgery within the past 6 months or surgery planned in the next 6 months. Recruitment and randomization procedures Participants are recruited using newsletter announcements, flyers, brochures, and informational talks given at each facility. Retirement community residents who are interested in the study are screened to assess eligibility. Eligible residents who provide written informed consent are then asked to complete the baseline measures and to provide the name of their primary care provider (PCP), as well as permission to contact the PCP. PCPs of SMG group participants are sent a letter about the study and asked to contact the research nurse if there is any medical reason to restrict the resident's participation in the exercise portion of the study. After all participants from a facility have completed the baseline questionnaires, the facility is randomized to receive either the BOOK or the SMG. Randomization is done by facility, rather than by individual participant, for several reasons. First, it expands the number of participating facilities by making feasible recruitment from smaller facilities. If approximately 5% of residents were recruited from any one facility, then it would not be scientifically or financially sound to involve facilities with fewer than 200 residents in independent or assisted living. A pilot study indicated that the ideal self-management group size is 5–12 participants. If we randomized within facilities, at least 10 participants would need to be recruited from each facility to allow 5 SMG participants. However, if all participants within a facility are randomized to the same condition, then smaller facilities can participate. If more than 12 residents in a facility randomized to the SMG condition enroll in the study, more than one group is scheduled. A second advantage of randomization by facility is that there is little risk of participants in one condition talking with participants randomized to another condition about their experiences in the study. Thus, there is less treatment contamination and likelihood that participants from different conditions will compare treatments, a situation that can provoke dissatisfaction among participants who do not receive the treatment of their choice. Pain self-management group (SMG) The SMG intervention, which consists of seven weekly 90-minute group sessions, includes the major components of empirically-supported self-management interventions [23,24], refined for use with the elderly (see Table 1). For example, we include a discussion of myths about pain in older adults (e.g., pain is an inevitable part of aging) and focus on exercises that are effective and safe for older adults with musculoskeletal pain. The intervention is designed to decrease participants' physical disability and pain intensity; increase participation in home, social, and recreational activities; and enhance participants' self-efficacy for managing chronic pain. To accomplish these objectives, the intervention provides basic information about pain management, teaches problem-solving and relaxation skills, and provides practice with a variety of pain management techniques. Participants receive a class syllabus, relaxation tape, Theraband® tubing for the performance of selected exercises, and two hot/cold gel packs. Table 1 Summary of the self-management group intervention SESSION NUMBER: TOPICS MAJOR CONTENT AND ACTIVITIES Session 1: Introduction; Basic principles of pain Review purpose of the program/study. Review definition, types, & mechanisms of pain. Discuss myths about pain in older adults. Emphasize goals of chronic pain management. Discuss signs/symptoms that require medical attention. Introduce problem-solving techniques for pain management. Session 2: Role of exercise & physical activity in pain management Discuss exercise in pain management: problem of de-conditioning, types of exercise, tips for starting exercise program. Demonstrate & practice specific exercises. Introduce relaxation and breathing techniques as effective pain management strategies. Practice progressive muscle relaxation & abdominal breathing. Session 3: Engaging in pleasant, meaningful activities; pacing activities Discuss ways in which chronic pain may be limiting participation in enjoyable or meaningful activities Use problem solving to develop individualized plans for increasing these activities. Discuss strategies for activity pacing and rationale for avoiding guarding and inactivity. Practice relaxation. Session 4: Challenging negative thoughts; Dealing with pain flare-ups and setbacks Discuss critical role of thoughts and appraisals about pain in determining affective and behavioral responses to pain. Help participants to identify negative thoughts that they may have in response to pain. Practice challenging negative thoughts with positive thoughts about effective ways to manage pain. Discuss strategies for dealing with setbacks and pain-flare-ups. Practice relaxation. Session 5: Non-drug pain therapies; Heat & cold; Dealing with pain flare-ups and setbacks (continued) Describe rationale for using nondrug pain therapies. Describe and practice application of heat and cold; review precautions in using heat and cold for pain Continue discussion about coping with pain flare-ups & setbacks in pain management. Practice relaxation. Session 6: Pain medications & complementary therapies Describe the role of medications for pain management. Discuss the major types of pain medications. Describe the use of complementary therapies in pain management. Discuss steps in making informed decisions about all pain therapies. Session 7: Pain management plan; Wrap-up Discuss maintenance of gains made through the program. Review coping with set backs & pain flare-ups. Revise written individualized maintenance plans for each participant. A key component of this self-management group is the development of personalized pain management plans. Participants begin developing a plan during the first class and revise it each week as they learn and practice additional pain management skills. With the assistance of the facilitator and, at times, other group members, participants review pain control strategies that they have learned and practiced and choose one or several strategies that best meet their individual needs and interests. Participants identify specifically what they will do (in measurable terms) and define the parameters (e.g., how many times per week, how far they will walk, how many repetitions of each exercise they will do). Although each person develops his or her own plan, the plans incorporate the same repertoire of activities that are taught in the class. These plans are monitored weekly during the classes and during follow-up phone calls (described below). Educational book control condition (BOOK) Participants who are assigned to the BOOK condition receive a copy of The Chronic Pain Workbook, 2ndEdition [25]. Facilitators telephone participants 1 and 4 weeks after participants receive the workbook. The BOOK condition was designed to control for attention and information. In these calls, facilitators inquire about participants' current pain and functioning, and ask about use of pain therapies and self-management techniques. There is no specific therapeutic component in the phone calls and facilitators do not help BOOK participants identify goals or develop a pain management plan. Booster and follow-up phone calls The SMG group facilitator telephones each participant at 12, 16, 22, and 30 weeks after the final group session. During the booster phone calls, facilitators inquire about pain and functioning, current pain management plans, and successes and obstacles in meeting pain management goals, as well as provide encouragement and assistance in problem-solving obstacles encountered in pain management. BOOK participants receive follow-up phone calls at the same intervals to control for attention. Steps taken to ensure and monitor group facilitator adherence Group facilitators are nurses and psychologists with expertise in geriatrics and/or pain management and experience in facilitating therapeutic groups. All are specifically trained according to the treatment protocol. We monitor group facilitator adherence to the self-management group protocol, as recommended by Waltz et al. [26]. All facilitators receive and review a facilitator's syllabus that contains a detailed protocol describing the goals, contents, and activities for each of the 7 sessions. Group facilitators have met 3 times to discuss protocol and treatment integrity issues. Finally, each session for each treatment group is audiotaped. Twenty percent of the audiotapes are randomly chosen and reviewed by a trained research nurse who is not involved in any other aspects of the study. The research nurse listens to the tapes and evaluates the degree to which the group sessions are conducted according to the protocol using a checklist developed for this purpose. Measures Study measures were chosen based on psychometric properties, including sensitivity to change; brevity; and appropriateness for use with community-dwelling, older adults with chronic pain. They are described below and summarized in Table 2. Table 2 Measures and assessment times CONSTRUCT/MEASURE SCREENING/BASELINE POST-INTERVENTION 6-MONTH FOLLOW-UP 12-MONTH FOLLOW-UP Physical Functioning √ √ √ √ Roland-Morris Disability Questionnaire Brief Pain Inventory (BPI) – pain interference subscale Pain Intensity √ √ √ √ Brief Pain Inventory – pain intensity subscale Mood Disturbance/ Social functioning √ √ √ Geriatric Depression Scale Pain Beliefs and Coping √ √ √ Chronic Pain Coping Inventory – (includes pain medication use) Coping Strategies Questionnaire – catastrophizing, praying/hoping subscales Self-efficacy Scale Pain Knowledge √ √ Demographics, Medical Conditions, Medications √ Screening & Intake Questionnaire Adapted Charlson Index Cognitive Functioning √ Folstein Mini-Mental State Examination Pretreatment Expectations √ Adherence to Treatment √ √ Attendance at classes Completion of reading assignments Attainment of goals (Personal Pain Management Plan) Descriptive measures The following measures are administered at baseline to describe the sample and to explore whether these variables are associated with treatment response. We will compare the two study groups on these measures to determine whether they are comparable at baseline. Screening and intake interview schedule – demographic information and pain history During the screening process and baseline assessment, participants are asked a series of questions to elicit demographic and pain history variables, including age, race, ethnicity, gender, marital status, education level, sites and duration of pain, and prior and current pain treatments. Folstein mini-mental state examination (MMSE) [27] The MMSE is a measure that is widely used to assess cognitive function, particularly in older adults. It consists of 30 items, and requires 5–10 minutes to administer. Items assess orientation, memory, attention, and calculation. The MMSE has been demonstrated to be valid and to have good test-retest reliability [28]. Charlson index of comorbidity (CI) The CI is an extensively used, valid, and reliable measure of comorbid medical conditions [29]. The CI uses 19 categories of comorbidity; each category is weighted and scored according to an algorithm [29]. Higher scores indicate greater health burden from comorbid causes. In this study, we are using a self-report version of the CI demonstrated to be reliable and valid in a group of older adults [30]. Because comorbid conditions may be associated with pain appraisal, coping, and outcomes [31], we will examine the association between comorbid conditions and response to therapy. Process measures Self-efficacy scale (SES) Participants complete the 8-item version of Lorig et al.'s Self- Efficacy Scale [32], which assesses confidence in ability to manage pain and associated problems such as fatigue and negative mood [33,34]. Previous studies have supported the reliability and validity of this measure [32,34,35]. The SES has been tested and used in studies of older adults [36]. Coping strategies questionnaire (CSQ) [37] The CSQ is one of the most widely used measures of pain coping and catastrophizing [38,39]. Measures derived from the CSQ have been shown to be associated with various measures of functioning among patients with different pain conditions [38,40-43]. The CSQ has demonstrated reliability and validity in several samples of older adults, including those who are older than 75 years [44]. For this study, only the catastrophizing and praying/hoping subscales are used. Catastrophizing is included because prior studies have shown that this variable is associated with pain intensity, depression, and disability [45]. The praying/hoping subscale was included because this coping strategy has been found to be associated with the pain experience of older persons[46]. Chronic pain coping inventory (CPCI) The CPCI measures cognitive and behavioral coping strategies used by people to manage chronic pain. It contains 9 subscales: guarding, resting, asking for assistance, relaxation, task persistence, exercise/stretch, seeking support, coping self-statements, and medication use [47]. The CPCI scales have been shown to have acceptable internal consistency and test-retest reliability, and to be associated significantly with physical disability and depression [47-49]. Additional development and psychometric testing have supported the reliability and validity of an additional activity pacing subscale [49]. Pretreatment expectations Prior to learning the study condition to which they are randomized, participants are asked the degree to which they believe that each study condition will be helpful to them. They respond using a 0 to 10 scale, with 0 indicating "not helpful at all" and 10 indicating "extremely helpful." Treatment adherence 1. Class attendance. Group leaders document weekly class attendance. Total attendance is assessed as a percentage of classes the participant attended (out of 7). 2. Reading log/usefulness. Both BOOK and SMG participants complete a form in which they report the amount read on each topic using a 0–5 scale ("I did not look at the section at all" to "I read the section thoroughly"). They also rate the usefulness of each section using a 0–5 scale ("Not at all useful" to "Very useful"). 3. Goal attainment. Attainment of SMG participants' pain management goals is assessed using the Personal Pain Management Plan (PPMP). Each week, participants in the SMG group are asked to document the type and frequency of each activity they have chosen to utilize in the management of their chronic pain. They monitor and document the pain management activities that they actually performed over the week. Participants also document obstacles that they have encountered in trying to meet their goals and the solutions they have identified to overcome those obstacles. This form is printed on 2-page paper. The top copy is turned in each week and participants keep the bottom copy for their own records. The PPMP serves several purposes: 1) to assist participants to identify and follow through on their personalized goals; 2) to assess treatment adherence; and 3) to cross-validate data that are collected using the Chronic Pain Coping Inventory. Outcome measures Primary outcome Roland-Morris disability questionnaire (RMDQ): The RMDQ [50] is widely used to assess physical disability associated with low back pain. The RMDQ has been demonstrated to be valid, reliable, and responsive to change [50-55]. Although developed as a measure of physical disability related to back pain, the RMDQ, re-worded without reference to the back, has been found to be a reliable and valid measure of physical disability for patients with other chronic pain problems as well [52]. The RMDQ is scored from 0–24, with higher scores indicating more severe physical disability. Physical disability, as measured by the RMDQ, is the primary study outcome. Secondary outcomes Brief pain inventory (BPI): The BPI is a widely-used, reliable, valid instrument that assesses pain history, location, intensity, and activity interference [56,57]. For this study, pain intensity is measured by calculating the mean of four items in which respondents are asked to rate their average, current, least, and worst pain during the past week, using a scale of 0 ("No pain") to 10 ("Pain as bad as you can imagine"). [58]. Pain-related interference is a composite measure of the degree to which pain limits a person's general function [57]. This variable is calculated as the mean of ratings of pain interference with general activity, mood, walking, work (including housework), relations with others, sleep, and enjoyment of life. Each item is rated on a scale of 0 ("Does not interfere") to 10 ("Completely interferes"). Geriatric depression scale (GDS): The GDS [59] is a 30-item self-report measure specifically designed to assess depressive symptoms in older persons. Scores of 11 or higher are considered indicative of depression in older adults. Good sensitivity and specificity for detecting depression in geriatric psychiatric and medical outpatients has been demonstrated (84–100% sensitivity; 73–96% specificity) [60,61]. The GDS was selected over other available depression measures because of its screening efficiency with geriatric outpatient populations, its focus on affective rather than physical symptoms, and its true/false scoring format, which studies have found to be simpler for older adults to complete [61]. Sample size calculations and statistical analyses Power analysis/sample size calculations A mixed effects model will be used to analyze data using the participant as the unit of analysis and controlling for baseline value of the outcome as a covariate. A reasonably accurate approximation to this analysis could be obtained by the following procedure: first compute change scores (pre to post) for each person, then collapse to get the mean change score within each site, then do t-tests on these means. This simpler model was used for power calculations, since it allows standard software to be used. The plan to randomize by site, rather than by individual participant, required additional considerations in calculating statistical power. With this group-randomized design, power depends on the correlation of people within sites, or the intra-class correlation. Effect size is defined as the mean change score of all individuals in the intervention group minus the mean change score of all individuals in the control group, divided by the standard deviation of change score within groups. Power calculations for the proposed study are based on estimates of 34 sites (17 intervention and 17 control), 6.4 participants per site (N = 218) providing data at 12 months (20% attrition rate). Table 3 shows how power (the probability of detecting a difference) varies with the correlation of individuals within site and the effect size. The second column of this table shows the "effective sample size," meaning that the study would have the same power as a study with this sample size and no clustering. If the correlation is zero, the effective sample size is 272, the actual sample size. A correlation of 1 would indicate that all individuals in each site have exactly the same outcome (i.e., no different from having one person per site), so the effective sample size would be 27. Analysis of data from a pilot study showed an intra-class correlation (ICC) of .07 [62]. Although this estimate should be interpreted cautiously because of the limited number of sites in the pilot study, it indicates that the intra-class correlation will probably be fairly small, perhaps 0.05 to 0.1. Our target sample size of 273 enrolled and 20% attrition at 12-month follow-up (yielding a final sample size of 218), assuming ICC=.1, will result in 84% power for detecting an effect size of .5, which Cohen [63] refers to as a "moderate" effect size. Table 3 Power for detecting a difference between the intervention and control group, depending on effect size and intra-class correlation (34 sites, average 6.4 subjects per site) Intra-class correlation Effective sample size Effect size (the difference in means between the two groups, divided by the within-group standard deviation) .40 .50 .60 .70 0.00 218 84% 96% 99% 100% 0.05 171 74% 90% 97% 100% 0.10 141 65% 84% 94% 98% 0.20 105 52% 71% 86% 94% 0.30 83 43% 61% 77% 88% 0.50 59 32% 46% 61% 75% 1.00 34 20% 29% 40% 51% Statistical analysis The test of hypothesis 1 compares the SMG and BOOK participants on the primary outcome (physical disability) and secondary outcomes (pain intensity, pain-related interference with activities, and depressive symptom severity) at each of the 3 follow-up assessments. The analytic method that we will use to evaluate this hypothesis is the mixed effects analysis of covariance (ANCOVA), as proposed by Laird and Ware [64] and implemented in the SAS PROC MIXED procedure [65,66]. This model will have two random effects, site and person nested within site. Group (i.e., treatment or control) and Time will be fixed effects. The repeated measurements of physical disability at post-intervention, 6 months, and 1 year will be the outcome measure. The baseline value of physical disability will be included in the model as a covariate. Any baseline variables that are correlated with the outcome variable and/or differ between the two treatment groups (e.g., gender, age, comorbidity) will also be included as covariates in the analysis. If the main effect for group is significant, contrasts within this model will be used to test for treatment effect separately at each of the three outcome times. Secondary analyses will be similar, fitting a mixed effects model that uses one of the secondary outcomes (e.g., pain intensity, pain-related interference, and depression) in place of physical disability. The analysis of Hypothesis 1 will be by intent-to-treat. Hypothesis 2 involves comparing the SMG and BOOK groups on changes in process variables (pain-related beliefs and coping strategies). A mixed effects model, as described under hypothesis 1, will be used for these analyses. As for hypothesis 1, baseline variables that are predictive of outcome and/or differ between groups will be included as covariates in the analyses for hypothesis 2. Hypothesis 3 involves the correlation of changes in beliefs and coping to changes in the outcome variables. For each assessment time, change from baseline will be computed and scatter plots will be used to describe relationships, with Pearson and/or Spearman correlation coefficients used to summarize the strength of the association. Although we hypothesize that significant associations in changes will occur only in the SMG group, we also will perform exploratory analyses in the BOOK group to assess for these associations. In addition to performing major analyses to test study hypotheses, we will also perform exploratory analyses to examine whether there are subgroups of participants in whom the intervention had a particularly strong or a particularly weak effect. For example, we will explore whether: (1) there is a difference in response to therapy based on age group (young-old, mid-old, old-old); (2) men respond differently to therapy than women; and (3) pain severity at baseline is related to strength of treatment effect. These analyses will be performed using the ANCOVA described above, augmented by adding, for example, an indicator for female gender and the interaction term between gender and treatment group. Discussion Persistent pain is a common problem in older adults that can be debilitating. Self-management strategies that incorporate physical and psychosocial pain coping skills are effective in decreasing pain and improving function and mood in younger adults. Little is known, however, about the efficacy of this therapy for older adults, especially those in the mid-old to old-old range. Our randomized controlled trial assesses the efficacy of such a treatment program, as compared with a control condition, in decreasing pain and improving physical and psychosocial functioning in elderly retirement community residents with chronic pain. Competing interests None declared. Authors' contributions ME and JAT developed the intervention and conducted the pilot test of the self-management groups. KCC developed the analysis plan, conducted the power calculations, and wrote the related sections of the paper. CAK assisted in refining the intervention. ME and JAT wrote the initial description of the intervention and this article. All authors read and approved the final manuscript. 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==== Front BMC Med GenetBMC Medical Genetics1471-2350BioMed Central London 1471-2350-5-191528799210.1186/1471-2350-5-19Research ArticleAre p.I148T, p.R74W and p.D1270N cystic fibrosis causing mutations ? Claustres Mireille 1Mireille.Claustres@igh.cnrs.frAltiéri Jean-Pierre 1Jean-Pierre.Altieri@igh.cnrs.frGuittard Caroline 1Caroline.Guittard@igh.cnrs.frTemplin Carine 1Carine.Templin@igh.cnrs.frChevalier-Porst Françoise 2francoise.chevalier-porst@chu-lyon.frGeorges Marie Des 1Marie.Desgeorges@igh.cnrs.fr1 Laboratoire de Génétique Moléculaire, Institut Universitaire de Recherche Clinique et Centre Hospitalier Universitaire, 641 avenue du Doyen Gaston Giraud, 34093 Montpellier, France2 Laboratoire de Biochimie pédiatrique, Centre Hospitalier Universitaire Paul-Brousse, 69000 Lyon, France2004 2 8 2004 5 19 19 16 4 2004 2 8 2004 Copyright © 2004 Claustres et al; licensee BioMed Central Ltd.2004Claustres et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background To contribute further to the classification of three CFTR amino acid changes (p.I148T, p.R74W and p.D1270N) either as CF or CBAVD-causing mutations or as neutral variations. Methods The CFTR genes from individuals who carried at least one of these changes were extensively scanned by a well established DGGE assay followed by direct sequencing and familial segregation analysis of mutations and polymorphisms. Results Four CF patients (out of 1238) originally identified as carrying the p.I148T mutation in trans with a CF mutation had a second mutation (c.3199del6 or a novel mutation c.3395insA) on the p.I148T allele. We demonstrate here that the deletion c.3199del6 can also be associated with CF without p.I148T. Three CBAVD patients originally identified with the complex allele p.R74W-p.D1270N were also carrying p.V201M on this allele, by contrast with non CF or asymptomatic individuals including the mother of a CF child, who were carrying p.R74W-p.D1270N alone. Conclusion These findings question p.I148T or p.R74W-p.D1270N as causing by themselves CF or CBAVD and emphazises the necessity to perform a complete scanning of CFTR genes and to assign the parental alleles when novel missense mutations are identified. ==== Body Background Cystic fibrosis (CF) is a common, often fatal disease with a well-defined genetic cause, so that it is now recommended in many countries in Europe and the United States to offer genetic screening for CF mutations to identify carriers among adults with a positive family history of CF, partners of individuals with CF, couples planning a pregnancy, couples seeking prenatal care and, recently, neonatal screening. Because of the mutational heterogeneity and the rarity of many mutations, most clinical DNA laboratories offer tests that aim to detect 75–95 % of CF alleles depending on the ethnic and geographic backgrounds of the population, using available commercial kits motsly including 20 to 31 mutations selected on the basis of their frequency as CF-causing mutations. A few laboratories (most often national reference laboratories) have developed the scanning of coding/flanking CFTR sequences to detect unknown mutations. As of February 2004, about 1200 disease-causing mutations have been identified in the cystic fibrosis transmembrane conductance regulator (CFTR) gene Frameshift, splice-site, nonsense, and in-frame but nonfunctional deletions (such as p.F508del) are disease-causing mutations. By contrast, the status of some missense mutations is extremely difficult to assess and functional studies are not available to diagnostic laboratories. Missense mutations may represent, depending on the populations, up to 45% of mutations responsible for CF or CBAVD (congenital bilateral absence of vas deferens). Moreover, due to improved scanning strategies, a growing number of complex alleles (several sequence changes on the same gene) are thought to affect the expression of the disease phenotype by modulating the effect of a mutation [1-5]. The most striking exemple is the length of the intron 8 polythymidine tract (7, 9, or 5 thymidines) on exon 9 splicing as a genetic modifier of the severity of the p.R117H mutation [1]. Another exemple is the revertant mutation p.R553Q which, when carried on the same gene as p.F508del, is associated with a CF phenotype with normal chloride concentration in sweat test [6] and which, when expressed in heterologous cells, can partially correct the processing and Cl- channel gating defects caused by the p.F508del mutation [7]. With the start of population screening for CF carriers, new data on the prevalence of some missense mutations have been provided, questioning their involvement as disease-causing mutations. In North American populations, missense mutations p.I148T and p.D1270N were found >100 times and >200 times, respectively, more frequently in carrier screening than in CF patients [8,9]. Moreover, we and others have found that individuals affected with CF or CBAVD carry p.D1270N associated with p.R74W on the same allele [p.R74W;p.D1270N] [10,11,5]. Similarly, p.I148T has been shown to be associated with a CF phenotype only as a complex allele, i.e. when associated with mutation c.3199del6 on the same gene [8]. A completely asymptomatic male individual who is a compound heterozygote for p.D1270N and p.I148T has been recently identified [9]. These findings provided evidence that these missense changes may not be the true mutations and prompted us to reanalyze all the patients in our CF or CBAVD cohort who had been originally diagnosed as compound heterozygotes for either p.I148T or [p.R74W;p.D1270N] and another mutation on the other allele. The result of full scanning of CFTR sequences showed that a second mutation (c.3199del6 or the novel mutation c.3395insA) was associated in cis with p.I148T in all individuals with a CF phenotype, and that a third missense mutation (p.V201M) was associated in cis with complex allele [p.D1270N;p.R74W] in patients with a CBAVD phenotype in this series. Methods CFTR scanning for individuals with p.I148T or [p.D1270N;p.R74W] From 1990 to 2003, we have analysed for CFTR mutations genomic DNA from 437 families with CF and 170 with isolated azoospermia caused by CBAVD, using a combination of mutation screening for known and scanning for unknown mutations. The first step was the search of 31 CF mutations detected by the ABI oligonucleotide ligation assay and 3 common intronic mutations by using restriction analysis. The second step was the scanning of coding/flanking sequences by DGGE (Denaturing Gradient Gel Electrophoresis) using 32 GC-clamped amplimers (which in our experience detected 98% of CFTR mutants), followed by sequencing to resolve abnormal PCR products (BigDye terminator cycle sequencing on ABI 310 automate sequencer). Whenever possible, family members were assayed for the mutations and associated polymorphisms. We detected 160 different mutations in the CF group accounting for 97 % of CF alleles, and 64 different mutations in the CBAVD group accounting for 85% of CBAVD alleles, which represents one of the highest allelic heterogeneity reported so far. Usually, mutation scanning is stopped when two mutations are found to be in trans. In this study, we analyzed by DGGE the entire coding and flanking regions of the CFTR gene of individuals who had been previously found to carry p.I148T or the complex allele [p.R74W;p.D1270N] and assayed their relatives for the additional sequence changes identified. We also re-analyzed the CFTR gene of a CF patient who had been originally described with c.394delTT in trans of c.3195del6 [12], now renamed c.3199del6 (see the Results). Studies to determine the frequency of each sequence alteration described in this report were performed on 600 chromosomes from our general population (Southern France). In addition, we also reanalyzed two additional CF patients previously found to carry p.I148T in the Lyon genetic center. The study was approved by the institutional ethical committees and informed consent was obtained from families. Nomenclature Gene variants and mutants are described using DNA and protein designation: intronic changes, deletions, insertions and frameshifts are reported at the cDNA level (c.) and amino acid changes at the protein level (p.), as recommended in the Human Genome Variation Society web page . Results A CF mutation (c.3199del6 or c.3395insA) is associated in cis with p.I148T in CF patients Two out of 437 CF patients analyzed in Montpellier and two out of 801 CF patients analyzed in Lyon were found to carry p.I148T, which was initially thought to be one of the two mutations responsible for CF in these patients. However, thorough re-analysis of the entire CFTR sequence determined that a CF mutation (c.3395insA or c.3199del6) was present on the same gene in both cases (table 1). Table 1 CFTR haplotypes associated with mutations found in CF patients carrying p.I148T in cis with c.3395insA or c.3199del6 and in one CF patient carrying c.3199del6 alone Indiv No. Age at Diagnosis Phenotype CFTR Mutations CFTR haplotype IVS1 IVS8 IVS8 IVS8 470 IVS17B IVS17B EGHa CA CA TGm Tn TA CA CF1 7 yrs CF-PI c.394delTT 21 23 10 9 M 36 13 B c.3199del6 22 16 11 7 V 7 17 C CF2 10 yrs CF-PS [c.3395insA;p.I148T] 21 23 10 9 M 7 17 B p.R334W 22 17 11 7 V 46 13 A CF3 6 ms CF-PI [c.3199del6;p.I148T] 21 23 10 9 M 7 17 B p.F508del 21 23 10 9 M 31 13 B CF4 3 yrs CF-PI [c.3199del6;p.I148T] 22 23 nd 9 M 7 17 B p.F508del 22 17 nd 9 M 31 15 B CF5 6 ms CF-PI [c.3199del6;p.I148T] 22 23 nd 9 M 7 17 B p.F508del 22 23 nd 9 M 31 13 B aEGH, extragenic haplotype XV2c/TaqI, KM19/PstI ; nd, not determined Patients CF1-3 were from the cohort of Montpellier (n = 437), patients CF4-5 were from the cohort of Lyon (n= 801). Mutation c.3199del6 can also occur alone as a CF-causing allele Mutation c.3199del6 was found to be carried without p.I148T in a young CF male with 394delTT on the other allele, diagnosed at the age of 7 years on the basis of typical pulmonary disease, pancreatic insufficiency, poor growth and positive sweat test [12]. Mutation c.3199del6 was initially described by us in 1994 in this patient as c.3195del6 [12], in accordance with the first draft of mutation nomenclature [13]. However, it occurred in the same palindromic sequence in exon 17a than mutation c.3199del6 reported in 1998 by Bozon et al. [14]. Both mutations are expected to delete either amino acids Val1022 and Ile1023, or Ile1023 and Val1024 from the CFTR protein. As it is impossible to determine at the genomic level in which part of the palindrome each of them occurred, the most 3'copy of the repeat is arbitrarily assigned to have been mutated, according to the current rule [15]. Consequently, mutations c.3195del6 and c.3199del6 should be considered as identical and reported as c.3199_3204del. The familial segregation analysis of polymorphisms covering the CFTR gene showed that p.I148T, when present in individuals with a CF phenotype, occurred on a unique haplotype carrying IVS8-9T whatever the mutation in cis, c.3395insA or c.3199del6 (table 1). By contrast, c.3199del6 without p.I148T occurred on a different haplotype carrying IVS8-7T. Mutations p.I148T, c.3199del6 and c.3395insA were not found on 600 chromosomes from our general population. Triple-mutant allele [p.R74W;p.V201M;p.D1270N] is found in males with CBAVD whereas double-mutant allele [p.R74W;p.D1270N] is found in asymptomatic individuals Re-analysis of the CFTR gene in families carrying [p.R74W;p.D1270N] identified a third mutation (p.V201M) on the same chromosome in three unrelated individuals with CBAVD (table 2). Only the double-mutant p.R74W-p.D1270N was present in the two unaffected individuals who were found with these changes in our sample. The first case was a young boy who had been initially suspected of having CF at age 4 years because of allergic rhinitis but for whom the diagnosis of CF was later ruled out; no other CFTR sequence alteration could be identified and the sweat tests were negative (chloride values <40 mM). The second individual was the mother of a CF girl who was compound heterozygous for p.F508del and p.P67L. This woman, who was carrying p.P67L on one CFTR gene and [p.R74W-p.D1270N] on the other (table 1), was completely asymptomatic at age 45 years and displayed three negative sweat tests (chloride values <20 mM). The triple and double mutant alleles seem to have occurred on the same haplotype TG11-T7-V470. Table 2 CFTR sequence changes found in individuals carrying missense alterations p.R74W, p.D1270N, or p.V201M Mutations Haplotype IVS1 IVS8 IVS8 IVS8 470 IVS17B IVS17B CA CA TGm Tn TA CA CBAVD1 p.R1066C 22 16 11 7 V 30 13 [p.R74W;p.V201M;p.D1270N] 22 16 11 7 V 31 13 CBAVD2 p.M952I 26 17 10 7 M 7 17 [p.R74W;p.V201M;p.D1270N] 22 16 11 7 V 31 13 CBAVD3 [p.R74W;p.V201M;p.D1270N] 22 16 11 7 V 31 13 [p.R74W;p.V201M;p.D1270N] 22 16 11 7 V 31 13 Individual non affected with CF No mutation 21 nd 10 7 M 7 17 [p.R74W;p.D1270N] 22 nd 11 7 V 30 13 Asymptomatic mother of a CF affected girl p.P67L 23 16 10 7 M 7 17 [p.R74;p.D1270N] 22 16 11 7 V 31 13 Discussion p.I148T is a low penetrance CF mutation or a neutral polymorphism Since its initial description in a CF Canadian patient with pancreatic insufficiency [16], the mutation p.I148T, which changes a conserved amino acid and occurs in the first cytoplasmic loop of the CFTR protein, has been considered as a severe CF allele in many countries. It was thought to be the second most common CF mutation in the French Canadian population, accounting for 9.1% of the French Canadian chromosomes [17], whereas in France, p.I148T accounted for only 0.11 % of the CF alleles in a sample of 3,710 patients affected with the disease [5]. p.I148T can now be detected by several commercially available kits developed for routine screening of CF carriers and for CF neonatal screening, and recently it has been included in the core panel of 25 CF mutations recommended by the American College of Medical Genetics (ACMG) [18]. Thousands of individuals are being screened for this mutation worldwide and it is possible that several prenatal diagnosis have been or will be performed. However there are now several lines of evidence that question the role of p.I148T by itself in causing disease. First, compound heterozygosity for p.I148T and a severe CF mutation was recently identified in several healthy individuals [9,19]. When affected and unaffected individuals carrying apparently the same mutational genotype were re-analyzed for additional changes that could explain the different phenotypes, p.I148T was found to be associated in cis with another mutation, c.3199del6, in patients with a classic CF phenotype, whereas healthy adults who were compound heterozygous for p.I148T and a severe CF mutation or homozygous for p.I148T did not carry the deletion [8]. In a recent study, the p.I148T mutation has been further documented to be linked with the 3199del6 mutation in all 24 CF patients of French Canadian descent originally identified as compound heterozygous for the p.I148T mutation and a second severe CFTR mutation [20]. Second, p.I148T was found to be over 100 times more common in two independent U.S. carrier screening programmes than in CF patients: it accounted for 6.4 to 7.7% of chromosomes detected in the screened populations versus 0.06 to 0.068% of CF chromosomes in CF patients [8. 9]. This discrepancy suggests that p.I148T is either a poorly penetrant mutation or a neutral polymorphism. Third, when transiently expressed in epithelial cells, p.I148T mutant protein is normally processed and is able to mediate normal chloride transport with properties identical with those of wild-type cells [21]. As the mutant seems to suppress the ability of CFTR to support HCO3- transport, it has been hypothesized that p.I148T may contribute to disease through Cl- coupled HCO3- altered transport; however, the major CFTR functions are retained by the mutant [21]. Fourth, we show in this study for the first time that p.I148T can be associated with a frameshift mutation c.3395insA in exon 17b instead of in-frame deletion c.3199del6 in exon 17a. Insertion c.3395insA (designated as c.3395_3396insA) is a previously unreported mutation that is predictive of premature termination of translation at amino acid residue 1155. The truncated protein lacking the 325 last amino acids is believed to be not functional and be degraded rapidly, generating no detectable protein. A CFTR alteration producing a premature termination signal is a class I mutation, considered severe enough to cause CF by itself and exclude the contribution of any other sequence change on the same allele. Fifth, in contrast with other studies that stated that only the complex allele [p.I148T;9T;c.3199del6] appeared to be associated with a classic CF phenotype [8], we demonstrate that c.3199del6 is associated with a CF phenotype even if the deletion occurs on a chromosome that does not carry p.I148T, which adds further value to the consideration that p.I148T is not a true mutation but simply a polymorphism. Although no functional test was performed to prove its contribution to the severe phenotype, mutation c.3199del6 has been considered as a defective allele as it results in the loss of two amino acid residues in the TM10 domain of the CFTR protein and has not been detected in non-CF alleles. Our data fully support the recent recommendation that p.I148T should not be included in the mutation panel selected for prenatal screening strategy [22]. The complex allele [p.R74W;p.D1270N] may be not enough to cause disease We and others had initially described p.R74W [23] and p.D1270N [24] in isolation but they have since been found in association in many CBAVD or CF patients [10,11] and these two changes were thought to be deleterious, alone or in combination. A few complex alleles have been expressed in heterologous systems to evaluate the impact on CFTR processing and Cl- channel activity and better understand the contribution of each missense mutation on phenotype. When expressed in HeLa cells, mutant p.R74W, p.D1270N and [p.R74W;p.D1270N] did not affect CFTR processing, however a lower cAMP-responsive anion conductance was observed with the double mutant [p.R74W;p.D1270N] [3]. The assay suggested that p.R74W alone should be considered as a polymorphism, p.D1270N alone could generate a CBAVD phenotype while the complex allele could produce a more severe phenotype as p.R74W could enhance the effect of p.D1270N [3]. However these findings have not yet been confirmed by other studies. We have found here that a triple-mutant [p.R74W;p.V201M;p.D1270N] allele was carried in all three patients with CBAVD whereas only the double mutant [p.R74W;p.D1270N] allele was present in two asymptomatic individuals including an obligate carrier who was compound heterozygous for a CF mutation. Another mother carrying [p.R74W;p.D1270N] in trans of a CF mutation has been described previously; despite two positive sweat tests she was absolutely asymptomatic [25]. Missense p.V201M in exon 6a changes a valine for a methionine in the third transmembrane domain; it was initially reported alone in a French patient with CBAVD [26], then in Brazilian patients with CF [27]. Recent large scale screening for CF carrier showed that p.D1270N was present 205 times more commonly in the screened population than in the CF patients (frequency of 14% versus 0.068%); in addition, a completely asymptomatic adult compound heterozygote for p.D1270N and p.I148T has been identified [9]. Although it is not known whether these alleles are associated or not with the third change p.V201M, there are now enough evidence to question the role of the complex allele [p.R74W;p.D1270N] as being a CF or CBAVD mutation. Further experimental and genetic investigations will be necessary to demonstrate the role of p.V201M in causing disease. Conclusions This report further corroborates the recent hypothesis [9] that p.I148T and p.R74W-p.D1270N may not be true CF/CBAVD mutations. If these observations are further confirmed by a large multicentric study, they will have important implications for genetic counseling of patients and couples found to carry p.I148T or [p.R74W;p.D1270N]. They also pinpoint several important points in genetic testing for CF : first, the necessity of scanning the whole regions of the CFTR gene for diagnosis purposes, whatever the cost; second the necessity to better standardize mutation nomenclature, and third the usefulness of confirming inheritance of mutations from both parents whenever possible to avoid the risk for erroneously reporting changes in trans that are in fact complex alleles. Competing interests None declared. Authors'contributions JPA, CG, CT and FC carried out the molecular genetic studies. MDG coordonated the molecular analysis. MC conceived the study and drafted the manuscript. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here: Acknowledgements We thank the CHU of Montpellier and the French Association against CF for their support, and the reviewers for their helpful comments. ==== Refs Kiesewetter S Macek M JrDavis C Curristin SM Chu CS Graham C Shrimpton AE Cashman SM Tsui LC Mickle J A mutation in CFTR produces different phenotypes depending on chromosomal background Nat Genet 1993 5 274 278 7506096 Savov A Angelicheva D Balassopoulou A Jordanova A Noussia-Arvanitakis S Kalaydjieva L Double mutant alleles: are they rare? Hum Mol Genet 1995 4 1169 1171 8528204 Fanen P Clain J Labarthe R Hulin P Girodon E Pagesy P Goossens M Edelman A Structure-function analysis of a double-mutant cystic fibrosis transmembrane conductance regulator protein occurring in disorders related to cystic fibrosis FEBS Lett 1999 452 371 374 10386624 10.1016/S0014-5793(99)00647-X Romey MC Pallares-Ruiz N Mange A Mettling C Peytavi R Demaille J Claustres M A naturally occurring sequence variation that creates a YY1 element is associated with increased cystic fibrosis transmembrane conductance regulator gene expression J Biol Chem 2000 275 3561 3567 10652351 10.1074/jbc.275.5.3561 Claustres M Guittard C Bozon D Chevalier F Verlingue C Ferec C Girodon E Cazeneuve C Bienvenu T Lalau G Dumur V Feldmann D Bieth E Blayau M Clavel C Creveaux I Malinge MC Monnier N Malzac P Mittre H Chomel JC Bonnefont JP Iron A Chery M Georges MD Spectrum of CFTR mutations in cystic fibrosis and in congenital absence of the vas deferens in France Hum Mutat 2000 16 143 156 10923036 10.1002/1098-1004(200008)16:2<143::AID-HUMU7>3.0.CO;2-J Dork T Dworniczak B Aulehla-Scholz C Wieczorek D Bohm I Mayerova A Seydewitz HH Nieschlag E Meschede D Horst J Pander HJ Sperling H Ratjen F Passarge E Schmidtke J Stuhrmann M Cystic fibrosis with three mutations in the cystic fibrosis transmembrane conductance regulator gene Hum Genet 1991 87 441 446 1715308 Teem JL Berger HA Ostedgaard LS Rich DP Tsui LC Welsh MJ Identification of revertants for the cystic fibrosis delta F508 mutation using STE6-CFTR chimeras in yeast Cell 1993 73 335 346 7682896 10.1016/0092-8674(93)90233-G Rohlfs EM Zhou Z Sugarman EA Heim RA Pace RG Knowles MR Silverman LM Allitto BA The I148T CFTR allele occurs on multiple haplotypes: a complex allele is associated with cystic fibrosis Genet Med 2002 4 319 323 12394343 10.1097/00125817-200209000-00001 Strom CM Huang D Buller A Redman J Crossley B Anderson B Entwistle T Sun W Cystic fibrosis screening using the College panel: platform comparison and lessons learned from the first 20,000 samples Genet Med 2002 4 289 296 12172395 10.1097/00125817-200207000-00007 Anguiano A Oates RD Amos JA Dean M Gerrard B Stewart C Maher TA White MB Milunsky A Congenital bilateral absence of the vas deferens. A primarily genital form of cystic fibrosis JAMA 1992 267 1794 1797 1545465 10.1001/jama.267.13.1794 Casals T Bassas L Ruiz-Romero J Chillon M Gimenez J Ramos MD Tapia G Narvaez H Nunes V Estivill X Extensive analysis of 40 infertile patients with congenital absence of the vas deferens: in 50% of cases only one CFTR allele could be detected Hum Genet 1995 95 205 211 7532150 Claustres M Laussel M Desgeorges M Demaille J Identification of a 6 bp deletion (3195del6) in exon 17a of the cystic fibrosis (CFTR) gene Hum Mol Genet 1994 3 371 372 7516234 Beaudet AL Tsui L-C A suggested nomenclature for designating mutations Hum Mutat 1993 2 245 248 8401532 Bozon D Cystic fibrosis Mutation Data Base, NL 70 March 19, 1998 Den Dunnen JT Antonarakis E Nomenclature for the description of human sequence variations Hum Genet 2001 109 121 124 11479744 10.1007/s004390100505 Bozon D Zielenski J Rininsland F Tsui L-C Identification of four new mutations in the cystic fibrosis transmembrane conductance regulator gene: I148T, L1077P, Y1092X, 2183AA>G Hum Mutat 1994 3 330 332 7517268 The Cystic Fibrosis Genetic Analysis Consortium Population variation of common cystic fibrosis mutations Hum Mutat 1994 4 167 177 7530552 Grody WW Cutting GR Klinger KW Richards CS Watson MS Desnick RJ Subcommittee on Cystic Fibrosis Screening, Accreditation of Genetic Services Committee, ACMG. American College of Medical Genetics. Laboratory standards and guidelines for population-based cystic fibrosis carrier screening Genet Med 2001 3 149 154 11280952 10.1097/00125817-200103000-00010 Rohlfs EM Sugarman EA Heim RA Allitto BA Frequency of carriers of two cystic fibrosis mutations in an apparently unaffected adult population Genet Med 2001 3 237 Ruchon AF Ryan SR Rozen R Scott P Genotype-phenotype correlation between the complex allele I148T-3199del6 and cystic fibrosis In : Annual Meeting of the American Association of Human Genetics [abstract 1402] Abstract appears in Am J Hum Genet Suppl 2003 Choi JY Muallem D Kiselyov K Lee MG Thomas PJ Muallem S Aberrant CFTR-dependent HCO3- transport in mutations associated with cystic fibrosis Nature 2001 410 94 97 11242048 10.1038/35065099 Wald NJ Morris JK Rodeck CH Haddow JE Palomaki GE Cystic fibrosis: selecting the prenatal screening strategy of choice Prenat Diagn 2003 23 474 483 12813761 10.1002/pd.618 Claustres M Laussel M Desgeorges M Giansily M Culard JF Razakatsara G Demaille J Analysis of the 27 exons and flanking regions of the cystic fibrosis gene : 40 different mutations account for 91,2% of the mutant alleles in Southern France Hum Mol Gen 1993 2 1209 1213 7691344 Dean M Gerrard B Stewart C Krueger L Holsclaw D Quittell L Baranov V Kapronov N Leppert M Amos J White M Identification of cystic fibrosis mutations Adv Exp Med Biol 1991 290 45 51 1719771 Verlingue C David A Audrezet MP Le Roux MG Mercier B Moisan JP Ferec C Asymptomatic carrier of two CFTR mutations: consequences for prenatal diagnosis ? Prenat Diagn 1993 13 1143 1148 7513889 Ferec C Cystic fibrosis Mutation Data Base January 1st, 1998. Bernardino AL Ferri A Passos-Bueno MR Kim CE Nakaie CM Gomes CE Damaceno N Zatz M Molecular analysis in Brazilian cystic fibrosis patients reveals five novel mutations Genet Test 2000 4 69 74 10794365 10.1089/109065700316516

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==== Front BMC CancerBMC Cancer1471-2407BioMed Central London 1471-2407-4-411528578210.1186/1471-2407-4-41Case ReportAdenoid cystic carcinoma of the parotid metastasizing to liver: case report Harish K 1drkhari@yahoo.comMangala Gouri SR 2drkhari@yahoo.com1 Department of Surgical Oncology, M. S. Ramaiah Medical College & Hospital, Bangalore – 560054, India2 Department of Pathology, M. S. Ramaiah Medical College & Hospital, Bangalore – 560054, India2004 30 7 2004 4 41 41 20 3 2004 30 7 2004 Copyright © 2004 Harish and Mangala Gouri; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background Adenoid cystic carcinoma is a rare malignant parotid tumor. Metastasis can occur even a decade or more after initial treatment of the primary. Case presentation We report a 60 year old female patient who presented with adenoid cystic carcinoma of the parotid gland. She underwent a total conservative parotidectomy followed by adjuvant radiotherapy. While on follow up, patient developed multiple liver metastases which manifested three years later. Patient lived for another two years before she died of her disease. Conclusions Although distant metastases of adenoid cystic carcinoma develop frequently, isolated metastasis to liver is unusual. Even after manifestation of distant metastasis, patients can be expected to live for a number of years. Palliative chemotherapy can be considered in symptomatic cases while the usefulness of metastatectomy is controversial. ==== Body Background Adenoid cystic carcinoma (ACC) is a rare malignant neoplasm of the salivary gland. Salivary gland neoplasms constitute 3% of cancers of all sites, of which, 10–15% are malignant [1,2]. Though ACC is the most common malignant tumor of the submandibular, sublingual and minor salivary glands, it accounts for only 15% of parotid cancers [3]. They are generally slow growing and spread relentlessly to adjacent structures. Hematogenous spread is more common than lymphatic spread, the common sites of metastasis being the lung, bone and viscera [4,5]. We present a case of multiple liver metastases occurring 3 years after surgery for ACC of the parotid gland. The primary therapy, metastasis and outcome of ACC are discussed. Case presentation A 60 year old woman presented with a small swelling beneath the right ear lobe of 4 months duration. The swelling measured 2 × 1 cm placed in the superficial part of the parotid and was not fixed. There was no facial nerve palsy or palpable cervical nodes. A fine needle aspiration cytology (FNAC) was carried out which showed the lesion to be ACC [6]. The clinical staging was T1, N0, M0. The patient underwent a total conservative parotidectomy after metastatic work up. Histopathology revealed ACC with cribriform pattern and perineural invasion (Figure 1). 60 Gy adjuvant external beam radiotherapy was administered post-operatively to the parotid area and the neck. Patient was placed on regular follow-up. Three years after primary surgery, patient presented with heaviness and pain in the right hypochondrium of 15 days duration. Patient was anicteric and abdominal examination revealed firm nodular and non tender enlargement of the liver. There was no ascites. Surgical site and neck were clinically normal. Chest roentgenogram was normal. Ultrasonography (US) of the abdomen revealed multiple metastatic lesions scattered in both lobes (Figure 2). Liver function tests were normal and an US guided FNAC revealed metastatic ACC (Figure 3). Since the lesions were multiple and scattered over both lobes of liver, surgical option was not considered and the patient was offered palliative chemotherapy which she declined. She developed pedal edema and abdominal distention 20 months after detection of liver metastasis. On clinical examination, patient was anicteric but liver had increased in size and abdomen showed evidence of a little free fluid. Chest CT scan was normal. Bone scan did not suggest any metastatic focus. Patient died a month later still without evidence of local recurrence or pulmonary metastasis. Conclusions Although ACC is the second most common malignant salivary gland neoplasm and constitutes approximately one third of all salivary gland malignancies it constitutes only 2% of parotid neoplasms [3]. As ACC is neurotropic, frozen section analysis of nerve margins is suggested specially when nerve is grossly involved by the tumor [7]. A total conservative or a radical parotidectomy is advocated for ACC though the main intent is to obtain a tumor free area of at least 1 cm [8]. ACC, with its often unusually slow biologic growth, tends to have a protracted course and ultimately a poor outcome, with a 10-year survival reported to be less than 50% for all grades [9,10]. These carcinomas typically show frequent recurrences and late distant metastases [11]. In a retrospective review of 92 cases, a tumor size greater than 4 cm was associated with an unfavorable clinical course [12]. Cribriform and solid patterns seen histologically were thought to predict more biological aggressiveness while tubular pattern represented more differentiated pattern of ACC. Over long periods of patient follow-up such grade based prognostication is less valid. Currently, stage and tumor location are the only factors considered prognostically significant [13]. Radiotherapy has been used as a primary modality for patients with surgical contraindications and in those with unresectable neoplasms. Though no improvement in survival is reported, the use of adjuvant radiation improves locoregional control and disease free survival. This patient received adjuvant radiation and did not have any locoregional recurrence. Regional metastasis is less common occurring in about 17% while systemic failure occurs in 33 to 50% of the patients [4,8]. Though involvement with distant metastases are unpredictable, organs involved in the order of decreasing frequency are lung, bone, brain and the liver [3]. Other rare metastatic sites of parotid and non parotid ACC include stomach, toe, choroids, brain and skin [14-18]. The initial site of metastasis is usually the organ containing the first capillary bed (first filter) and hence lungs would be the common site of metastasis [19]. Clinical observations from various malignancies have indicated that metastasis from certain types of tumor tend to occur in specific target organs leading to the famous 'soil and seed' hypothesis where metastatic cells 'home' to the organ [20]. Though liver metastasis has been reported, most of the liver metastases reported are of non parotid ACC [3,5]. The occurrence is usually metachronous or synchronous with metastasis to other organs like the lung as it is the first filter. In the series of Spiro, of the 74 patients developing metastasis from salivary gland ACC, 23 did so without loco-regional recurrence while 5 had isolated bone metastasis [5]. Sung and colleagues found metastases in 46 out of 94 head and neck ACC [21]. In that study, only one patient developed liver metastasis and that patient had metastasis to both lung and bone. In this case, the patient manifested with multiple metastatic foci in the liver as the first and only metastatic organ which is very unusual. Surgical options of metastatectomy were not explored as patient had multiple metastases involving both lobes of liver. Although the patient lived with disease for a further two years, she did not show any evidence of lung metastasis or loco-regional recurrence. In this patient, the liver metastasis could have occurred prior to treatment as an organ of preference; evidenced by the fact that there were no other organs showing metastasis nor was there a loco-regional recurrence later. Studies in ACC have shown long tumor doubling times of pulmonary metastasis and late recurrences up to 10 years after primary treatment [22]. The estimated doubling time of lung metastasis in ACC ranges from 200 to 600 days [22]. There is even a suggestion that metastasis at the cellular level could occur many years prior to clinical presentation of primary tumor. FNAC was done to prove the metastatic foci in this patient and can be a useful tool for diagnosis [23]. Although this patient declined chemotherapy, chemotherapeutic responses have been reported in ACC [24]. ACC carries a mortality of 75–80% over a 30 year period and most patients who die of their disease do so between 5 and 10 years after initial treatment [10]. Our patient died 5 years from diagnosis with metastatic disease that developed 3 years after initial treatment. ACC is a rare malignant tumor of parotid gland. Metastasis can manifest very late and hence a long term follow-up and a high index of suspicion is necessary to diagnose them early. An annual ultrasound study of abdomen would be desirable on follow-up. Unlike metastasis from other malignancies, these grow indolently and long term survival can be expected even with multiple metastases as also evidenced in the present case. Chemotherapy could be considered in selected patients as a therapeutic option in metastatic disease. List of abbreviations used ACC: Adenoid cystic carcinoma FNAC: Fine needle aspiration cytology Gy: Gray Competing interests None declared Authors' contributions KH was the principal clinician who planned the evaluation and procedure, in addition to conceptualizing and drafting the article. SRMG was the pathologist. Both the authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here: Acknowledgments Since the patient has expired, the legal heir was informed that the case would be published and his consent was obtained. Figures and Tables Figure 1 Photomicrograph showing small darkly stained cells with scanty cytoplasm arranged in nests fenestrated by round or oval spaces – cribriform pattern, H & E (× 100) Figure 2 Abdominal ultrasound showing multiple hypoechoiec (short arrow) and hyperechoeic lesions (long arrow) in the liver Figure 3 FNAC liver showing metastatic ACC, H & E (× 400) ==== Refs Luna MA Thawley SE, Panje WR, Batsakis JG, Lindberg RD Pathology of tumors of the salivary glands In Comprehensive management of head and neck tumors 1999 Philadelphia: WB Saunders company 1106 46 Spiro RH Salivary neoplasms: Overview of a 35 year experience with 2807 patients Head Neck Surg 1986 8 177 84 3744850 Spiro RH Huvos AG Strong EW Adenoid cystic carcinoma of salivary origin. A clinicopathologic study of 242 cases Am J Surg 1974 128 512 20 4371368 10.1016/0002-9610(74)90265-7 Spiro RH Huvos AG Stage means more than grade in adenoid cystic carcinoma Am J Surg 1992 164 623 8 1334380 Spiro RH Distant metastasis in adenoid cystic carcinoma of salivary origin Am J Surg 1997 174 495 8 9374223 10.1016/S0002-9610(97)00153-0 Orell SR Sterrett GF Walters MNI Whitaker D editors Manual and atlas of fine needle aspiration cytology New York, NY, Orlando, FL: Churchill Livingstone, Harcourt Brace 1999 41 3 Hoffman H Funk G Endres D Thawley SE, Panje WR, Batsakis JG, Lindberg RD Evaluation and surgical treatment of tumors of the salivary gland In Comprehensive management of head and neck tumors 1999 Philadelphia: WB Saunders company 1147 81 Casler JD Conley JJ Surgical management of adenoid cystic carcinoma in the parotid gland Otolaryngol Head Neck Surg 1992 106 332 8 1314372 Spiro RH McGurk M, Renehan AG The controversial adenoid cystic carcinoma. Clinical considerations Controversies in the Management of Salivary Gland Disease 2001 Oxford, UK: Oxford University Press 207 11 Speight PM Barrett AW Salivary gland tumours Oral Dis 2002 8 229 40 12363107 10.1034/j.1601-0825.2002.02870.x Friedrich RE Bleckmann V Adenoid cystic carcinoma of salivary and lacrimal gland origin: localization, classification, clinical pathological correlation, treatment results and long-term follow-up control in 84 patients Anticancer Res 2003 23 931 40 12820326 Hamper K Lazar F Dietel M Caselitz J Berger J Arps H Falkmer U Auer G Seifert G Prognostic factors for adenoid cystic carcinoma of the head and neck: a retrospective evaluation of 96 cases J Oral Pathol Med 1990 19 101 7 2160530 Perez-Ordonez B Selected topics in salivary gland tumour pathology Curr Diagn Pathol 2003 9 355 65 10.1016/S0968-6053(03)00070-X Kakizaki S Ishihara H Onozato Y Abe T Sakurai S Iizuka H Katakai S Itoh H A case of primary adenoid cystic carcinoma in right submandibular salivary gland which showed an unusual metastasis to the stomach (in Japanese) Nippon Shokakibyo Gakkai Zasshi (The Japanese Journal of Gastroenterology) 1995 92 164 8 Weitzner S Adenoid cystic carcinoma of submaxillary gland metastatic to great toe Am Surg 1975 41 655 8 1163909 Gutmann SM Weiss JS Albert DM Choroidal metastasis of adenocystic carcinoma of the salivary gland Br J Ophthalmol 1986 70 100 3 3004556 Kazumoto K Hayase N Kurosumi M Kishi K Uki J Takeda F Multiple brain metastases from adenoid cystic carcinoma of the parotid gland Surg Neurol 1998 50 475 9 9842876 10.1016/S0090-3019(97)00341-8 Chang CH Liao YL Hong HS Cutaneous metastasis from adenoid cystic carcinoma of the parotid gland Dermatol Surg 2003 29 775 9 12828706 10.1046/j.1524-4725.2003.29196.x Sugarbaker EV Patterns of metastasis in human malignancies Cancer Biol Rev 1981 2 235 78 Hart IR "Seed and soil" revisited: Mechanisms of site specific metastasis Cancer Metastasis Rev 1982 1 5 16 6764375 Sung MW Kim KH Kim JW Min YG Seong WJ Roh JL Lee SJ Kwon TK Park SW Clinicopathologic predictors and impact of distant metastasis from adenoid cystic carcinoma of the head and neck Arch Otolaryngol Head Neck Surg 2003 129 1193 7 14623749 10.1001/archotol.129.11.1193 Umeda M Nishimatsu N Masago H Ishida Y Yokoo S Fujioka M Shibuya Y Komori T Tumor-doubling time and onset of pulmonary metastasis from adenoid cystic carcinoma of the salivary gland Oral Surg Oral Med Oral Pathol Oral Radiol Endod 1999 88 473 8 10519758 Mehrotra R Singh M Diagnosis of hepatic metastasis of adenoid cystic carcinoma of the salivary gland by fine needle aspiration Cytopathology 1999 10 216 7 10390072 10.1046/j.1365-2303.1999.0157a.x Budd GT Groppe CW Adenoid cystic carcinoma of the salivary gland: Sustained complete response to chemotherapy Cancer 1983 51 589 90 6295610

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==== Front BMC Public HealthBMC Public Health1471-2458BioMed Central London 1471-2458-4-291527474610.1186/1471-2458-4-29Research ArticleEvaluation of reporting timeliness of public health surveillance systems for infectious diseases Jajosky Ruth Ann 1RJajosky@cdc.govGroseclose Samuel L 23SGroseclose@cdc.gov1 Centers for Disease Control and Prevention, Epidemiology Program Office, Division of Public Health Surveillance and Informatics, Surveillance Systems Branch, Atlanta, Georgia, 30333, USA2 Centers for Disease Control and Prevention, National Center for HIV, STD, & TB Prevention, Division of STD Prevention, Statistics and Data Management Branch, Atlanta, Georgia, 30333, USA3 At the time this study was conducted this co-author was Chief of the Surveillance Systems Branch2004 26 7 2004 4 29 29 13 2 2004 26 7 2004 Copyright © 2004 Jajosky and Groseclose; licensee BioMed Central Ltd.2004Jajosky and Groseclose; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background Timeliness is a key performance measure of public health surveillance systems. Timeliness can vary by disease, intended use of the data, and public health system level. Studies were reviewed to describe methods used to evaluate timeliness and the reporting timeliness of National Notifiable Diseases Surveillance System (NNDSS) data was evaluated to determine if this system could support timely notification and state response to multistate outbreaks. Methods Published papers that quantitatively measured timeliness of infectious disease surveillance systems operating in the U.S. were reviewed. Median reporting timeliness lags were computed for selected nationally notifiable infectious diseases based on a state-assigned week number and various date types. The percentage of cases reported within the estimated incubation periods for each disease was also computed. Results Few studies have published quantitative measures of reporting timeliness; these studies do not evaluate timeliness in a standard manner. When timeliness of NNDSS data was evaluated, the median national reporting delay, based on date of disease onset, ranged from 12 days for meningococcal disease to 40 days for pertussis. Diseases with the longer incubation periods tended to have a higher percentage of cases reported within its incubation period. For acute hepatitis A virus infection, which had the longest incubation period of the diseases studied, more than 60% of cases were reported within one incubation period for each date type reported. For cryptosporidiosis, Escherichia coli O157:H7 infection, meningococcal disease, salmonellosis, and shigellosis, less than 40% of cases were reported within one incubation period for each reported date type. Conclusion Published evaluations of infectious disease surveillance reporting timeliness are few in number and are not comparable. A more standardized approach for evaluating and describing surveillance system timeliness should be considered; a recommended methodology is presented. Our analysis of NNDSS reporting timeliness indicated that among the conditions evaluated (except for acute hepatitis A infection), the long reporting lag and the variability across states limits the usefulness of NNDSS data and aberration detection analysis of those data for identification of and timely response to multistate outbreaks. Further evaluation of the factors that contribute to NNDSS reporting timeliness is warranted. ==== Body Background Public health surveillance is defined as the "ongoing systematic collection, analysis, and interpretation of data essential to the planning, implementation, and evaluation of public health practice, closely integrated with the timely dissemination of these data to those who need to know"[1]. Reasons for conducting public health surveillance can include the need to assess the health status of a population, establish public health priorities, and reduce the burden of disease in a population by appropriately targeting effective disease prevention and control activities [2]. Timeliness is a key surveillance system metric and should be periodically evaluated [3,4] because it can reflect the time delay between any number of response steps in the public health surveillance process. Surveillance system timeliness depends on a number of factors and its assessment should include a consideration of how the data will be used and the nature of the condition under surveillance (e.g., for infectious diseases, this includes the communicability of the disease) [3]. If the data are to be used to implement immediate disease control and prevention activities for infectious diseases that are acute, severe, and highly transmissible, timeliness is critical. Timeliness requirements for a surveillance system might vary by different levels of public health system (e.g., local, state, or national), on the basis of the intended uses of the surveillance data at that level (Table 1). For example, timely data are needed within a state for identifying cases or clusters of disease that will prompt an immediate public health response. Timely national surveillance data aggregated from a number of jurisdictions may be used for identifying multistate outbreaks or disease clusters and enable the federal public health system to assist the states in performing and coordinating their prevention and control activities. In reportable disease surveillance systems, health care providers and diagnostic laboratories usually report information regarding persons with notifiable conditions to the local public health system. Then, reporting proceeds in a hierarchical fashion to the state and then to the national level. Health care provider and public health system actions at each successive level of the reporting hierarchy contribute to reporting timeliness delays at the national level. Table 1 Potential uses of infectious disease surveillance data, by level of the public health system Intended Uses Used at which level(s) of the public health system?* Identify individual cases or clusters in a jurisdiction to prompt intervention or prevention activities Local, State (National) Identify multi-state disease outbreaks or clusters. State, National Monitor trends to assess the public health impact of the condition under surveillance. State, National (Local) Demonstrate the need for public health intervention programs and resources, as well as allocate resources. State, National (Local) Monitor effectiveness of prevention, control, and intervention activities. State, National (Local) Formulate hypotheses for further study. National (State) *Public health system level in parentheses represents secondary use of the data for that purpose. State and national surveillance processes Before data can be used for public health action, health-related data must be collected by the public health system, analyzed, and disseminated to those responsible for taking action (Figure 1). Within a state (Steps 1–7), the public health system can use surveillance data for a number of purposes, including outbreak detection and intervention planning and implementation (Table 1). The number and sequence of actions a state conducts before reporting data to the national public health system might vary by state, depending on state policies and protocols (Figure 1). For example, for nationally notifiable infectious disease reporting, CDC recommends that states report as soon as they first receive information about a suspect, probable, or confirmed case. However, some states only report confirmed cases, which usually requires laboratory confirmation, and decreases reporting timeliness at the national level. Figure 1 Sequence of actions needed to gather and use health-related information for public health purposes Each week, states and the U.S. territories report case information on persons suspected of having or diagnosed with a nationally notifiable infectious disease to the Nationally Notifiable Diseases Surveillance System (NNDSS), maintained by the Centers for Disease Control and Prevention (CDC) [5]. A nationally notifiable disease is one for which "regular, frequent, and timely information regarding individual cases is considered necessary for prevention and control of the disease" [6]. At the national level, NNDSS data are used for monitoring trends, program planning, evaluation, policy development, research, and monitoring the effectiveness of prevention and control activities. Although NNDSS reporting timeliness for these long-range goals and objectives is not critical, the threat of terrorism prompted consideration of whether NNDSS could be enhanced in the future to support public health response for either naturally occurring diseases or terrorism preparedness and response efforts. Therefore, the timeliness of NNDSS data was evaluated to determine if NNDSS could support timely notification and state response to multistate outbreaks. To provide a context for the evaluation of NNDSS timeliness, published studies reporting timeliness measures for infectious disease surveillance systems in the United States were reviewed. Methods Literature review Infectious disease surveillance evaluation studies reporting timeliness measures that were published between January 1970 and March 2003 in biomedical and public health literature were reviewed. English-language papers were identified by using the Medline database (U.S. National Library of Medicine). The search strategy used various combinations of the following key words "timeliness," "reporting delay," "time delay," "lag time," "disease surveillance," "disease outbreaks," "communicable diseases," and "infectious diseases." Reference lists of the studies identified through the Medline search and studies citing CDC's surveillance evaluation guidelines were also reviewed [3,7] Reports were included if they evaluated a public health surveillance system operating in the United States and provided a quantitative estimate of disease-specific timeliness (e.g., interval in days). Studies without quantitative timeliness estimates or that reported a quantitative estimate for a group of infectious diseases (versus a disease-specific estimate) were excluded. In addition, studies describing the timeliness of syndromic surveillance systems were excluded. Information abstracted for the review included the disease(s) under surveillance, the geographic area and time period studied, the purpose of the surveillance evaluation, the surveillance time interval measured, the surveillance processes or actions (steps in Figure 1) covered within the measured time interval, the timeliness measure, and the study's assessment of whether surveillance data timeliness met the surveillance goals. NNDSS timeliness Information available for assessing NNDSS reporting timeliness includes the Morbidity and Mortality Weekly Report [MMWR] week number the state assigns to each case and one of the following earliest known dates associated with the incidence of this disease (earliest known date) from the following list of hierarchical date types: onset date, diagnosis date, date of laboratory result, or date of first report to the community health system. National reporting delay was calculated as the difference in days between the midpoint of the MMWR week and the earliest known date reported in association with the case. This time interval reflects various state-specific surveillance intervals in the surveillance process that occur between the occurrence of a health event and the reporting of that health event to NNDSS, but at a minimum it includes Intervals 1–4 (Figure 1). National median reporting timeliness was calculated overall for the years 1999–2001, for each disease in our study, by date type and state, and across all states. Median reporting delay was calculated using Proc means in SAS version 8 software for Windows (SAS Institute, Inc., Cary, North Carolina). To assess whether analysis of NNDSS data could support the timely identification of multistate outbreaks at the national level, the percentage of NNDSS cases reports reported within one to two incubation periods for each of the diseases was determined. Incubation periods were used as a surrogate measure for period of communicability which is critical to consider when implementing effective, disease-specific prevention and control measures. For this analysis, estimated incubation periods were used for the seven nationally notifiable infectious diseases selected for this study: 7 days for cryptosporidiosis, 4 days for Escherichia coli O157:H7 (E. coli), 30 days for acute hepatitis A virus infection, 4 days for meningococcal disease, 20 days for pertussis, 1.5 days for salmonellosis, and 3 days for shigellosis [8]. These diseases were selected because they were confirmed on the basis of laboratory criteria; they have the potential to occur in epidemics; they were designated nationally notifiable five years or more before the study period began; and the magnitude of reported disease incidence supported this analysis. Only finalized case-specific data reported from U.S. states and two autonomous reporting entities (New York City and Washington D.C., referred to as states, hereafter) that designated the reported condition as notifiable (reportable by law or regulation) and that met NNDSS publication criteria [9] were included in the analysis. Data were analyzed for MMWR years 1999, 2000, and 2001. Results Literature review Eight papers were identified that met the inclusion criteria for this study (Table 2 - see Additional file: 1) [10-17]. Seven of the eight papers met the inclusion criteria resulting from the literature review; an additional paper was identified from the review of reference lists of studies identified through the Medline search and studies citing CDC's evaluation guidelines [3,7]. Three of the eight papers in this study assessed national reporting timeliness; the remaining five papers focused on local or state reporting timeliness. The studies of national reporting timeliness focused on the following diseases: acquired immunodeficiency syndrome (AIDS) [17]; Neisseria meningitidis and Haemophilus influenzae infections [16]; and shigellosis, salmonellosis, hepatitis A, and bacterial meningitis [11]. The studies of local or state reporting timeliness analyzed data for AIDS [14,15], tuberculosis [13], influenza-like illness [10], and meningococcal disease [12]. In seven of the eight papers, timeliness was calculated as the median reporting delay between the date of disease occurrence (e.g., disease onset date, diagnosis date, or laboratory result date) and the date the public health system was notified or as the proportion of cases reported to the public health system in a specific time interval. In one study [10], epidemic curves were compared for two influenza surveillance systems and timeliness was assessed as the time interval between the epidemic peaks noted in each system. In addition, two studies described the factors associated with delayed reporting [13,15]. Seven of the eight studies addressed whether the calculated timeliness measure met the needs of the surveillance process being evaluated [10,12-17]. Measured timeliness was compared with recommended reporting timeliness in two papers – a national recommendation for local tuberculosis reporting timeliness [13] and a state mandate for reporting meningococcal disease cases to local public health [12]. The adequacy of the timeliness measure for the surveillance purpose was also assessed in other ways: 1) by comparing the timeliness of the same surveillance interval in an AIDS surveillance system before and after a major revision in the AIDS surveillance case definition [17], 2) by comparing the timeliness of the same surveillance interval across an active and a passive AIDS surveillance system [14], 3) by comparing outbreak detection abilities of an existing sentinel health care provider-based surveillance system for influenza-like illness with a new school-based system monitoring illness absenteeism [10], 4) by assessing whether reporting timeliness for Neisseria meningitidis and Haemophilus influenzae was adequate to initiate a rapid public health response [16], and 5) by comparing the timeliness of reporting by whether the case-patient's initial AIDS-defining condition was included in the 1997 or 1993 AIDS surveillance case definition [15]. The reporting timeliness of AIDS and bacterial meningitis (including meningococcal disease) surveillance systems were more frequently assessed than those for other infectious diseases. The AIDS reporting timeliness studies indicate that local and national AIDS reporting timeliness meets the goals of the AIDS surveillance systems monitoring trends, targeting prevention programs, estimating needs for medical and social services, and allocating resources [14,15,17]. Timeliness of AIDS surveillance improved after the revision of the AIDS surveillance case definition in 1993 [14,15,17]. Evaluation of Tennessee's Neisseria meningitidis infection surveillance system for 1989–1992 indicated that the lengthy reporting interval limited the usefulness of the system for supporting rapid response for control and prevention [16]. In contrast, a 1991 evaluation of New York State's meningococcal surveillance system indicated that the majority of cases (66%) were being reported within the recommended time frame (i.e., within one day of the diagnosis to ensure chemoprophylaxis for exposed persons) and therefore, supported prevention and control efforts [12]. In addition, on the basis of nationally notifiable infectious disease data from 1987, bacterial meningitis had the shortest reporting timeliness (median 20 days) of the other infectious diseases studied [11]. The definition of reference dates used in the timeliness evaluations varied. The initial date associated with the case varied among date of disease onset, date of diagnosis, and date of positive culture result. The ending date for the timeliness studies evaluated was the date the case report was received by the public health system, whether at the local, state, or national level. This time period corresponds to the sum of Intervals 1 and 2 or Interval 2 alone for local or state timeliness studies (Figure 1). For national evaluations of timeliness, the time period assessed was the sum of Intervals 1, 2, 3, and 4 or only Intervals 2, 3, and 4 (with or without inclusion of Intervals 5, 6, 7, and 8, dependent upon state protocol). NNDSS timeliness For MMWR years 1999–2001, a total of 9,276 cases of cryptosporidiosis, 12,332 cases of E. coli O157:H7 infection, 41,058 cases of hepatitis A virus acute infection, 7,090 cases of meningococcal disease, 22,735 cases of pertussis, 120,688 cases of salmonellosis, and 60,693 cases of shigellosis and were reported to NNDSS. Of those, 7,079 (76.3%) cryptosporidiosis case reports, 9,674 (78.4%) case reports of E. coli O157:H7 infection, 32,953 (80.3%) case reports of acute hepatitis A virus infection, 5,580 (78.7%) case reports of meningococcal disease, 19,904 (87.5%) case reports of pertussis, 84,746 (70.2%) case reports of salmonellosis, and 41,643 (68.6%) case reports of shigellosis were eligible for analysis. A total of 72,293 (26.4%) case reports were excluded for one or more of the following reasons: reported as a summary or aggregate record in which individual cases may have different event dates (20,194 cases), unknown or missing date types (20,019 cases), date type coded to MMWR report date (11,851 cases), and calculated reporting lag had a value of zero (indicating the event date and midpoint of the MMWR week matched) or had a negative value (indicating the event date was later than the mid-point of the MMWR week [67,557 cases]). Timeliness of reporting varied by disease and date type (Table 3). For cases reported with a disease onset date, the median reporting delay across all reporting states varied from 12 days for meningococcal disease to 40 days for pertussis. For cases reported with a laboratory result date, median reporting delay varied from 10 days for both meningococcal disease and shigellosis to 19 days for pertussis. There was also substantial variation in state-specific median reporting delays for each disease (Table 3). For example, for meningococcal disease cases reported with a laboratory result date, state-specific median reporting delay varied from a median of 2 days in one state to 117 days in another. Table 3 Timeliness of reporting of selected nationally notifiable infectious diseases, by date type, NNDSS, 1999–2001 Date type (Intervals from Figure 1) Disease (incubation period*), Characteristic Disease onset (Intervals 1,2,3,4) Diagnosis date (Intervals #2,3,4) Lab result date (Intervals #2,3,4) Date of first report to the community health system (Intervals #3,4) Cryptosporidiosis (7 day incubation period) Median time interval (days) 22 14 13 26 State-specific reporting rangea 2–149 1–73 2–58 1–53 No. cases 4,130 956 1,825 168 No. states 44 24 41 15 % within 1, 2 incubation periodsb 24%, 39% 37%, 50% 35%, 54% 19%, 33% E. Coli O157:H7 (4 day incubation period) Median time interval (days) 17 21 11 15 State-specific reporting rangea 2–81 2–41 1–53 1–49 No. cases 6,891 473 2,206 104 No. states 48 22 39 14 % within 1, 2 incubation periodsb 15%, 27% 13%, 25% 19%, 39% 21%, 33% Hepatitis A, acute (30 day incubation period) Median time interval (days) 23 18 12 12 State-specific reporting rangea 2–54 2–80 2–29,231+ 1–126 No. cases 21,570 4,394 6,695 294 No. states 49 36 39 14 % within 1, 2 incubation periodsb 62%, 84% 67%, 83% 82%, 94% 79%, 91% Meningococcal disease (4 day incubation period) Median time interval (days) 12 13 10 10 State-specific reporting rangea 2–56 1–54 2–117 4–62 No. cases 3,804 450 1,255 71 No. states 50 30 39 7 % within 1, 2 incubation periodsb 23%, 39% 26%, 40% 25%, 44% 31%, 42% Pertussis (20 day incubation period) Median time interval (days) 40 31 19 23 State-specific reporting rangea 2–124 1–106 2–190 2–48 No. cases 18,750 289 758 107 No. states 50 26 34 15 % within 1, 2 incubation periodsb 24%, 50% 34%, 60% 53%, 78% 45%, 68% Salmonellosis (1.5 day incubation period) Median time interval (days) 17 7 12 16 State-specific reporting rangea 2–44 1–54 2–61 1–27 No. cases 49,659 5,558 28,172 1,357 No. states 47 35 42 28 % within 1, 2 incubation periodsb 4%, 13% 17%, 43% 6%, 17% 7%, 19% Shigellosis (3 day incubation period) Median time interval (days) 15 10 10 9 State-specific reporting rangea 2–43 1–51 2–34 1–26 No. cases 26,635 2,850 11,603 555 No. states 46 28 41 17 % within 1, 2 incubation periodsb 15%, 22% 33%, 39% 22%, 35% 29%, 41% *Source: Control of Communicable Diseases Manual 17th Edition [8]. +The maximum state-specific median reporting delay for this disease and date type is from a state that reported 19 cases having event years 1919 or 1920. Excluding these cases as data entry errors, the maximum state-specific median reporting delay is 78 days. aState-specific median reporting range (minimum, maximum) in days b% of cases reported within 1 and 2 incubation periods, respectively For the same date type, NNDSS diseases with longest incubation periods tended to have a higher percentage of cases reported within one or two incubation periods than NNDSS diseases with shorter incubation periods (Table 3). For example, for acute hepatitis A virus infection, which had the longest incubation period of all the study diseases, more than 60% of cases were reported within one incubation period, for each date type reported. For all other diseases except pertussis, less than 40% of cases were reported within one incubation period for each reported date type. For pertussis, the percentage of cases reported within one incubation period varied from 24% for reports with disease onset date to 53% for case reports with laboratory result dates. In addition, state-specific percentage of cases reported within one or two incubation periods varied for a given disease and date type (data not shown). Comparison of NNDSS timeliness and literature review results The 1999–2001 NNDSS meningococcal disease median reporting interval between date of disease onset and date of report to CDC in this study was 8 days shorter than a previous study reported [11] using 1987 notifiable disease data for bacterial meningitis (median 20 days); and, the meningococcal disease median reporting delay was 9 days shorter in this study than in a previous study [16] using Tennessee's data for the years 1989–1992 for Neisseria meningitidis infection (median 21 days). In addition, the median reporting delay between disease onset and the date of report to CDC was shorter in this study than in a previous study (which used 1987 notifiable disease data) by 10 days for hepatitis A, 5 days for salmonellosis, and 8 days for shigellosis [11]. Discussion Few published studies evaluating surveillance systems presented timeliness measures. When timeliness was evaluated, standard methods were not used. Information collected by public health surveillance systems should support the quantitative assessment of timeliness by various steps in the pubic health surveillance process. Public health programs should periodically assess timeliness of specific steps in the surveillance system process to ensure that the objectives of the surveillance system are being met. A more structured approach to describing timeliness studies should be considered. Published papers describing local or state surveillance system reporting timeliness generally do not explicitly describe the surveillance system processes contributing to the timeliness measure, such as processing and analyzing the data or implementing a public health action before data are reported from a state to CDC. To facilitate future comparisons of reporting timeliness across jurisdictions, studies should include an explicit description of the public health surveillance reporting process and the surveillance process interval being measured. Additionally, surveillance information systems must support the collection of appropriate reference dates to allow the assessment of the timeliness of specific surveillance processes. A more structured approach to describing timeliness studies could include a description of the following characteristics: 1) the level of the public health system being assessed (e.g., local, state, or national), 2) the purpose of the surveillance evaluation, 3) goals of the surveillance system, 4) the surveillance interval being measured and a description of the reference dates that define the upper and lower boundaries of the surveillance interval, 5) the surveillance steps (processes or activities) that contribute to the surveillance interval being measured, 6) whether the measured timeliness met the needs of the surveillance step being evaluated, and 7) whether the timeliness met the goals of the surveillance system. No single timeliness measure will achieve the purpose of all evaluations or meet all the goals of the surveillance system. In addition, if the goal of the surveillance evaluation is to identify ways to improve timeliness, the analysis should identify factors associated with delayed reporting, such as the role of specific case ascertainment sources. The 1999–2001 national notifiable diseases data were timely enough to support the following surveillance objectives: monitoring trends over time, informing allocation of public health resources, monitoring the effectiveness of disease control, identifying high risk populations, and testing hypotheses. If NNDSS data are to be used to support timely identification of and response to multistate outbreaks at the national level, the timeliness of reporting needs to be enhanced for all diseases, but especially for diseases with the shortest incubation periods (e.g., cryptosporidiosis, E. coli O157:H7, meningococcal disease, salmonellosis, and shigellosis). Until reporting timeliness is enhanced, the application of aberration detection analytic methods to NNDSS data to aid in the identification of changes in disease reporting that may indicate a multistate outbreak in time to alert states for the purposes of disease control and prevention may be of limited use. Future work to improve reporting timeliness will need to address the substantial variation across states. As states enhance their reporting mechanisms with the use of automated electronic laboratory reporting systems [18], there may be less variation in state-specific reporting timeliness, but this should be assessed. NNDSS timeliness improved compared to timeliness of notifiable infectious diseases measured in previous reports [11,16]. However, the methods or variables used in these analyses were different. A few factors may have contributed to improvements in timeliness seen in this study. Since 1992, states have been routinely transmitting electronic case-specific records intended to improve reporting procedures and protocols. In addition, the use of automated electronic laboratory reporting to enhance infectious disease case reporting may have contributed to increased timeliness. Our study findings are subject to several limitations. The variables available for assessing NNDSS reporting timeliness are based on the MMWR week numbers that are assigned by states and the earliest known date reported in association with the case. While these variables might provide an estimate of national reporting timeliness, NNDSS data do not include a fixed date defining when a case report was initially transmitted to CDC or received at CDC, which would provide a more precise measure of national reporting timeliness. NNDSS data management protocols should be modified to permit direct calculation of national reporting timeliness. If the ability to support outbreak detection at the national level using NNDSS data is generally viewed as an important and sustainable enhancement for the NNDSS, states and CDC programs should facilitate reporting that more closely approximates real-time and define reporting protocols and data requirements to ensure that reporting timeliness can be improved and accurately monitored. The current NNDSS practice of weekly reporting and data processing limits reporting timeliness to CDC. Lastly, 72,293 (26.4%) cases were excluded from our analysis because the information contained in the database would not permit calculation of timeliness and this exclusion may have resulted in our study results either falsely overestimating or underestimating the magnitude of NNDSS reporting lags. The reporting timeliness variations across states may result from different reporting protocols in the states (e.g., centralized versus distributed reporting within the state's public health system) or from variations in how states assign MMWR week numbers. Other factors that might have contributed to reporting delay in our study included: the patient's recognition of symptoms; the patient's acquisition of medical care; the use of confirmatory laboratory testing; reporting by the health care provider or the laboratory to the local, county, or state public health authority; the volume of cases identified in the state; case follow-up investigations to verify the case report or to collect additional case information; periods of decreased surveillance system activity due to variable staffing levels; computer system down-time for maintenance, upgrades, or new application development; and data processing routines, such as data validation or error checking. Following a structured approach to evaluation of timeliness by specifying the surveillance objectives and the process(es) being measured may allow better definition of the factors that contribute to reporting delay. It was beyond the scope of this study to assess how these factors contribute to NNDSS reporting timeliness. In addition to reporting timeliness, other surveillance system attributes are important to assess (e.g., completeness of reporting). Completeness of notifiable infectious diseases reporting in the United States varies from 9% to 99% [7]. Six of the eight papers reviewed for this study assessed completeness of reporting [12-17]. One paper [14] noted that although the timeliness of the AIDS passive and active surveillance systems were comparable, the completeness of the active AIDS reporting system far exceeded the reporting completeness for the passive system. This highlights the importance of evaluating completeness and timeliness and other surveillance system attributes concurrently, before contemplating any changes to a surveillance system based on the assessment of a single attribute. To improve public health surveillance infrastructure and performance in the United States, CDC and local and state health agencies are integrating a number of public health surveillance systems monitoring infectious diseases in the United States, including the NNDSS, into the National Electronic Disease Surveillance System (NEDSS) [19,20]. NEDSS outlines a standards-based approach to disease surveillance and intends to connect public health surveillance to the clinical information systems infrastructure. As a result, NEDSS promises to improve the accuracy, completeness, and timeliness of disease reporting to state and local health departments and CDC. Conclusions To facilitate comparisons of surveillance system timeliness studies across jurisdictions or health conditions, a more standardized approach to describing timeliness studies is warranted. Public health surveillance systems should ensure that timeliness can be measured for specific surveillance system processes and in the context of the goals of surveillance. In addition, when timeliness is being measured, it is important to be explicit about how it is being measured. Our analysis of NNDSS reporting timeliness suggests that current acute hepatitis A infection reporting timeliness may be sufficient to support a timely public health response in the event of a multistate outbreak. However, for the other conditions evaluated, the long reporting lag and the variability across states limits the usefulness of NNDSS data and aberration detection analysis of those data for identification of and response to multistate outbreaks. The NNDSS timeliness data presented in this paper represents a baseline against which timeliness can be measured in the future. Further study is needed to identify the major sources of reporting delay and to assess how NNDSS reporting timeliness may be improved for the timely detection of cases and disease clusters. Competing interests None declared. Author's contributions Both authors contributed equally to project conception and write-up of the manuscript. RAJ was responsible for data analysis. Both authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here: Supplementary Material Additional File 1 Published reports quantitatively measuring timeliness of reporting infectious disease surveillance data. Table summarizes the findings of the review of published literature about quantitative measurements of infectious disease surveillance system timeliness Click here for file Acknowledgements We wish to acknowledge the health departments from the 50 U.S. States, New York City, and Washington DC that collect nationally notifiable infectious disease data from various case ascertainment sources and voluntarily report these data to CDC. ==== Refs Thacker SB Berkelman RL Public health surveillance in the United States Epidemiol Rev 1988 10 164 190 3066626 Thacker SB Teutsch SM, Churchill RE Historical development In Principles and Practice of Public Health Surveillance 2000 New York: Oxford University Press, Inc 1 16 Centers for Disease Control and Prevention Updated guidelines for evaluating public health surveillance systems: Recommendations from the Guidelines Working Group MMWR 2001 50 1 35 Centers for Disease Control Guidelines for evaluating surveillance systems MMWR 1988 37 1 18 Koo D Wetterhall SF History and current status of the National Notifiable Diseases Surveillance System Journal of Public Health Manag Pract 1996 2 4 10 Centers for Disease Control and Prevention Summary of Notifiable Diseases – United States, 2001 MMWR 2001 50 i 108 Doyle TJ Glynn MK Groseclose SL Completeness of notifiable infectious disease reporting in the United States: An analytical literature review Am J Epidemiol 2002 155 866 874 11978592 10.1093/aje/155.9.866 James Chin Control of Communicable Diseases Manual 2000 17th Washington DC: American Public Health Association Centers for Disease Control and Prevention Nationally notifiable infectious diseases event (disease or condition) code list with print criteria 2004 Accessed 07/04 Lenaway DD Ambler A Evaluation of a school-based influenza surveillance system Public Health Rep 1995 110 333 337 7610226 Birkhead G Chorba TL Root S Klaucke DN Gibbs NJ Timeliness of national reporting of communicable diseases: The experience of the National Electronic Telecommunications System for Surveillance Am J Public Health 1991 81 1313 1315 1928531 Ackman DM Birkhead G Flynn M Assessment of surveillance for meningococcal disease in New York State, 1991 Am J Epidemiol 1996 144 78 82 8659488 Curtis AB McCray E McKenna M Onorato IM Completeness and timeliness of tuberculosis case reporting: A multistate study Am J Prev Med 2001 20 108 112 11165451 10.1016/S0749-3797(00)00284-1 Hsu L Schwarcz S Katz M Comparison of simultaneous active and passive AIDS case reporting in San Francisco [Letters To The Editor] J Acquir Immune Defic Syndr 2000 23 204 10737437 Schwarcz SK Hsu LC Parisi MK Katz MH The impact of the 1993 AIDS case definition on the completeness and timeliness of AIDS surveillance AIDS 1999 13 1109 1114 10397542 10.1097/00002030-199906180-00015 Standaert SM Lefkowitz LB Horan JM Hutcheson RH Shaffner W The reporting of communicable diseases: A controlled study of Neisseria meningitidis and Haemophilus influenzae infections Clin Infect Dis 1995 20 30 36 7727666 Klevens RM Fleming PL Li J Gaines CG Gallagher K Schwarcz S Karon JM Ward JW The completeness, validity, and timeliness of AIDS surveillance data Annals of Epidemiol 2001 11 443 449 10.1016/S1047-2797(01)00256-3 Effler P Ching-Lee M Bogard A Ieong MC Nekomoto T Jernigan D Statewide system of electronic notifiable disease reporting from clinical laboratories: Comparing automated reporting with conventional methods [erratum appears in JAMA 2000 Jun 14;283(22):2937] JAMA 1999 282 1845 1850 10573276 10.1001/jama.282.19.1845 Centers for Disease Control and Prevention National Electronic Disease Surveillance System (NEDSS) 2003 Accessed 07/04 National Electronic Disease Surveillance Systems Working Group National Electronic Disease Surveillance System (NEDSS): A standards-based approach to connecting public health and clinical medicine Journal of Public Health Manag Pract 2001 7 43 50

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==== Front BMC Public HealthBMC Public Health1471-2458BioMed Central London 1471-2458-4-311528386910.1186/1471-2458-4-31Research ArticleThe usefulness of the Korean version of modified Mini-Mental State Examination (K-mMMSE) for dementia screening in community dwelling elderly people Jeong Seul-Ki 1dialogue@dreamwiz.comCho Ki-Hyun 2kcho@chonnam.ac.krKim Jae-Min 3jmkim@mail.chosun.ac.kr1 Department of Neurology, Seonam University School of Medicine, 120-1, Mareuk-dong, Seo-gu, Gwangju, South Korea2 Department of Neurology, Chonnam University School of Medicine, South Korea3 Department of Psychiatry, Chosun University School of Medicine, South Korea2004 30 7 2004 4 31 31 31 12 2003 30 7 2004 Copyright © 2004 Jeong et al; licensee BioMed Central Ltd.2004Jeong et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background We assessed whether the Korean version of modified Mini-Mental State Examination (K-mMMSE) has improved performance as a screening test for cognitive impairment or dementia in a general population compared with the Korean Mini-Mental State Examination (K-MMSE). Methods Screening interviews were conducted with people aged 65 and over in Noam-dong, Namwon-city, Jeonbuk province. There were 522 community participants, of whom 235 underwent clinical and neuropsychological examination for diagnosis of dementia and Cognitive Impairment No Dementia (CIND). Sensitivity, specificity and areas under the receiver operating characteristic (ROC) curves for the K-mMMSE and the K-MMSE were the main outcome measures. Results Cronbach's alpha for the K-mMMSE was 0.91, compared with 0.84 for the K-MMSE. The areas under the ROC curves in identifying all levels of CIND or dementia were 0.91 for the K-mMMSE and 0.89 for the K-MMSE (P < 0.05). For the K-mMMSE, the optimal cut-off score for a diagnosis of CIND was 69/70, which had a sensitivity of 0.86 and a specificity of 0.79, while, for a diagnosis of dementia, the optimal cut-off score of 59/60 had a sensitivity of 0.91 and a specificity of 0.78. The K-mMMSE also had a high test-retest reliability (r = 0.89). Conclusion Our findings indicate that the K-mMMSE is more reliable and valid than the K-MMSE as a cognitive screen in a population based study of dementia. Considering the test characteristics, the K-MMSE and modified version are expected to be optimally used in clinical and epidemiologic fields. ==== Body Background The Mini-Mental State Examination (MMSE) is a brief screening test that quantitatively assesses the cognitive status of elderly people [1,2]. It is easy to administer and has shown good reliability. Although its validity as a screening test is acceptable for clinical samples, it has been shown to have difficulty in discriminating between demented and non-demented individuals in community-based samples [2]. The MMSE has been found to be influenced largely by pre-morbid ability and is less sensitive to focal brain dysfunction [3] or mild dementia [4]. These limitations led to the development of the Modified Mini-Mental State Examination (3MS) in 1987 [5], which expanded the MMSE from 30 to 100 points to provide finer discrimination. In addition, the 3MS added four items: personal information, including date and place of birth; verbal fluency; abstract reasoning; and a second delayed recall trial. The 3MS also graded temporal orientation and broadened the delayed recall measures, which included cued and recognition formats. While retaining the brevity and ease of administration of the MMSE, the 3MS improved the validity and reliability of identifying individuals with dementia [6,7], and in predicting functional outcomes in patients with stroke [8]. In 2002, a group from the Cache County Study modified the 3MS for use as a cognitive screen in an epidemiologic study of dementia [9]. These modifications substituted the recall of personal demographic information with the recall of current and past prominent politicians. The main reason for this modification was the difficulty the researchers had in verifying personal demographic information. In addition, the scaling of the items in the time orientation and writing parts of the test was changed, and the time allotted for animal naming was shortened. This revised form of the 3MS (3MS-R) demonstrated good sensitivity in detecting dementia in a general population and providing age- and education-specific normative data and cut-off values at the 7th and 10th percentiles [9]. In Korea, the MMSE was translated into two versions, the Korean version of the Mini-Mental State Examination (MMSE-K) and the Korean Mini-Mental State Examination (K-MMSE) [10,11]. Both Korean versions of the MMSE were tested for validity and efficacy in clinical settings [11,12] and partly in epidemiologic research [13]. Both were somewhat modified to adjust better to the cultural background in Korea, but both shared all the limitations of the original MMSE. Recently the Korean Modified Mini-Mental State Examination (K-3MS) was introduced and validated in a clinical setting [14]. Although the K-3MS was found to be a reliable cognitive screening measure, there was no significant difference between the K-3MS and extracted MMSE for detecting individuals with dementia. In addition, components of the K-3MS could not be compared with items extracted from the K-MMSE and MMSE-K. We have therefore introduced the Korean version of modified Mini-Mental State Examination (K-mMMSE), and we have determined whether its validity is superior to that of the K-MMSE as a screen for cognitive impairment or dementia in a community setting. Methods Subjects Potential participants for this study were recruited from all inhabitants of Noam-dong, Namwon-city, Jeonbuk-province, South Korea, aged 65 and over in 2003, as recorded in national residents registration lists. The area surveyed covered 8.93 km2 and had an estimated population of 6,883, of whom about 7% were aged 65 or over. All participants gave informed consent, and the study was conducted in accordance with the guidelines in The Declaration of Helsinki and approved by the appropriate research ethics committee. Among the 522 eligible subjects aged 65 and over identified from registration lists, 235 (45%) completed clinical examinations after the interview and formed the study sample for principal analysis. Of the remaining subjects, we were unable to establish contact with 162 (31%), 75 (14%) refused to participate, 18 (3%) did not complete the survey, 7 (1%) had severe pre-morbid illness including blindness and deafness, 4 (0.8%) had changed address, and 3 (0.6%) had died before the visit. The principal apparent reason for the difficulties in establishing contact was that the person was in a regular daily activity or away from home, visiting family members living elsewhere. The 18 individuals (3%) who did not complete the survey questionnaire or were not examined clinically had a mean age of 74.9 ± 10.3 years; 13 (72%) were females, and 4 (22%) were educated. Of all the eligible subjects, participants and non-participants did not differ in age (73.5 ± 6.8 y vs. 74.6 ± 7.8 y, respectively) or gender (66% and 62%, all P values > 0.1). Assessment and measurements Interviewers received a seven-day training session on administering the screening instruments and were supervised throughout by the project neurologist. Cognitive status was classified in two stages. In the first stage, interviewers carried out home-based interviews for data on cognitive function, past medical history, and demographic characteristics. All participants were contacted for cognitive screening using a formulated battery, from which the K-mMMSE and K-MMSE were extracted. And they were rated by a knowledgeable informant using the Short form of Samsung Dementia Questionnaire (S-SDQ) and Korean Instrumental Activities of Daily Living (K-IADL) [15,16]. The S-SDQ is a Korean version of the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE), with 15 items and scores ranging from 0 to 30 [15]. The K-IADL is composed of 11 items that grade functional abilities, with scores calculated as the sum of points over the number of applicable questions and ranging from 0.0 to 3.0 [16]. High scores on the S-SDQ and K-IADL indicate poor performance. Both tests were found to be uncontaminated by pre-morbid ability, including education or age [15,16]. At the second interview, physicians who were blinded to the cognitive scores performed a clinical examination and neuropsychiatric inventory on participants who completed the first survey questionnaire. The clinical examination verified the presence of cognitive impairment. The diagnostic criteria for dementia were based on those of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) [17] and were subdivided according to the guidelines of the National Institutes of Neurological and Communicative Disorders and Stroke and the Alzheimer's disease and Related Disorders Association (NINCDS-ADRDA) [18]. Severity of dementia was staged using the Korean version of the Expanded Clinical Dementia Rating (CDR) scale [19]. The physician and neurologist made independent diagnoses and CDR scoring and subsequently held a case conference to reach a consensus diagnosis, classifying the person as either cognitively normal, cognitively impaired with no dementia (CIND), or having dementia. A diagnosis of CIND represents an attempt to classify people with recognizable cognitive decline who did not meet the criteria for dementia. This group included people who complained of cognitive decline and showed impaired memory function, but did not have any non-cognitive alterations, including intact activities of daily living. At both stages, home visits were repeated on at least two occasions if no contact was made. Instruments We translated the original 3MS-R into Korean according to the guidelines recommended by the modifiers [9]. The item regarding political figures, which asked the participants to name the current president, vice president, and state governors, was replaced with questions about current and previous presidents, because there is no vice president in the government of South Korea. We assessed temporal orientation according to three methods used to calculate year and time in Korea: the solar, lunar and Tangun era. We replaced the words "shirt," "nickel" and "honesty" in the memory task with the words "airplane," "pine tree" and "sincerity." In Korean, the first two words coincided with the K-MMSE items and ended with vowel sounds ("bee-haeng-gi," and "so-na-mu," respectively); while "seong-sil" in Korean, which means sincerity, was substituted for "jeong-jik," which is equivalent to the English word honesty, inasmuch as a pilot study found that "jeong-jik" was more difficult to hear or perceive than "seong-sil", possibly because the latter ended with a voiced sound and could be heard more comfortably. In explaining the appropriate questions and answers, we presented a simple example prior to asking the first question, specifically, "the eyes and nose are different, but they are similar in being part of our face." In a pilot study, most elderly subjects could not understand the concept of similarity without this example, and they became intolerant to our interview unless an example was provided. After providing the example, however, most subjects were more cooperative and tried to answer properly. We asked subjects to write a spontaneous sentence and scored whether it was legible and correct, with or without prompting. The total possible score was 100, and a K-MMSE score could be generated from it. Statistical analysis For demographic factors, mean or median values and proportions were calculated according to the cognitive impairment strata. Cronbach's alpha was used to quantify internal consistencies of the K-mMMSE and K-MMSE [20]. We assessed the stability and test-retest reliability with 30 subjects who took the K-mMMSE twice. Receiver operating characteristic (ROC) curves were used to determine the validity of the two screening tests graphically and statistically. The areas under the ROC curves (AUC) were calculated and described with standard errors (SE) using the trapezoidal rule [21], and comparison between AUCs was made by the algorithm with an estimated covariance matrix [22]. Cut-off points were chosen to optimize the trade-off between false-negative and false-positive rates. The choice of whether to judge the screening tests by their ability to identify CIND or dementia was addressed practically by assessing both. The validity of the K-mMMSE and K-MMSE were compared, first between those with CIND or dementia and those who were normal, and then between those with dementia and those with CIND or normal. All statistical calculations were performed using Stata 8.2 software (Stata, College Station, TX). Results Descriptive statistics Descriptive statistics are displayed in Table 1 for the total sample and according to the cognitive impairment strata. Of the 235 participants, 46 (19.6%) were classified as having dementia and 54 (22.9%) as having CIND. Overall levels of education were very low, in that 118 participants (50.2%) had no formal education, of whom 83 (70.3%) were illiterate. Severity of cognitive impairment was directly related to mean age and inversely related to number of years of education. Women had higher rates of being cognitively impaired or demented than men. The median scores on the K-mMMSE and K-MMSE decreased with severity of cognitive impairment. Median scores on the informant questionnaires of the S-SDQ and K-IADL increased with poorer cognitive status. The inter-quartile ranges (IQR) also steadily increased, reflecting increasing variability in cognitive and functional status. Four respondents scored perfectly on the K-MMSE, whereas none scored perfectly on the K-mMMSE, suggesting that the K-mMMSE might be less prone to the ceiling effect in this population. Table 1 Subject characteristics All subjects (n = 235) Normal (n = 135) CIND (n = 54) Dementia (n = 46) Demographic characteristics Age, mean ± SD, y 73.5 ± 6.7 71.9 ± 5.3 73.8 ± 7.4 77.8 ± 7.8 Women, % 66.4 57.8 74.1 82.6 Education, median (IQR), y 1 (0–6) 4 (0–6) 0 (0–5) 0 (0–2) Cognitive measures, median (IQR), score K-mMMSE 64 (48–80) 78 (66–85) 54 (44–63) 38 (29–47) K-MMSE 20 (14–25) 24 (20–27) 16 (13–21) 12 (9–15) S-SDQ 9 (5–13) 7 (3–10) 10 (5–14) 14 (10–21) K-IADL 0.22 (0.09–0.50) 0.11 (0.00–0.29) 0.27 (0.11–0.60) 1.10 (0.40–1.67) CIND; Cognitive Impairment No Dementia, SD; standard deviation, IQR; Inter-quartile range, K-mMMSE; Korean version of modified Mini-Mental State Examination, K-MMSE; Korean Mini-Mental State Examination, S-SDQ; Short form of the Samsung Dementia Questionnaire, K-IADL; Korean Instrumental Activities of Daily Living. Reliability The estimated Cronbach's alpha was 0.91 for the K-mMMSE and 0.84 for the K-MMSE. Relative to each cognitive impairment stratum (normal, CIND, and dementia), the alphas were 0.84, 0.81 and 0.81, respectively, on the K-mMMSE and 0.74, 0.72, and 0.63, respectively, on the K-MMSE. Neither age nor gender had any substantial impact on internal consistency. Stratum-specific alphas of the K-mMMSE for the different subgroups ranged from 0.86 to 0.91 in men and 0.89 to 0.90 in women. The retest of the K-mMMSE was assessed in 30 subjects (mean interval, 26 days; range, 19–32 days). The correlation coefficients for the total scores were 0.89 on the K-mMMSE and 0.85 on the K-MMSE. The coefficients of the 15 items of the K-mMMSE were all significant, ranging from 0.37 for similarities to 0.83 for time orientation. The re-tested subjects were representative of the entire study population, in that the sociodemographic characteristics of the 30 retested subjects were similar to the other participants in mean age (74.0 ± 7.4 y vs. 73.5 ± 6.7 y), educational years (3.5 ± 3.2 y vs. 3.4 ± 3.9 y), K-mMMSE scores (63.8 ± 21.0 vs. 63.1 ± 20.4), and proportion of women (80.0% vs. 66.4%; P = 0.132). Validity of the K-mMMSE and K-MMSE Construct validity Construct validity data between the K-mMMSE and other cognitive or functional measures are shown in Table 2. K-mMMSE was found to be significantly correlated with all measures, including CDR, Sum of Boxes of CDR (CDR-SB), and informant questionnaires such as the S-SDQ and K-IADL. The correlation coefficient between K-mMMSE and K-MMSE scores was 0.94. According to the CDR scores, the median values of the K-mMMSE and K-MMSE changed significantly (Table 3). Table 2 Correlations between K-mMMSE, K-MMSE and cognitive or functional measures (CDR, KIADL, and S-SDQ) K-mMMSE K-MMSE CDR CDR-SB KIADL S-SDQ K-mMMSE 1.000 K-MMSE 0.945* 1.000 CDR -0.755* -0.710* 1.000 CDR-SB -0.750* -0.702* 0.966* 1.000 KIADL -0.648* -0.614* 0.740* 0.793* 1.000 S-SDQ -0.489* -0.454* 0.529* 0.555* 0.617* 1.000 * P < 0.001 by Pearson's correlation analyses. K-mMMSE; Korean version of modified Mini-Mental State Examination, K-MMSE; Korean Mini-Mental State Examination, CDR; Clinical Dementia Rating, CDR-SB; Sum of Boxes of CDR, K-IADL; Korean Instrumental Activities of Daily Living, S-SDQ; Short form of the Samsung Dementia Questionnaire Table 3 K-mMMSE and K-MMSE scores for each CDR group CDR 0 (n = 137) 0.5 (n = 52) 1 (n = 33) 2+ (n = 13) K-mMMSE, Median (IQR)* 78 (66–85) 54 (44–63) 44 (35–50) 29 (12–31) K-MMSE, Median (IQR)* 24 (20–27) 16 (13–21) 12 (9–16) 10 (5–11) * P < 0.001 by Kruskal-Wallis test. K-mMMSE; Korean version of modified Mini-Mental State Examination, K-MMSE; Korean Mini-Mental State Examination, CDR; Clinical Dementia Rating, IQR; Inter-quartile ranges. Identification of combined CIND and dementia The performance of the K-mMMSE (AUC ± SE, 0.91 ± 0.02) was significantly superior to that of the K-MMSE (0.89 ± 0.02; P = 0.041). The ROC curves plotted in the same graph suggested that the performance of the K-mMMSE was superior to that of the K-MMSE at almost all cut-off points (Figure 1). At a cut-off of 69/70 for CIND, the K-mMMSE had a sensitivity of 0.86 (95% Confidence Intervals, 0.78–0.92), a specificity of 0.79 (0.71–0.86), a positive likelihood ratio (LR) of 4.15, and a negative LR of 0.18. In comparison, at a cut-off of 20/21 for CIND, the K-MMSE had a sensitivity of 0.82 (0.73–0.89), a specificity of 0.79 (0.71–0.86), a positive LR of 3.95 and a negative LR of 0.23. Figure 1 Receiver operating characteristic (ROC) curves of the K-mMMSE and the K-MMSE for combined CIND and dementia. K-mMMSE (light blue), K-MMSE (brown), and diagonal line. Area under ROC Curves (AUC): K-mMMSE = 0.91, K-MMSE = 0.89. Identification of dementia Both the K-mMMSE and the K-MMSE could properly discriminate demented from normal individuals, but there was no significant difference between them (AUC, 0.92 vs 0.91; P = NS). At the cut-off of 59/60, the K-mMMSE had a sensitivity of 0.91 (0.79–0.98), a specificity of 0.78 (0.72–0.84), a positive LR of 4.21 and a negative LR of 0.11. At a cut-off point of 18/19, the K-MMSE had a sensitivity of 0.91 (0.79–0.98), a specificity of 0.76 (0.69–0.82), a positive LR of 3.82 and a negative LR of 0.11. Discussion We have shown here that the K-mMMSE is a valid, reliable, and stable cognitive screening instrument, as well as being more sensitive to all levels of CIND and dementia, compared to the K-MMSE. The K-mMMSE has been shown to have a broader spectrum of cognitive domains, including political figures, word fluency, similarities, and delayed recall. Furthermore, the expanded 100 point scoring allows finer discrimination of cognitive impairment. Thus, the K-mMMSE represents a summary form of administration and scoring. Internal consistency results of the K-mMMSE and K-MMSE were comparable to those observed in previous community studies. Cronbach's alpha (á) for the 3MS has been reported to be 0.91 in a community study, a value identical to that found here [23]. Another population study has reported alphas for the 3MS and MMSE of 0.87 and 0.78, respectively, which were slightly lower than our findings of 0.91 and 0.84 [6]. Cronbach's alpha has been reported to be influenced by educational status or variability of response, in that it was higher in groups having fewer years of education [24] and in clinical populations having greater variability [25]. Our population consisted of a high percentage with no formal education (50.2%), and their scores were very variable (inter-quartile ranges for the K-mMMSE and the K-MMSE of 48–80 and 14–25, respectively). Test-retest reliability results of the K-mMMSE were also comparable to those in previous studies. Correlation coefficients of 0.91 to 0.93 have been reported for small samples of community dwelling residents and dementia patients, which are slightly higher than our value of 0.89 [26]. The Stirling County Study found a coefficient of 0.78, but items requiring less judgment exhibited lower reliability than items requiring more judgment [23]. In contrast, we found markedly lower reliability in items requiring more judgment, i.e., similarities (r = 0.37), compared with simple items, i.e., temporal orientation (r = 0.81). The discrepancy might be due to a difference of time lag, in that the Stirling County Study retest was performed over a 3 year interval, with individual retests ranging from 0.9 to 4.0 years. Furthermore their retested subjects were not representative of all participants. We observed a correlation coefficient of 0.85 for the K-MMSE over all levels of cognitive status, which is in line with generally acceptable findings [2]. Scores on the K-mMMSE and K-MMSE increased after retest, with differences in mean values of 4.4 and 2.6 points, respectively, presumably due to a practice or studying effect after a short interval [1,27,28]. The K-mMMSE was superior to the K-MMSE for diagnosis of all levels of CIND or dementia, as well as being slightly superior at almost all cut-off points. Since dementia is usually preceded by CIND or mild cognitive impairment (MCI), the definition of both requires explication [29,30]. Subjects with CIND or MCI have been found to be at increased risk for developing dementia or, more specifically, Alzheimer's disease and some vascular subtypes of dementia [30,31]. The difference between the K-mMMSE and the K-MMSE in diagnosing this condition might mean that the former was more sensitive to the mild stage or pre-dementia than the latter. In this respect, the K-mMMSE seemed to partially overcome a weakness of the K-MMSE, that is, insensitivity to mild dementia [4]. The present findings suggested that the K-MMSE was actually a fairly reasonable instrument as well. Given the faster administration of the K-MMSE, it would be a choice of clinicians to use optimally, recognizing that the K-MMSE was slightly inferior in terms of its test characteristics. The two cognitive screening measures did not differ significantly, however, in the detection of dementia. These results are comparable to the findings of McDowell et al. [6]; however, their validity results differed between the two language groups studied, namely French and English speakers. The 3MS was superior only in the diagnosis of combined CIND or dementia in French, but not English, speaking participants. There were fewer French than English participants (434 vs. 1166), and they had fewer years of education (6.8 vs. 9.2 years). These differences were also observed in our study samples, with the most important being the smaller sample size, inasmuch as statistical significance was directly influenced by the total number of participants [22]. Even Cache County modifications to the 3MS showed a good sensitivity and specificity, 3MS-R was also dependent on their cultural and social factors which might limit general use in non-US population [9]. For this reason, cross validation was a very important step for a cultural validation of the instrument. The K-mMMSE was shown to be more significantly correlated with other tests for cognitive status or functional abilities, such as the CDR, S-SDQ, and K-IADL, than was the K-MMSE. The correlation coefficients of the CDR were higher than the informant questionnaires, which might be due to the characteristics of the questions. That is, the K-mMMSE and K-MMSE are cognitive screening measures, and the CDR includes items about the cognitive aspects for scoring, whereas the informant questionnaires (S-SDQ and K-IADL) are comprised only of questions related to functional abilities. To the best of our knowledge, this is the first report showing concurrent validity of the modified MMSE series. There are important limitations to our findings. First, the subjects who participated in this study showed very low levels of educational background, perhaps limiting its general usefulness, especially regarding the cut-off points for a diagnosis of CIND or dementia. The low educational attainment, however, has been one of important characteristics of our elder population, because they were largely deprived of education due to Korean War and Japanese colonial dominion over the country [32]. And the study design, which showed the validities of and comparison between the two cognitive screening measures, would be appropriate for selected community samples, because all participants have a two-stage interview and a clinical examination, thus reducing verification bias. Second, although the trapezoidal rule provide a more accurate method of estimating the "true" AUC, an AUC derived from the parameters of a straight-line fit to the ROC plot tends to slightly underestimate the AUC of a Gaussian-based ROC. Finally, although we observed no significant differences between participants and non-participants, the rate of participation in our study was somewhat low. The majority of non-participants were those with whom we could not meet on two separate visits, suggesting that individuals who refused to participate may be more intelligent or active than the participants. If this were true, however, our results would not change, and additional statistical power may be added to our analysis. Conclusions We conclude that the K-mMMSE is a valid, stable, and reliable cognitive screen in an epidemiologic study. The K-mMMSE is more sensitive to all levels of CIND and dementia than the K-MMSE. Future investigations with the K-mMMSE will examine age-, sex-, and education-specific reference values to determine how performance patterns on individual items may discriminate between those with or without cognitive impairment and dementia subtypes. Competing interests None declared. Authors' contributions SKJ performed physical measurements, collected data, and drafted the manuscript. KHC participated in data collection and reviewed the manuscript. JMK conceived of the study and participated in its design, and also performed physical measurements. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here: Acknowledgements We thank Professors Seol-Heui Han, Jin-Sang Yoon, and Young-Hyun Kim for their valuable assistance in preparing the manuscript. ==== Refs Folstein MF Folstein SE McHugh PR "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician J Psychiatr Res 1975 12 189 198 1202204 10.1016/0022-3956(75)90026-6 Tombaugh TN McIntyre NJ The mini-mental state examination: a comprehensive review J Am Geriatr Soc 1992 40 922 935 1512391 Dick JP Guiloff RJ Stewart A Blackstock J Bielawska C Paul EA Marsden CD Mini-mental state examination in neurological patients J Neurol Neurosurg Psychiatry 1984 47 496 499 6736981 Feher EP Mahurin RK Doody RS Cooke N Sims J Pirozzolo FJ Establishing the limits of the Mini-Mental State. Examination of 'subtests' Arch Neurol 1992 49 87 92 1728269 Teng EL Chui HC The Modified Mini-Mental State (3MS) examination J Clin Psychiatry 1987 48 314 318 3611032 McDowell I Kristjansson B Hill GB Hebert R Community screening for dementia: the Mini Mental State Exam (MMSE) and Modified Mini-Mental State Exam (3MS) compared J Clin Epidemiol 1997 50 377 383 9179095 10.1016/S0895-4356(97)00060-7 Khachaturian AS Gallo JJ Breitner JC Performance characteristics of a two-stage dementia screen in a population sample J Clin Epidemiol 2000 53 531 540 10812327 10.1016/S0895-4356(99)00196-1 Grace J Nadler JD White DA Guilmette TJ Giuliano AJ Monsch AU Snow MG Folstein vs modified Mini-Mental State Examination in geriatric stroke. Stability, validity, and screening utility Arch Neurol 1995 52 477 484 7733842 Tschanz JT Welsh-Bohmer KA Plassman BL Norton MC Wyse BW Breitner JC An adaptation of the modified mini-mental state examination: analysis of demographic influences and normative data: the cache county study Neuropsychiatry Neuropsychol Behav Neurol 2002 15 28 38 11877549 Park JH Kwon YC Modification of the mini-mental state examination for use in the elderly in a non-western society: Part I. Development of Korean Version of Mini-Mental State Examination Int J Geriatr Psychiatry 1990 5 381 387 Kang YW Na DL Han SH A Validity study on the Korean Mini-Mental State Examination (K-MMSE) in dementia patients J Korean Neurol Assoc 1997 15 300 308 Park JH Park YN Ko HJ Modification of the Mini-Mental State Examination for use in the elderly in a non-western society: part II. Cutoff points and their diagnostic validities Int J Geriatr Psychiatry 1991 6 875 882 Kim JM Shin IS Yoon JS Kim JH Lee HY Cut-off score on MMSE-K for screening of dementia in community dwelling old people J Korean Geriatr Psychiatry 2001 5 163 168 Sohn EH Lee AY Park HJ The validity and reliability of the Korean Modified Mini-Mental State (K-3MS) Examination J Korean Neurol Assoc 2003 21 346 356 Choi SH Na DL Oh KM Park BJ A Short form of the Samsung Dementia Questionnaire (S-SDQ): development and cross-validation J Korean Neurol Assoc 1999 17 253 258 Kang SJ Choi SH Lee BH Kwon JC Na DL Han SH The reliability and validity of the Korean Instrumental Activities of Daily Living (K-IADL) J Korean Neurol Assoc 2002 20 8 14 Association American Psychiatric Diagnostic and Statistical Manual of Mental Disorders: DSM-IV 1994 Washington, American Psychiatric Association McKhann G Drachman D Folstein M Katzman R Price D Stadlan EM Clinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer's Disease Neurology 1984 34 939 944 6610841 Choi SH Na DL Lee BH Hahm DS Jeong JH Yoon SJ Yoo KH Ha CK Han IW Estimating the Validity of the Korean Version of Expanded Clinical Dementia Rating (CDR) Scale J Korean Neurol Assoc 2001 19 585 591 Cronbach LJ Coefficient alpha and the internal structure of tests Psychometrika 1951 16 297 334 Hanley JA McNeil BJ The meaning and use of the area under a receiver operating characteristic (ROC) curve Radiology 1982 143 29 36 7063747 DeLong ER DeLong DM Clarke-Pearson DL Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach Biometrics 1988 44 837 845 3203132 Bassuk SS Murphy JM Characteristics of the Modified Mini-Mental State Exam among elderly persons J Clin Epidemiol 2003 56 622 628 12921930 10.1016/S0895-4356(03)00111-2 Jorm AF Scott R Henderson AS Kay DW Educational level differences on the Mini-Mental State: the role of test bias Psychol Med 1988 18 727 731 3186871 Holzer CEIII Tischler GL Leaf PJ Greenley JR An epidemiologic assessment of cognitive impairment in a community population Research in Community Mental Health 1984 4 London England, JAI Press 3 32 Teng EL Chui HC Gong A Comparisons between the Mini-Mental State Exam (MMSE) and its modified version: the 3MS test International Psychogeriatric Association Psychogeriatrics: biomedical and social advances 1990 189 192 Keating H. J., 3rd "Studying" for the Mini-Mental Status Exam J Am Geriatr Soc 1987 35 594 595 3571811 Bravo G Hebert R Reliability of the Modified Mini-Mental State Examination in the context of a two-phase community prevalence study Neuroepidemiology 1997 16 141 148 9159769 Petersen RC Smith GE Waring SC Ivnik RJ Kokmen E Tangelos EG Aging, memory, and mild cognitive impairment Int Psychogeriatr 1997 9 Suppl 1 65 69 9447429 10.1017/S1041610297004717 Shah Y Tangalos EG Petersen RC Mild cognitive impairment. When is it a precursor to Alzheimer's disease? Geriatrics 2000 55 65 68 Meyer JS Xu G Thornby J Chowdhury MH Quach M Is mild cognitive impairment prodromal for vascular dementia like Alzheimer's disease? Stroke 2002 33 1981 1985 12154249 10.1161/01.STR.0000024432.34557.10 Lee JC Korea's health care policy of the twentieth century Uisahak 1999 8 137 145 12212608

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==== Front BMC Med EthicsBMC Medical Ethics1472-6939BioMed Central London 1472-6939-5-410.1186/1472-6939-5-4Research ArticleWestern medical ethics taught to junior medical students can cross cultural and linguistic boundaries Ypinazar Valmae A 1v.ypinazar@uq.edu.auMargolis Stephen A 2s.margolis@uq.edu.au1 School of Education, James Cook University, Townsville, Queensland, 4810, Australia2 Department of General Practice, Monash University, 867 Centre Road, East Bentleigh, Victoria, 3165, Australia2004 30 7 2004 5 4 4 14 5 2004 30 7 2004 Copyright © 2004 Ypinazar and Margolis; licensee BioMed Central Ltd.2004Ypinazar and Margolis; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background Little is known about teaching medical ethics across cultural and linguistic boundaries. This study examined two successive cohorts of first year medical students in a six year undergraduate MBBS program. Methods The objective was to investigate whether Arabic speaking students studying medicine in an Arabic country would be able to correctly identify some of the principles of Western medical ethical reasoning. This cohort study was conducted on first year students in a six-year undergraduate program studying medicine in English, their second language at a medical school in the Arabian Gulf. The ethics teaching was based on the four-principle approach (autonomy, beneficence, non-malfeasance and justice) and delivered by a non-Muslim native English speaker with no knowledge of the Arabic language. Although the course was respectful of Arabic culture and tradition, the content excluded an analysis of Islamic medical ethics and focused on Western ethical reasoning. Following two 45-minute interactive seminars, students in groups of 3 or 4 visited a primary health care centre for one morning, sitting in with an attending physician seeing his or her patients in Arabic. Each student submitted a personal report for summative assessment detailing the ethical issues they had observed. Results All 62 students enrolled in these courses participated. Each student acting independently was able to correctly identify a median number of 4 different medical ethical issues (range 2–9) and correctly identify and label accurately a median of 2 different medical ethical issues (range 2–7) There were no significant correlations between their English language skills or general academic ability and the number or accuracy of ethical issues identified. Conclusions This study has demonstrated that these students could identify medical ethical issues based on Western constructs, despite learning in English, their second language, being in the third week of their medical school experience and with minimal instruction. This result was independent of their academic and English language skills suggesting that ethical principles as espoused in the four principal approach may be common to the students' Islamic religious beliefs, allowing them to access complex medical ethical reasoning skills at an early stage in the medical curriculum. ==== Body Background Medical ethics has increasingly become a common component of the undergraduate curriculum at many medical schools, often within a defined humanities program [1-3]. In 1999, the European Federation of Internal Medicine, the American College of Physicians and the American Board of Internal Medicine launched the Medical Professionalism Project, which placed medical ethics at the centre of a charter of behaviour and attitudes for all physicians [4]. In 2003, the Liaison Committee on Medical Education in the USA identified the teaching of medical ethics as a core curriculum component of modern medical school education [5]. Medical ethics teaching can occur within the traditional model of medical education, where a separate program of clinical instruction follows several years of medical sciences [6]. However, there is some evidence to suggest that a vertically integrated learning model where the study of clinical subjects runs parallels to and is integrated with basic sciences may be more effective [7,8]. This has resulted in a trend towards including clinical experience in the early years of the medical school curriculum. There is increasing evidence that this enhances student attitudes towards patients [9], provides a structure for teaching integrated clinical medicine [10] and better prepares students for the clinical years [11]. Although Islam has a long tradition of ethical reasoning, there had been little impetus to establish courses in ethics within medical school curricula in the Arabian Gulf. The Faculty of Medicine and Health Sciences (FMHS) was almost alone in having done so, an initiative introduced by expatriate family physicians from New Zealand who had undertaken training in Western medical ethics. Ethics had been taught at the FMHS since 1997 in a vertically integrated program that spanned all levels of the curriculum, based on the four-principle approach developed by Beauchamp and Childress [12,13] as modified by Herbert; autonomy, beneficence, non-malfeasance and justice [14,15] (See Table 1). Although it was less than ideal to focus the medical ethics curriculum on an imported model, there was little support within the UAE University for a course centred on local culture and traditions. Table 1 Ethical Principles utilized in the teaching program Primary Principle Subsection principles 1. Autonomy a) Disclosure b) Truth telling c) Informed consent d) Competence e) Paternalism f) Confidentiality g) Decision-making 2. Beneficence 3. Non-malfeasance 4. Justice English has become the lingua franca of medicine, with most international medical societies, publications and meetings conducted in English [16,17]. This has encouraged the development of English language medical schools in countries where English is a second language, including the Arabian Gulf. There is a significant body of literature describing how people from different cultures utilise different approaches to the clinical application of medical ethics [18,19]. However, there is little information about teaching medical ethics across cultural and linguistic boundaries. Social anthropology has demonstrated that there is a strategic mixing of language with culture and that both culture and social systems are conceptualised in language [20,21]. This would suggest that students learning medicine in English, their second language, could experience dissonance between the content of their courses and the context of their everyday lives, especially in socially formulated issues such as medical ethics. The aim of this study was to investigate whether Arabic speaking students studying medicine in an Arabic country, albeit with the language of instruction being English, would be able to correctly identify some of the principles of Western medical ethical reasoning, a discipline that challenged significant cultural and linguistic boundaries. Methods Setting The FMHS at the United Arab Emirates (UAE) University offers a six-year undergraduate program in medicine. Students are admitted after a one-year post high school tertiary orientation year, which includes additional English language instruction. Although all students are citizens of the UAE, speaking Arabic as their first language, the course is conducted in English therefore students are required to meet an English language proficiency level in order to be accepted into the medical school. Faculty members come from across the globe, with approximately 1/3 with English as their first language, 1/3 with Arabic as their first language and 1/3 with a different primary language. All medical students participated in an introductory course in medical ethics, conducted in the first three weeks of first year and taught by a non-Muslim native English speaker from New Zealand with no knowledge of the Arabic language. Apart from his qualifications in Family Medicine, he had also undergone training in Western medical ethics. Although the course was respectful of Arabic culture and tradition, the content of the introductory course focused on Western medical ethical reasoning and excluded an analysis of Islamic medical ethics. Based on the principles of adult learning, the educational strategy focused on the use of real clinical encounters after minimal orientation, followed by an interactive debriefing session. Rather than provide a sound basis for ethical reasoning, the aim of the introductory course was to introduce the students to the central importance of ethical principles in medical practice, knowing that a more complete and integrated understanding would develop over the ensuing six years of the course. Following two 45-minute interactive seminars, students in groups of 3 or 4 visited a primary health care centre for one morning, sitting in with an attending physician seeing his or her patients. In the absence of any clinical understanding at this early point in their training, the students were encouraged to focus all their energies on medical ethics. Following the visit to the primary health care centre each student submitted a personal report for summative assessment in which they described the ethical situations they had observed and then provided an appropriate label according to the four-principal approach. Although the seminars were in held in English, the clinical sessions were conducted in Arabic. When questioned by the investigator (SM), the clinical staff stated they had never received formal instruction in medical ethics. The clinical staff were discouraged from indicating ethical issues to the students; the educational process was for the students to identify these on their own. Following submission of their personal report, a third seminar of the introductory course was held with the same teacher where students were invited to share and discuss their experiences. Sample This study examined two cohorts of first year students, 33 students from the 2002 – 2003 academic year and 29 students from the 2003 – 2004 academic year (i.e. all students enrolled in these courses). Each cohort experienced the same admission criteria, underwent the same curriculum, was taught ethics by the same native English-speaking teacher and utilised the same group of primary health care physicians. Analysis methodology Although both experienced educators and educational researchers, the investigators (VY and SM) did not teach medical ethics at this level of the curriculum. Each investigator coded all personal reports independently and any discrepancies were resolved by mutual agreement. A positive score for labelling any of the four principles and the subsets of autonomy was only allocated when the accompanying description corresponded with the label given. Merely listing a label was not coded as positive. As an indicator of general academic ability, the students' score on a multidisciplinary unit test held at the end of the fifth week of year one was also considered. The results of this test have been considered as a variable in the study to determine if there was a correlation between general academic ability and the students' competency in identifying ethical principals and to avoid associated bias. This multidisciplinary unit test covered all topics taught in the first 5 weeks including anatomy, chemistry, medical physics and medical ethics. The pass mark was set at 75%. The medical ethics component contributed 5% of the total mark. As not all students had the same clinical experience, each individual student may not have had the opportunity to observe the same range of ethical issues during their clinical experience. For example, some students may not have seen an example of competence to detail in their report. Hence, as this manuscript concerns each individual student's ability to report what he or she as an individual had observed in an experience not shared across the whole group, only numbers of ethical issues identified by individual students are reported rather than the total numbers of students per ethical issue. A third variable included was their score in a standardised test of English, the Test of English as a Foreign Language (TOEFL) [22], used in the selection process to enter medical school. Although initially designed as a measure of the English language proficiency of international students wishing to study at colleges and universities in the North America, this test was widely used in the Arabian Gulf. The TOEFL is a multiple-choice examination that measured listening, comprehension, vocabulary and reading [23]. This test measures the English language proficiency of non-native speakers of English and as such has relevance in the FMHS as the medical course there is taught in English. The nominal requirement at the FMHS is a minimum score of 500. As this test has a non-linear scoring system, this is substantially lower than the 550 – 580 required in Western universities in North America, Australasia and the UK. The Statistical Package for the Social Sciences was used for analysing the results [24]. Simple frequency analysis was used to describe demographics, TOEFL scores, unit test results and quantification of ethics issues. The correlation between the TOEFL score and Multidisciplinary Unit Test Score was assessed by Pearson's correlation coefficient as both variables were normally distributed and held a linear relationship. As the number of ethical issues identified was not distributed in a Gaussian fashion, frequency distributions were reported by median and range from minimum to maximum, while the appropriate non-parametric statistics were used: Mann-Whitney U test for comparisons between variables and Kendall's tau-b test for bivariate correlations. The level of statistical significance was defined as p < 0.05. The Research Ethics Committee of the United Arab Emirates University Faculty of Medicine and Health Sciences, which complies with the ethical rules for human experimentation that are stated in the Declaration of Helsinki, approved the project. Results All members of each class participated in this study. Participant demographics are detailed in Table 2. The age range was from 19–21 years; all were practicing Muslims and had Arabic as their first language. Table 2 Participant demographics, TOEFL score and test results Class Cohort 2002–2003 Cohort 2003–2004 Male Female Male Female n 13 20 11 18 TOEFL* score prior to entry to medical school 498 +/- 27.8 518 +/- 58.2 514.9 +/- 40.9 505.6 +/- 29.0 Multidisciplinary Unit Test Score [pass = 75%] 82.8 +/- 5.1 82.7 +/- 6.6 81.9 +/- 6.8 83.9 +/- 3.6 [All enrolled students in this course participated] * The Test of English as a Foreign Language The similarities of issues identified and described across the group of students who attended the same clinic were highly suggestive that the events described actually occurred. However, there were sufficient differences in identified principles, evidence provided and labels given, to indicate that reports were written independently. Table 3 details the ethical issues identified. Although the initial expectation was that there were only a limited number of ethical issues that could be identified in a single clinical session, each student acting independently was able to correctly identify a median number of 4 different medical ethical issues (range 2–9) and correctly identify and label accurately a median of 2 different medical ethical issues (range 2–7) There was no significant difference in results between males and females except for 'autonomy mislabelled as a different ethical issue' (male: median = 0, range= 0–2; female median = 0, range = 0–3; p = 0.002) and 'autonomy / confidentiality mislabelled as a different ethical issue' (male: all results = 0; female median = 0, range = 0 – 2; p = 0.03). Table 3 Analysis of Ethics assignments: the median and range from minimum to maximum of the number of issues identified by individual students as detailed in their personal report Median Range Total number of ethical issues identified: Labelled correctly 2 2 – 7 Mislabelled as a different ethical issue or subset of Autonomy not defined 2 3 – 9 [Labelled correctly] + [mislabelled] 4 2 – 9 Total number of issues identified as ethical which were not ethical issues 0 0–4 Total number of autonomy issues identified Labelled correctly 1 0–4 Labelled as Autonomy, no subsection specified 0 0–3 Mis-labelled as a different ethical issue 0 0–3 Total number of autonomy: disclosure issues identified Labelled correctly 0 0–1 Labelled as Autonomy, no subsection specified 0 0–1 Mis-labelled as a different ethical issue 0 0–1 Total number of autonomy: truth telling issues identified Labelled correctly 0 0–1 Labelled as Autonomy, no subsection specified 0 0–1 Mis-labelled as a different ethical issue 0 0 – 0 Total number of autonomy: informed consent issues identified Labelled correctly 0 0 – 2 Labelled as Autonomy, no subsection specified 0 0 – 1 Mis-labelled as a different ethical issue 0 0 – 1 Total number of autonomy: competence issues identified Labelled correctly 0 0 – 0 Labelled as Autonomy, no subsection specified 0 0 – 1 Mis-labelled as a different ethical issue 0 0 – 0 Total number of autonomy: paternalism issues identified Labelled correctly 0 0 – 1 Labelled as Autonomy, no subsection specified 0 0 – 1 Mis-labelled as a different ethical issue 0 0 – 1 Total number of autonomy: confidentiality issues identified Labelled correctly 0 0 – 1 Labelled as Autonomy, no subsection specified 0 0 – 1 Mis-labelled as a different ethical issue 0 0 – 2 Total number of autonomy: decision – making issues identified Labelled correctly 0 0 – 2 Labelled as Autonomy, no subsection specified 0 0 – 2 Mis-labelled as a different ethical issue 0 0 – 2 Total number of beneficence issues identified Labelled correctly 0 0 – 2 Mis-labelled as a different ethical issue 0 0 – 1 Total number of non-malfeasance issues identified Labelled correctly 0 0 – 2 Mis-labelled as a different ethical issue 0 0 – 3 Total number of justice issues identified Labelled correctly 0 0 – 1 Mis-labelled as a different ethical issue 0 0 – 2 The four cohorts of students displayed a wide range of TOEFL scores ranging from the low 400 s through the mid 600 s. There was a moderate correlation between the TOEFL score and the multidisciplinary unit test score (r = 0.616, p < 0.001). There was no statistically significant correlation between the TOEFL score and the number of ethical issues identified. There were weak statistically significant correlations between the multidisciplinary unit test scores and ethical issues identified for 'total number of issues correctly identified' (r = 0.26, p = 0.008) and 'number of autonomy issues correctly identified' (r = 0.21, p = 0.04). There were no other statistically significant correlations between test scores and ethical issues identified. Discussion This study has demonstrated that these first year students were able to identify medical ethical issues in a clinical setting after minimal instruction. Although introductory courses by their very nature aim to build on the students' previously accumulated knowledge, understanding and experience, especially the unstructured kind based on life experience, the students in this study were able to develop this skill with very minimal instruction, when compared to the normal length of introductory medical ethics courses [25]. Feldman et al found important differences in the ethical practices and beliefs of Internists in the USA and China, even amongst those practicing Western medicine and suggested that some basic bioethical principles may be culturally based rather than universal [26]. One important feature in this regard is the concept of autonomy, where more traditional or tribal based societies, such as is seen in the Arabian Gulf States, often view autonomy as relating to the group rather than the individual. Hence, students learning ethics that incorporate Western constructs and are delivered in a Western language may fail to see the relevance or appropriateness to their understanding of their culture and society. However, this study has demonstrated that the students were able to correctly identify the concept of autonomy and some of its sub groupings. Although the students in this study demonstrated that they were able to use an imported model of ethical principles, this study did not directly address whether the students embraced the underlying conceptual framework, as the educational objectives of the introductory course were primarily to arouse interest and discussion amongst the students. However, informal review of the performance in examination settings of earlier cohorts of students who underwent similar educational programs suggests that by the end of their pre-registration medical training students do internalise the concepts and appear to understand their clinical applications. Further studies could investigate the impact of ethical training on their eventual behaviour as independent clinicians. This study had an underlying a priori assumption that the students would not be successful in identifying ethical issues due to a combination of the brief nature of the introductory seminars, their relative youth and inexperience with the adult learning model and being at the beginning of their medical training. Hence, the relatively high number of issues identified and the acceptable accuracy in labelling suggests that these students did demonstrate a reasonable level of skill even in the absence of a control group to help validate this conclusion. With little research available on the impact of early education in medical ethics, further studies utilising a control group would prove beneficial to determine what issues students would have been able to identify with no training. With ethics and professionalism being globally recognised as an integral component of primary medical degree curriculum, the results of the project suggest that early exposure may be beneficial in that it would provide a solid base in ethics, an essential requirement for their later clinical training. If ethical principles are clearly established early in the students' training, all future clinical training can be considered from an ethical standpoint. Jackson found that corporate managers' ethical decision-making was more influenced by their home country than by the country in which they resided [27]. This suggests the overriding importance culture and tradition has on one's values and beliefs systems. Hence the absence of a correlation between English language ability, accuracy in identification of ethical issues and number of issues identified suggests that in this case the basic conceptualization of medical ethics transcended the possible values and beliefs systems implicit in teaching a Western ethical curriculum in the English language in this environment. A number of researchers have suggested that the four principles of Western medical ethics have always existed in Islam [28-30]. Islam has an ethical and moral tradition which is intimately linked to Qur'anic teachings [31]. While the students would be familiar with ethical principles as enshrined in their religious beliefs, the linguistic constructs and labels of Western medical ethics as outlined in the four principle approach would be unfamiliar to these students. Perhaps the ethical principles embedded in their religion enabled the students to juxtapose Western linguistic constructs onto the ethical events observed in the clinical situation. They demonstrated an ability to correctly identify, describe and label ethical events despite using new language constructs, given that English is their second language. The relative importance of the intervention compared to their background knowledge could be further addressed in an expanded study using a control group. This study found at best a weak correlation between general academic ability and the number and accuracy of ethics issues identified. This suggests that even academically weak students were able to grasp the concepts being taught. Perhaps this outcome was enhanced by two factors; utilizing an adult learning model where students worked together in groups (although assignments were individually prepared) undergoing real rather than simulated experiences and the incorporation of their Islamic religious beliefs and self developed ethical reasoning. The students in this study had a broad range of English language skills as suggested by the large range in TOEFL results. Although there is no clear evidence that TOEFL correlates with the ability to conceptualise theoretical constructs presented in English, there is strong evidence that TOEFL correlates with grade point average at a North American Universities [32,33], and some evidence it correlates with the degree of participation of UAE students in problem based learning sessions [34]. This study only addressed the ability of medical students at the onset of their medical training to assimilate and conceptualise the basic principles of ethical reasoning. In particular, no assessment was made of the long-term impact of this course on 'moral enculturation' as this study has only described one component of a longitudinal six-year course in medical ethics. Conclusions This study has demonstrated that these students could identify medical ethical issues based on Western constructs, despite learning in English, their second language, being in the third week of their medical school experience and with minimal instruction. This result was independent of their academic and English language skills suggesting that ethical principles as espoused in the four principal approach may be common to the students' Islamic religious beliefs, allowing them to access complex medical ethical reasoning skills at an early stage in the medical curriculum. Competing interests None declared. Authors' contributions SM conceived the study, prepared the ethics application, coded the student's material, analysed the results, prepared and reviewed the manuscript. VY prepared the ethics application, prepared the coding sheet, coded the student's material, analysed the results, prepared and reviewed the manuscript. 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==== Front BMC BiochemBMC Biochemistry1471-2091BioMed Central London 1471-2091-5-111527475110.1186/1471-2091-5-11Research ArticleCharacterization of yeast histone H3-specific type B histone acetyltransferases identifies an ADA2-independent Gcn5p activity Sklenar Amy R 1sklenar.39@osu.eduParthun Mark R 1parthun.1@osu.edu1 Department of Molecular and Cellular Biochemistry, College of Medicine and Public Health, The Ohio State University, Columbus, OH 43210, USA2004 26 7 2004 5 11 11 19 2 2004 26 7 2004 Copyright © 2004 Sklenar and Parthun; licensee BioMed Central Ltd.2004Sklenar and Parthun; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background The acetylation of the core histone NH2-terminal tails is catalyzed by histone acetyltransferases. Histone acetyltransferases can be classified into two distinct groups (type A and B) on the basis of cellular localization and substrate specificity. Type B histone acetyltransferases, originally defined as cytoplasmic enzymes that acetylate free histones, have been proposed to play a role in the assembly of chromatin through the acetylation of newly synthesized histones H3 and H4. To date, the only type B histone acetyltransferase activities identified are specific for histone H4. Results To better understand the role of histone acetylation in the assembly of chromatin structure, we have identified additional type B histone acetyltransferase activities specific for histone H3. One such activity, termed HatB3.1, acetylated histone H3 with a strong preference for free histones relative to chromatin substrates. Deletion of the GCN5 and ADA3 genes resulted in the loss of HatB3.1 activity while deletion of ADA2 had no effect. In addition, Gcn5p and Ada3p co-fractionated with partially purified HatB3.1 activity while Ada2p did not. Conclusions Yeast extracts contain several histone acetyltransferase activities that show a strong preference for free histone H3. One such activity, termed HatB3.1, appears to be a novel Gcn5p-containing complex which does not depend on the presence of Ada2p. ==== Body Background Histones H3 and H4 are among the most evolutionarily conserved proteins (>90% identity from yeast→humans) [1]. Octamers composed of one histone H3/H4 tetramer and two histone H2A/H2B dimers package 146 bp of DNA into the basic repeating subunit of chromatin, the nucleosome [1]. Hence, as fundamental components of chromatin, these proteins are an integral part of all cellular processes involving chromosomal DNA. The physical characteristics of the histones are precisely regulated in the cell by an elaborate network of post-translational modifications that include acetylation, methylation, phosphorylation, ubiquitination and ADP-ribosylation [2-4]. These modifications are found primarily on the NH2-terminal tails of the histones. These domains, which protrude from the core of the nucleosome, are free to interact with, and be acted upon by, the nuclear environment. The past several years has seen the identification of numerous enzymes that are capable of modifying the histones. These enzymes are generally found in large, multi-subunit complexes and have activities that are not only specific for a given histone but are specific for particular amino acid residues within the histone [5,6]. The most well characterized histone modifying enzymes are the histone acetyltransferases (HATs). HATs catalyze the transfer of an acetyl moiety from acetyl-coenzyme A to the ε-amino group of lysine residues in the histone NH2-terminal tails. Historically, these enzymes have been classified as either type A or type B, based upon substrate specificity and cellular localization [7]. Found in the nucleus, type A HATs utilize nucleosomal histones as substrates. A number of Type A HATs have been identified in yeast. These include Gcn5p (SAGA, ADA, SLIK, SALSA and HAT-A2 complexes), Sas2p (SAS complex), Sas3p (NuA3 complex), Esa1p (NuA4 and picNuA4 complexes) and Elp3 (Elongator complex) [8-22]. These enzymes have been characterized primarily in the context of transcriptional activation but are likely to be involved in other chromatin mediated events as well [23,24]. Type B HATs were initially described as cytoplasmic enzymes that acetylate free histones in conjunction with chromatin assembly [7]. The de novo assembly of chromatin is a complex, multi-step process that occurs most prominently during DNA replication (but also accompanies other cellular processes involving DNA synthesis) [25,26]. Following induction of histone mRNA synthesis, histone proteins are translated in the cytoplasm. For histones H3 and H4, synthesis is rapidly followed by the acetylation of specific lysine residues in their NH2-terminal tail domains [27]. For newly synthesized histone H4, this acetylation occurs on lysine residues at positions 5 and 12 in all eukaryotic organisms examined to date [28,29]. For newly synthesized histone H3, acetylation appears to occur in distinct patterns that can differ from organism to organism [28,30,31]. The acetylated H3 and H4 form tetramers that are translocated into the nucleus and loaded onto DNA [32]. Following completion of the histone octamer by histone H2A/H2B addition, mature chromatin is formed following the deacetylation of histones H3 and H4 [33,34]. In contrast to the type A HATs, only one type B HAT has been characterized to date, Hat1p. Hat1p is an evolutionarily conserved enzyme that specifically acetylates free histone H4 [35-38]. Consistent with its identification as a type B HAT, recombinant yeast Hat1p, as well the Xenopus and Human Hat1p homologs, acetylates both lysine 5 and lysine 12 [35-39]. Hat1p was originally purified from yeast cytoplasmic extracts in a complex with Hat2p, a yeast homolog of the mammalian Rbap46/48 proteins [36,40,41]. Subsequent studies have shown that yeast Hat1p, as well as its higher eukaryotic counterparts, can also localize to the nucleus [37,38,42]. These results suggest that, while specificity for free histones is a bona fide characteristic, cytoplasmic localization may not be a strict criterion for classification as a type B HAT. Evidence has accumulated indicating that the acetylation of newly synthesized histones H3 and H4 play over-lapping roles in chromatin assembly. While yeast strains carrying a deletion of either the H3 or H4 NH2-terminal tail are viable, concomitant deletion of both NH2-termini (or combining tail deletions with alterations in specific sites of acetylation) results in a defect in nucleosome assembly and cell death [43,44]. In addition, while deletion of the HAT1 gene produces no observable phenotype, combining a deletion of HAT1 with specific lys→arg mutations in the NH2-terminus of histone H3 generates defects in both telomeric silencing and DNA damage repair [45,46]. However, despite the importance of the acetylation of newly synthesized histone H3 in chromatin assembly, there have been no type B histone acetyltransferases described that specifically target histone H3. To identify potential histone H3-specific type B HATs, we have systematically surveyed yeast extracts for candidate activities. Here we detail one such activity, termed HatB3.1. We provide evidence that this is a novel complex that utilizes Gcn5p as its catalytic subunit. Intriguingly, unlike previously identified Gcn5p-containing HAT complexes, HatB3.1 contains Ada3p, but not Ada2p. Results Identification of histone H3-specific type B histone acetyltransferase activities in yeast The highly selective activity of the native Hat1p/Hat2p complex for free versus nucleosomal histone H4 is the primary characteristic that distinguishes this enzyme from the type A histone acetyltransferases [35,36]. Therefore, to identify putative histone H3-specific type B HAT complexes, we systematically surveyed yeast extracts for activities that acetylated free histone H3 but not histone H3 packaged into chromatin. Extracts were prepared from cell cultures grown to mid-log phase to enrich for actively dividing cells, as the most robust period of chromatin assembly occurs during DNA replication. Yeast cell walls were digested with zymolyase and cytosolic extracts were produced by the lysis of the cells in low salt buffer followed by centrifugation to remove nuclei and large cell debris. Hence, this extract contained soluble cytoplasmic proteins as well as proteins loosely associated with the nucleus. The nuclear extract was obtained by incubating the nuclear pellet in buffer containing 1.0 M NaCl to extract proteins that are more tightly associated with the nucleus. It is difficult to reliably detect histone acetyltransferase activities in the relatively crude cytosolic and nuclear extracts. Therefore, to evaluate the intrinsic HAT activities present in each of the extracts, they were fractionated by anion and cation exchange chromatography. Fractions were assayed for HAT activity using 3H-acetyl Coenzyme A and equivalent amounts of either free histones or chromatin as substrate. Histones were then resolved by SDS-PAGE and acetylated species visualized by fluorography. Fractionation of the cytosolic extract on a DEAE column is shown Figure 1A. As expected, the predominant type B activity present in these preparations was attributable to Hat1p, as indicated by robust, free histone H4 acetylation (Fig. 1A, lanes 28–34). The identity of the Hat1p/Hat2p complex was confirmed by western blot analysis using polyclonal antibodies against both Hat1p and Hat2p (data not shown). Figure 1 Identification of putative histone H3-specific type B histone acetyltransferases. Cytosolic and nuclear extracts were prepared and fractionated as outlined in the flow chart. Inherent HAT activities were identified by assaying column fractions with 3H-Acetyl-Coenzyme A and equivalent amounts of either free histones or chromatin (as indicated). Reaction products were resolved by 18% SDS-PAGE and visualized by fluorography. The relative migrations of the core histones, as determined from coomassie blue staining, are denoted at the side of each fluorogram. The positions of Hat1p and putative H3-specific type B HATs are indicated by brackets. The cytosolic extract also contained at least two additional HAT activities. The first showed a clear peak that was centered on fraction 14 and acetylated free histones H3, H2B and H4. The activity of this HAT on chromatin was more difficult to determine as the H3 and H4 labeling seen in these fractions does not show a marked peak in fraction 14 and may be due to the leading edge of a HAT activity eluting at higher salt. Therefore, this activity may be a candidate type B HAT. There was also a distinct peak of HAT activity at fractions 18–20. With free histone substrates, this activity primarily acetylated histone H3. However, there was also a coincident peak of chromatin H3 and H4 acetylating activity in these fractions suggesting this activity is likely to be a type A HAT. Figure 2 HatB3.1 is a chromatographically distinct activity. DEAE fractions encompassing HatB3.1 activity were pooled and subjected to further fractionation. Fluorograms of liquid HAT assays, using free histones or chromatin as substrates, representative of gradient eluted Mono Q column fractions, showed that HatB3.1 activity can be separated from the overlapping activities present in the initial DEAE fractionation. Migration of the core histones is indicated. Migration of free histone H3 activity attributable to HatB3.1 is marked with an arrow. DEAE fractionation of the nuclear extract also revealed several distinct HAT activities (Figure 1B). There were two H4-specific type A HAT activities that peaked at fractions 14 and 18, as indicated by activity on both free and nucleosomal histones. There was also a significant peak of activity that acetylated free histone H3 (there was also slight acetylation of histone H2B that is more easily seen in Figure 3) that was coincident with a minor nucleosomal H3 HAT activity (Fig. 1B right panel, lanes 16–34). This activity also partly overlapped the nucleosomal H4 activities. This peak of activity was rather broad and most probably results from the partial overlap of at least two distinct activities. In fact, the separation of these activities was readily apparent in Figures 3 and 4. The strong overall preference of these activities for free histone H3 makes them good candidates for H3-specific type B HATs. As these are chromatographically distinct activities we have termed them HatB3.1 and HatB3.2 as indicated (Figure 1B, right panel). Figure 3 HatB3.1 activity is dependent upon GCN5. Nuclear extracts, generated as depicted in Figure 1 from the indicated isogenic deletion strains, were fractionated via DEAE anion exchange chromatography. Fluorograms of HAT assays resolved by 18% SDS-PAGE are shown with the migration of the core histones as indicated. Fractions of equivalent conductance are aligned for each strain. Regions containing HatB3.1, HatB3.2 and Hat1p are identified by brackets. Figure 4 Highly purified HatB3.1 contains Gcn5p and Ada3p in a high molecular weight complex. A) Flowchart outlining the partial purification of HatB3.1. B) Fluorograms of liquid HAT assays of the Superose 6 column fractionation of HatB3.1 activity (top 2 panels). Assays used either free histones or chromatin as substrate (as indicated). The relative elution of molecular weight standards is shown along the top, while the migration of histones H3 and H4 is indicated at the right. Column fraction aliquots (15 μL) were also resolved by SDS-PAGE and visualized by silver staining (bottom panel, protein ladder mobility is represented at right). Corresponding fraction numbers for both the fluorograms and silver stained gel are indicated along the bottom. C) Peak HatB3.1 containing Superose 6 fractions, as indicated at top of blots, were resolved by three identical 10% SDS gels, transferred to nitrocellulose and probed with the indicated antibodies (left of blots). Presence of Gcn5p, Ada2p and Ada3p in nuclear extract and/or column fractions was visualized via chemifluoresence. Relative migration of protein standards is shown on the right. Unbound material from the initial DEAE fractionation of the cytosolic and nuclear extracts was analyzed by cation exchange chromatography (carboxymethyl sepharose (CM)). While this fraction from the cytosolic extract appeared inactive, there were several additional HAT activities resolved from the nuclear extract (Figure 1C, data not shown). The presence of these activities in the DEAE flowthrough fraction is not simply due to column overloading as recycling the flowthrough fraction over the DEAE column a second time did not result in significant protein retention. Hence, these activities are chromatographically distinct from those that bind the DEAE resin. Two activities, centered on fractions 22 and 30, acetylated primarily histone H4. These appeared to be typical type A HAT's as they were active on both free histones and chromatin. A broad peak of histone H3-specific activity eluted from the CM column from fraction 10 through fraction 24 (with activity trailing through the remainder of the gradient). Comparison of the free histone and chromatin activities in these fractions suggested that this region of the gradient actually contained overlapping type A and type B activities. There was a distinct peak of free histone H3 acetylating activity centered on fractions 12 – 14 while acetylation of chromatin associated H3 peaked in fraction 16. Hence, the activity in fractions 12–14 is another candidate H3-specific type B HAT (labeled HatB3.3). HatB3.1 is specific for free histone H3 The fractions from the DEAE column that contained the activity that we have termed HatB3.1 modified not only free histone H3 but also free H4. In addition, a low level of nucleosomal H3 activity could also be seen in these fractions. To determine whether these activities were the result of a single enzyme complex or were due to multiple, overlapping complexes, these fractions were pooled, dialyzed and fractionated over a Mono-Q column (Figure 2). Inspection of the HAT activity profile of the fractions eluting from the Mono-Q column clearly demonstrated that multiple HAT activities overlapped with HatB3.1 during the initial fractionation of the nuclear extract. The HatB3.1 activity eluted from the Mono-Q column very early in the gradient and appeared to be highly specific for free histone H3. The second activity to elute from the Mono-Q column was specific for chromatin-associated histone H4. The third activity acetylated both free and nucleosomal histones H3, H2B and H4. These results indicated that the acetylation of multiple histones in the DEAE elution profile was the result of at least three overlapping activities and confirmed that HatB3.1 is a chromatographically distinct free histone H3-specific activity. Therefore, HatB3.1 was a good candidate for further characterization. HatB3.1 activity is dependent on GCN5 To gain insight into the identity of the catalytic subunit of HatB3.1, we constructed null mutants for each of the yeast HAT's that have demonstrated histone H3 activity as well as the known type B HAT, HAT1. Isogenic deletion strains (Δgcn5, Δsas2, Δsas3 and Δhat1) were grown and protein extracts prepared exactly as for the wild type strain. Nuclear extracts were again fractionated via DEAE column chromatography and fractions of equivalent conductivity assayed for HAT activity as described above. Parallel comparison of the HAT activity profiles from each strain provided biochemical evidence for the dependency of specific histone acetyltransferase activities on the presence of a particular HAT catalytic subunit (compare Figure 3 with Figure 1B). While subtle variations in observed specificity and intensity of HAT activity were seen throughout the profiles of the Δsas2 and Δsas3 strains, the robust H3 acetylation attributed to the HatB3.1 activity appeared unaffected by deletion of these enzymes (Figure 3, lanes 26–34). Conversely, HatB3.1 activity was abolished in a Δgcn5 strain (Figure 3, lanes 26–34). In addition, the HatB3.2 activity also appeared to be absent in extracts from a gcn5 strain indicating that both of these putative type B HAT activities are dependent on Gcn5p. Additionally, the integrity, in a Δgcn5 strain, of the overlapping free histone and chromatin (data not shown) activities in this region of the gradient confirmed that HatB3.1 was a chromatographically distinct HAT activity exhibiting specificity for free histone H3. Analysis of the activity profile from nuclear extracts derived from a Δhat1 strain identified a broad peak of Hat1p dependent activity that spanned fractions ~22–34. Western blot analysis using antibodies against Hat1p and Hat2p confirmed the presence of these proteins in fractions from this region of the gradient from the wild type extract (data not shown). As with the Hat1p-dependent activity in cytosolic extracts, this activity also appeared to be specific for free histone H4. This result confirmed previous observations indicating that Hat1p is localized to both the cytoplasm and the nucleus [37,42]. In addition, the presence of an authentic type B HAT activity in our nuclear extracts validated our use of these extracts for the identification of putative histone H3-specific type B HAT activities. HatB3.1 activity is dependent on ADA3 but not ADA2 There are two proteins, Ada2p and Ada3p, that are components of all known Gcn5p-containing HAT complexes and that are required for the activity of these complexes [9-11,13,14]. To determine whether the HatB3.1 activity was also dependent on these proteins, nuclear extracts were prepared from isogenic Δada2 and Δada3 strains and the status of the HatB3.1 activity determined by DEAE chromatography. As shown in Figure 4, the loss of ADA2 did not affect either the HatB3.1 or HatB3.2 activity but did cause a substantial increase in the free histone H4 specific activity that eluted late in the DEAE gradient. However, the HAT activity profile of the Δada3 extracts was strikingly similar to that seen for the gcn5 extracts with both the HatB3.1 and HatB3.2 activities absent. These results indicated that the HatB3.1 activity was dependent on ADA3 and that Ada2p is either not a component of the HatB3.1 activity or is not required for its stability. Partial purification of HatB3.1 To further characterize HatB3.1, this activity was purified through several chromatographic steps. The purification scheme is diagramed in Figure 5A. HatB3.1 containing fractions from the DEAE column were pooled, dialyzed to a conductivity similar to that of the loading buffer (DN(50)) and the dialysate applied to a cation exchange column (CM sepharose). HAT activity assays indicated that the HatB3.1 activity flowed through the CM sepharose column while bound proteins, resolved by a linear salt gradient, contained co-purifying HAT activities that acetylated both free and nucleosomal, H3 and H4 (data not shown). The presence of HatB3.1 in the CM sepharose flow through also confirmed that HatB3.1 and HatB3.3 were distinct activities. Figure 5 ADA3, but not ADA2, is essential for HatB3.1 activity. Nuclear extracts from isogenic Δada2 and Δada3 strains were prepared and fractionated as previously described for wild type and HAT deletion strains (Figures 1 and 3). Fluorograms reflecting HAT activity assays from fractions of equivalent conductivity from each strain, using free histones, are shown (fraction numbers are displayed at bottom [compare lanes to those in figure 3 as well]). Regions of HatB3.1 and HatB3.2 are highlighted by brackets. The proteins that flowed through the CM sepharose column were applied to a Mono-Q column and then eluted with a linear salt gradient. Fractions containing free histone H3 activity were pooled and concentrated by precipitation with 75% ammonium sulfate. The sample was then fractionated by size exclusion chromatography using a Superose 6 column. As seen in Figure 5B, the HatB3.1 activity peaked at fractions 48–50, indicating that a high molecular weight complex of ~500 kDa was responsible for this activity. The size of HatB3.1 remained stable throughout the course of purification as Superose 6 fractionation of the pooled HatB3.1 activity from the initial DEAE column displayed an identical mass (data not shown). The highly purified HatB3.1 retained its high degree of specificity for free histone versus chromatin substrates. There were also two peaks of free histone H4 specific activity seen in the Superose 6 elution profile. Western blot analysis indicated that Hat1p co-eluted with the low molecular weight species. The second peak of H4 activity co-purified with HatB3.1. Whether this acetylation of histone H4 was the result of a weak specificity of HatB3.1 for H4 or due to a second, co-eluting, HAT activity has not been resolved. Gcn5p and Ada3p, but not Ada2p, co-purified with the HatB3.1 activity The absence of HatB3.1 activity in extracts from a Δgcn5 strain indicated that HatB3.1 was dependent on Gcn5p, either indirectly via Gcn5p-mediated transcriptional regulation, or directly, as its catalytic subunit. While the HatB3.1 activity was highly purified relative to the initial nuclear extract, the peak Superose 6 fractions were still too complex to allow the definitive identification of specific bands that co-purified with the activity (Figure 5B). Extensive efforts to purify HatB3.1 to homogeneity have been unsuccessful. To determine whether Gcn5p was likely to be functioning as the catalytic subunit of HatB3.1, fractions across the peak of HatB3.1 activity from the Superose 6 column were probed with anti-Gcn5p antibodies. As seen in Figure 5C, Gcn5p was present in the fractions containing the peak of HatB3.1 activity from the Superose 6 column. This result is consistent with direct association of Gcn5p with the HatB3.1 complex. Duplicate blots were probed with anti-Ada2p and anti-Ada3p antibodies to determine whether these proteins also co-fractionated with the HatB3.1 complex. As expected, both Ada2p and Ada3p are present in the nuclear extracts (Figure 5C). However, while Ada3p precisely co-purified with Gcn5p and the peak of HatB3.1 activity, Ada2p did not appear to be associated with this complex. The absence of the Ada2p from the peak of HatB3.1 activity is consistent with the observation that HatB3.1 activity is independent of the ADA2 gene and suggests that Ada2p is not a component of the HatB3.1 complex. The absence of an Ada2p signal on the Western blot was not due to problems with sensitivity as comparison of the relative signals of Gcn5p, Ada2p and Ada3p in the nuclear extracts and Superose 6 fractions demonstrated that the presence of Ada2p in the Superose 6 fractions would have been readily apparent. While the HatB3.1 activity is enriched in the Superose 6 peak fractions relative to the original nuclear extract, the amount of Gcn5p and Ada3p present in these fractions is not enriched relative to the nuclear extract due to the fact that these proteins are components of at least five other histone acetyltransferase complexes. Hence, only a fraction of the Gcn5p and Ada3p present in the cell extracts was associated with HatB3.1. Discussion Considerable genetic and biochemical evidence indicates that, in most organisms, newly synthesized histone H3 is acetylated and that this acetylation plays a role in the de novo assembly of chromatin [28,30,31,43-48]. However, the enzymes responsible for this modification have remained elusive. In the present study we have comprehensively surveyed yeast extracts for putative, histone H3-specific, type B histone acetyltransferase activities. At least three candidate activities were identified, HatB3.1, HatB3.2 and HatB3.3. Further characterization of HatB3.1 indicated that this activity is a novel ~500 kDa HAT complex. In addition, our results suggest that Gcn5p and Ada3p are components of this complex but that, contrary to all previously isolated Gcn5p complexes, HatB3.1 is not associated with Ada2p. It does not appear that the HatB3.1 complex is merely an unstable form of one of the previously characterized Gcn5p-containing complexes as the apparent molecular weight of HatB3.1 did not vary during the course of its purification. There have been at least a dozen distinct HAT complexes identified in yeast [8-22,36,42]. Conservative analysis of our systematic fractionation of yeast cytosolic and nuclear extracts resolved 12 chromatographically separable activities. However, many of these activities were represented by rather broad peaks, likely to be composed of partially overlapping activities that may differentiate upon further purification (as seen in Figure 2). While many of the activities identified here may correspond to previously characterized complexes, it is difficult to determine these relationships, as our initial purification steps differ from those typically used for the isolation of other yeast HAT complexes. In particular, the purification of the SAGA, ADA, SLIK, SALSA, NuA3 and NuA4 complexes start from Ni2+-NTA agarose fractionated whole cell extracts, as these enzymes fortuitously bind to this resin [9,10,13,14,17,22]. Most histone acetyltransferases have substrate specificities that direct the acetylation of specific residues within one or more of the core histones [5]. However, these substrate specificities are not fixed and can be altered by the association of the catalytic subunits with different protein complexes [19,49]. The presence of numerous HAT complexes expands the repertoire of modification states that can be generated on the chromatin template. Therefore, as growing evidence indicates that specific cellular processes are associated with precise patterns of histone modification, the presence of multiple HAT complexes in cells is likely to be a reflection of the myriad events that must take place in the context of chromatin [50]. Despite the importance of histone acetylation in regulating chromatin structure, with the exception of Esa1p, none of the yeast histone acetyltransferases are essential for viability [51,52]. Also, the deletion of most HAT genes results in only relatively mild phenotypes [35,36,53-57]. One explanation for this observation is that some HATs perform functionally redundant roles in the cell [58,59]. Alternatively, examination of the HAT activity profiles of fractionated extracts derived from HAT deletion strains presented here suggests that there may be mechanisms that can compensate for the lack of one histone acetyltransferase by increasing the activity of other HAT complexes. For example, in a Δsas2 strain, there is a dramatic increase in an activity present in nuclear extracts that acetylates free histone H4 and which elutes from a DEAE column at a salt concentration similar to that of the nuclear form of Hat1p (Figure 3). In addition, deletion of the HAT1 gene causes a large increase in an activity that is coincident with the HatB3.1 activity. These results suggest the possibility that cells may monitor levels of histone modification and adjust specific HAT activities accordingly. HatB3.1 is the third native HAT complex identified from yeast that is only capable of acetylating free histones [15,36]. In addition to the histone H4 specific Hat1p/Hat2p complex, the SAS complex, composed of Sas2p, Sas4p and Sas5p, was recently shown to acetylate free histones H3 and H4. The potential classification of the SAS complex as a type B HAT is supported by the fact that the SAS complex has also been shown to be physically associated with the histone deposition proteins Cac1p and Asf1p [16,60,61]. However, the specific target of SAS complex acetylation, histone H4 lysine 16, has not been found to be acetylated in the pool of newly synthesized histones in any organism [15,30]. Therefore, it remains to be determined whether the SAS complex participates in the acetylation of newly synthesized histones H3 and H4 prior to histone deposition or whether it is involved in the post-assembly modification of histones. Gcn5p is the prototypical type A histone acetyltransferase. While rGcn5p is only capable of acetylating free histones under most experimental conditions, it has been identified as the catalytic subunit of five native HAT complexes that acetylate nucleosomal substrates (SAGA, ADA, A2, SLIK and SALSA) [9-11,13,14,31,62]. The most straightforward interpretation of the dependence of the HatB3.1 activity on a functional GCN5 gene and the co-elution of Gcn5p with highly purified HatB3.1 is that Gcn5p is also the catalytic subunit of HatB3.1. In the context of the type A HAT complexes, the Ada2p, Ada3p and TAFII68 proteins have been shown to be important for expanding the substrate specificity of Gcn5p to allow for the acetylation of nucleosomal histones [49,63-68]. Hence, the ability of Gcn5p to acetylate histones in chromatin is a property that must be conferred upon it by association with other proteins. The identification of Gcn5p as a component of a type B histone acetyltransferase activity suggests that classification as either type A or type B may not be an inherent property of an enzyme but, rather, may be a function of the association of the enzyme with specific accessory factors. Several properties of HatB3.1 indicate that it is distinct from previously identified Gcn5p-containing complexes. First, HatB3.1 is the only native Gcn5p-containing complex that does not have detectable activity on nucleosomal substrates. Second, the apparent molecular weight of HatB3.1 (~500 kDa), as determined by size exclusion chromatography, is much lower than that of the SAGA, ADA, SALSA and SLIK complexes but is similar to that reported for the A2 complex [9,13,14,64]. However, unlike HatB3.1, the A2 complex is both dependent upon, and co-purifies with, Ada2p. These results clearly distinguish HatB3.1 as a novel Gcn5p-containing HAT complex [64]. Ada2p, Ada3p and Gcn5p form a module that provides the catalytic activity to their associated type A HAT complexes [5]. In these complexes, there does not appear to be any direct physical interaction between Ada3p and Gcn5p but, rather, their association is mediated through Ada2p [55,67,69,70]. The absence of Ada2p from the HatB3.1 activity suggests that Ada3p and Gcn5p can directly associate under certain circumstances or that another subunit(s) of the HatB3.1 complex can replace the function of Ada2p in bridging the interaction of Ada3p and Gcn5p. The identification of a Gcn5p-containing complex that is independent of Ada2p also suggests that there are cellular processes, such as histone deposition, that are influenced by Gcn5p (and Ada3p) but that do not require Ada2p. However, with the exception of the specific synthetic lethality seen with Δgcn5 Δsas3 mutants, deletions of the GCN5, ADA2 and ADA3 genes have similar in vivo consequences [22,59,71,72]. The absence of phenotypes unique to Δgcn5 and Δada3 mutants may be the result of the complex functional redundancies observed in the assembly of chromatin. For example, Δhat1 and Δhat2 mutants only display phenotypes when combined with mutations in multiple lysine residues in the histone H3 NH2-terminal tail [45,46]. Uncovering these redundancies and deciphering the potential role of Gcn5p in the acetylation of newly synthesized histones is likely to require the characterization of the complete set of complexes that display type B histone acetyltransferase activity. Conclusions In conclusion, we have fractionated yeast cytoplasmic and nuclear extracts and resolved several putative histone H3-specific type B histone acetyltransferase activities. One of these activities, HatB3.1, is highly specific for histone H3 that is free in solution. A combination of genetic and biochemical evidence indicates that HatB3.1 is a novel complex that depends on GCN5 and ADA3 but that is independent of ADA2. Methods Yeast strains UCC1111 was used as the wild type yeast strain that serves as the genetic background for all deletion strains [45]. Null mutants for GCN5, SAS3, SAS2, ADA2, ADA3 and HAT1 were constructed using PCR-mediated gene disruption with the HIS3 reporter gene [73]. Extract preparation Cells were grown to mid-log phase in 1% yeast extract, 2% peptone, 2% glucose and 50 μg/mL ampicillin at 30°C. Cells were harvested at 4000 × g, 10', 4°C and total grams of cells recorded. All buffers contain 1.0 mM PMSF. Spheroplasts were prepared essentially as described previously using 0.25 mg of Zymolyase (U.S. Biologicals) per gram of cells for spheroplasting [74]. Spheroplasts were burst in 0.5 mL/g cells Lysis Buffer (18% Ficoll 400, 10 mM HEPES [pH 6.0]) followed by dilution in 1.0 mL/g cells Buffer A (50 mM NaCl, 1.0 mM MgCl2, 10 mM HEPES [pH 6.0]). Supernatant from a 1500 × g, 15' spin at 4°C was retained as a cytosolic extract. Pelleted material was washed once with Buffer A then resuspended in DN(1000) (DN buffers contain 25 mM Tris [pH 7.5], 10% glycerol, 0.1 mM EDTA and mM [NaCl] listed in parentheses). Supernatant from another 1500 × g spin as above yielded the nuclear extract. This extract was dialyzed O/N at 4°C into DN(0) to a conductivity similar to that of the cytosolic extract. Extracts were cleared by high speed centrifugation (~30,000 × g) prior to their chromatographic fractionation. Extract fractionation All columns were equilibrated with and run using DN Buffers. HPLC (ÄKTA purifier – Pharmacia) was employed for all column runs. Anion and cation exchange chromatography DEAE – Cleared extracts were loaded onto a HiPrep 16/10 DEAE FF column (Pharmacia). Following a 5 C.V. wash with DN(50), proteins were eluted with a linear, 20 C.V., salt gradient from 50 mM to 1.0 M NaCl. A flow rate of 1.0 mL/min. was used and 3.0 mL fractions were collected. CM – Either pooled peak fractions, dialyzed into DN(0) until at similar conductivity as DN(50) start buffer, or Flowthrough from the DEAE were loaded onto a HiPrep 16/10 CM FF column (Pharmacia). The column was washed and proteins eluted as described above. Mono Q – The flowthrough fraction from the CM column was loaded onto a Mono Q HR 5/5 column (Pharmacia). Following a 5 C.V. wash with DN(50), a 20 C.V., linear, salt gradient was employed as above and 0.5 mL fractions were collected. Ammonium sulfate precipitation Peak fractions of HatB3.1 activity from the Mono Q column were pooled and brought to 75% (NH4)2SO4 (0.516 g/mL) over 30' at 4°C. Following an additional 30' equilibration period at 4°C, precipitated protein was pelleted (10,000 × g, 10', 4°C) and resuspended in 300 μL cold, DN(0). Gel filtration chromatography A 250 μL aliquot of resuspended ammonium sulfate precipitate was loaded onto a Superose 6 HR 10/30 column (Pharmacia). The column was equilibrated with and run in DN(350) at a flow rate of 0.3 mL/min. and 0.25 mL fractions were collected. Molecular weight standards (Sigma, MW-GF-1000) were run using the same parameters and 24 μL aliquots of every other fraction run on a 10% SDS-polyacrylamide gel. The elution profile of the MW standards was determined by protein visualization via Coomassie blue staining. Liquid HAT assays Chicken erythrocyte core histones and chromatin were isolated as previously described [75,76]. Typically 10 μL aliquots of column fractions were incubated with 0.1 μM 3H-Acetyl Coenzyme A (5.50 Ci/mmol, Pharmacia) and ~1.0 mg/mL core histones or chromatin in a final volume of 100 μL at 1X [DN(75)]. 50 μL of each reaction was analyzed for HAT activity via liquid scintillation counting. The remaining assay mixture was brought to 1X [SDS Load Dye] to stop the reaction. In general, aliquots (24 μL) of these remaining assay mixtures were run on 18% SDS-polyacrylamide gels to resolve the histones. Gels were incubated in Autofluor (National Diagnostics), dried down and acetylated histone species visualized via fluorography. Western blot and gel analysis Superose 6 fractions exhibiting HAT B3 activity, as determined above, were run on 10% SDS-polyacrylamide gels and proteins were either visualized by silver staining or transferred to nitrocellulose using a semi-dry transfer apparatus (Biorad). Blots were processed following standard procedures. Goat, polyclonal antibodies against Gcn5p, Ada2p and Ada3p (Santa Cruz Biotechnology, Inc.) were used at 1:100 dilutions in 5% Milk/TBS-T. Donkey, HRP-labeled Anti-Goat IgG secondary antibody (Santa Cruz Biotechnology, Inc.) was used at 1:2500 dilution followed by detection with ECL+Plus (Pharmacia) and visualization via phosphoimager (STORM 860, Pharmacia). Authors' contributions A.R.S. performed all of the experiments presented here and drafted the manuscript. M.R.P. directed the project and edited the manuscript. Acknowledgements This work was supported by grants from the American Cancer Society (RPG-00-340-01-CSM) and the National Institutes of Health (1 R01 GM62970) to M.R.P.. ==== Refs van Holde KE Chromatin 1989 New York: Springer-Verlag Turner BM Cellular memory and the histone code Cell 2002 111 285 91 12419240 10.1016/S0092-8674(02)01080-2 Goll MG Bestor TH Histone modification and replacement in chromatin activation Genes Dev 2002 16 1739 42 12130533 10.1101/gad.1013902 Spotswood HT Turner BM An increasingly complex code J Clin Invest 2002 110 577 82 12208855 10.1172/JCI200216547 Roth SY Denu JM Allis CD Histone acetyltransferases Annu Rev Biochem 2001 70 81 120 11395403 10.1146/annurev.biochem.70.1.81 Narlikar GJ Fan HY Kingston RE Cooperation between complexes that regulate chromatin structure and transcription Cell 2002 108 475 87 11909519 10.1016/S0092-8674(02)00654-2 Brownell JE Allis CD Special hats for special occasions: Linking histone acetylation to chromatin assembly and gene 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Evidence for an adaptor complex in vivo J Biol Chem 1996 271 5237 45 8617808 10.1074/jbc.271.9.5237 Pina B Berger S Marcus GA Silverman N Agapite J Guarente L Ada3: A gene, identified by resistance to gal4-vp16, with properties similar to and different from those of ada2 Mol Cell Biol 1993 13 5981 9 8413201 Georgakopoulos T Gounalaki N Thireos G Genetic evidence for the interaction of the yeast transcriptional co-activator proteins gcn5 and ada2 Mol Gen Genet 1995 246 723 8 7898440 Baudin A Ozier-Kalogeropoulos O Denouel A Lacroute F Cullin C A simple and efficient method for direct gene deletion in saccharomyces cerevisiae Nucleic Acids Res 1993 21 3329 30 8341614 Lowary PT Widom J Higher-order structure of saccharomyces cerevisiae chromatin Proc Natl Acad Sci U S A 1989 86 8266 70 2682643 Feng HP Scherl DS Widom J Lifetime of the histone octamer studied by continuous-flow quasielastic light scattering: Test of a model for nucleosome transcription Biochemistry 1993 32 7824 31 8347588 Widom J Physicochemical studies of the folding of the 100 a nucleosome filament into the 300 a filament. Cation dependence J Mol Biol 1986 190 411 24 3783706

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==== Front Malar JMalaria Journal1475-2875BioMed Central London 1475-2875-3-281528386610.1186/1475-2875-3-28ResearchMolecular dissection of the human antibody response to the structural repeat epitope of Plasmodium falciparum sporozoite from a protected donor Chappel Jonathan A 1akang@avanir.comRogers William O 23brogers@noguchi.mimcom.netHoffman Stephen L 24slhoffman@sanaria.comKang Angray S 15akang@avanir.com1 Department of Molecular Biology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA2 Malaria Program, Naval Medical Research Center, Silver Spring, MD 20910-7500, USA3 Present address: Naval Medical Research Unit #3, Ghana Det, c/o Department of State, 2020 Accra Place, Washington, DC 20521-2020, USA4 Present address: Sanaria Inc, 12115 Parklawn Drive Suite L, Rockville, MD 20852, USA5 Present address: Avanir Pharmaceuticals Inc, 11388 Sorrento Valley Road, San Diego, CA 92121, USA2004 29 7 2004 3 28 28 15 5 2004 29 7 2004 Copyright © 2004 Chappel et al; licensee BioMed Central Ltd.2004Chappel et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background The circumsporozoite surface protein is the primary target of human antibodies against Plasmodium falciparum sporozoites, these antibodies are predominantly directed to the major repetitive epitope (Asn-Pro-Asn-Ala)n, (NPNA)n. In individuals immunized by the bites of irradiated Anopheles mosquitoes carrying P. falciparum sporozoites in their salivary glands, the anti-repeat response dominates and is thought by many to play a role in protective immunity. Methods The antibody repertoire from a protected individual immunized by the bites of irradiated P. falciparum infected Anopheles stephensi was recapitulated in a phage display library. Following affinity based selection against (NPNA)3 antibody fragments that recognized the PfCSP repeat epitope were rescued. Results Analysis of selected antibody fragments implied the response was restricted to a single antibody fragment consisting of VH3 and VκI families for heavy and light chain respectively with moderate affinity for the ligand. Conclusion The dissection of the protective antibody response against the repeat epitope revealed that the response was apparently restricted to a single VH/VL pairing (PfNPNA-1). The affinity for the ligand was in the μM range. If anti-repeat antibodies are involved in the protective immunity elicited by exposure to radiation attenuated P. falciparum sporozoites, then high circulating levels of antibodies against the repeat region may be more important than intrinsic high affinity for protection. The ability to attain and sustain high levels of anti-(NPNA)n will be one of the key determinants of efficacy for a vaccine that relies upon anti-PfCSP repeat antibodies as the primary mechanism of protective immunity against P. falciparum. ==== Body Background Malaria threatens public health in regions of the world where more than a third of the human population lives [1,2]. It has been shown that immunization with radiation-attenuated Plasmodium sporozoites, the infective stage of the malaria parasite, confers protective immunity [3,4]. The role of specific antibody in conferring protection was demonstrated with passive administration of murine mAbs directed against the major repeat epitope of the circumsporozoite (CS) protein [5] in a rodent model. The corresponding epitope of the human malaria parasite Plasmodium falciparum is contained within the repeat tetramer peptide (Asn-Pro-Asn-Ala)n, (NPNA)n [6]. In some studies of volunteers protected against malaria by immunization with radiation attenuated P. falciparum sporozoites, protected individuals had significant elevations of anti-repeat antibodies (>19 μg/ml) [7]. With the advent of recombinant combinatorial antibody technology [8,9] and phage display [10-13] it is possible to attempt to dissect the human antibody response against a wide range of pathogens. In order to further investigate the role of the human antibody response in P. falciparum sporozoite induced protection, a phage display library of antibody gene fragments isolated from the peripheral blood lymphocytes of such a protected donor (WR5) [7] was assembled. Recombinant antibodies against the PfCSP structural repeat (NPNA)3 epitope were selected. Recognition was restricted to a single antibody designated PfNPNA-1, encoded by VH3 and VκI families. This restricted humoral response has implications for rational vaccine design and the potential use of this human monoclonal antibody to prevent P. falciparum infection. Methods RT-PCR of Immunoglobulin genes A human volunteer (WR5), who was previously exposed to the bites of γ-irradiated P. falciparum infected Anopheles mosquito's and subsequently shown to be protected against a non-irradiated parasite challenge, donated lymphocytes by leukophoresis five days after a booster challenge (appropriate informed consent was obtained) for details see Egan et al., [7]. The irradiated sporozoite immunization protocol was approved by the Naval Medical Research Institute's Committee for the Protection of Human Subjects in accordance with the US Navy regulation (SECNAVINST3900.39B) governing the use of human participants in medical research. Total RNA was extracted from 2 ml of packed cells using an RNA isolation kit (Stratagene, La Jolla, CA) with a modified protocol [9]. The equivalent of 2.5 μg total RNA template were used in each cDNA synthesis reaction using reverse transcriptase (Invitrogen, CA) with oligonucleotide oligo dT or 3 'HuVH (5'GCCCCCAGAGGTGCTCTTGGA-3', anneals in CH1 domain) following the instructions provided by the supplier. The genes encoding variable heavy (VH) and the kappa chain (κ) were accessed by RT-PCR and combined by overlap extension PCR, resulting in shuffling of the VH and the VL domains. The VH PCR amplification was carried out with the cDNA template generated using the 3'HuVH primer. The VH domains were amplified using 5'HuVHA and 3'HuVH-Link 3' designed to anneal with the sequence corresponding to the first β-strand of the CH1 domain and overlap with the 5'HuVk primer. The κ chains were amplified using 5'HuVk and the 3'Hukappa primers. The VH and the κ chain PCR products were combined by overlap extension PCR using a VH flanking primer 5'HuVHB (to introduce a NheI site) and the 3'HuKappa primer. Oligonucleotide primer sequences 5'HuVk 5'-TATTAGCGGCCGCCCAACCAGCCATGGCCGAEFIJLOPETGACBCAGTCTCC-3' (where B=G+C+T, S=G+C, E = 50%A+33%C+17%T, F = 83%A = 17%G, I = 83%T+17%C, J = 50%T+33%C+17%G, L = 67%G+17%T+17%C, O = 67%T+17%A+17%C, and P = 83%G+17%C) 3'HuKappa 5'-TCCTGAAGCTTGACGACCTTCGATCTCTCCCCTGTTGAAGCTCTT-3' 5'HuVHA 5'-SAGGTGCAGCTGSTGSAGTCTGG-3' 5'HuVHlink3' 5'-GGCTGGTTGGGCGGCCGCTAATATGGAGGAGGGTGCCAGGGGGAAGAC-3' 3'HuVHB 5'-GTTTCGCTAGCGTAGCTCAGGCTSAGGTGCAGCTGSTGSAGTCTGG-3' The procedural steps are illustrated in Figure 1. Figure 1 VH/κ library construction. A schematic diagram of the steps involved in constructing a VH/κ library from mRNA isolated from PBL. Cloning PCR fragments into pORFES and JC-M13-88 The PCR amplified VH/κ products were digested with restriction enzymes NheI and HindIII, and ligated into pORFES [14]. An aliquot of E. coli transformed with the ligation mixture was plated with and without carbenicillin selection, to determine the number of functional inserts. The VH/κ coding sequences are directionally inserted for expression between an OmpA leader peptide (to direct the polypeptide into the periplasm), and the β-lactamase. Functional full-length VH/κ β-lactamase fusion polypeptide is secreted into the periplasm. Bacteria harbouring plasmids conferring antibiotic resistance may be positively selected. The VH/κ coding insert may be readily transferred as a XbaI-HindIII fragment into the JC-M13-88 phage vector to display the insert polypeptide as a gpVIII fusion. The selected "functional" library of VH/κ inserts were excised from pORFES using XbaI and HindIII, ligated into pre-digested JC-M13-88 [4], and transformed into E. coli (XL1-Blue: Stratagene). Phage was produced overnight at 37°C in the presence of 1 mM IPTG, unless otherwise stated. A schematic outline of the vectors is shown in Figure 2. Figure 2 Illustration of vectors pORFES, JC-M13-88 and pAbHIS. Phage panning The peptide (NPNA)3C (Chiron Mimotopes Peptide Systems, San Diego, CA.) was conjugated to BSA using Imject Activated Immunogen kit (Pierce, Rockford, IL) according to the manufacturers guidelines. ELISA plates (Dynatech Immunlon I, Alexandria, VA) were coated with BSA or (NPNA)3C-BSA and used in phage panning experiments essentially as described elsewhere [5]. To blocked antigen coated wells a total of 4 × 1010 plaque forming units (pfu) of the phage library in dilution buffer (PBS pH 7.2, Tween-20 0.05%, BSA 0.1%, NaN3 0.02%) was added (1 × 1010 plaque forming units (pfu) per well). After 4 h the wells were washed and the bound phage were eluted by applying either 0.1 M glycine-HCl, pH2.2 or a solution of the free peptide (NPNA)3 (~8 μM) dissolved in dilution buffer, for 15 min at ambient temperature. An aliquot of the phage elute was titered, and the remainder was used to propagate phage for further rounds of panning. The three-domain single chain antibody retains the kappa constant domain thus permits plaques filter lifts to be probed with anti-human kappa chain antibodies for immunodetection. VH and VL coding sequences were determined by sequencing of replicative form (rf) phage DNA prepared from κ-positive plaques, using the oligonucleotides primers: 3'Seq VH-JC130 (5'-CGGCCATGGCTGGTTGGGCGGCC-3') and 3'Seq VL-JC128 (5'TTCAACTGCTCATCAGATGGCGG-3'). Expression of PfNPNA-1 VH/k in E. coli The expression vector pAbHIS, was constructed by modification of pUC18. The β-galactosidase coding region was removed and XbaI-HindIII sites introduced upstream of a sequence encoding a six histidine tail. Insertion of VH/κ coding sequence selected by phage display as XbaI-HindIII fragment would result in the expressed polypeptide being secreted into the periplasmic space with a hexa-histidine tag. The plasmid pAbHIS was constructed by PCR modification of pUC18 using the primers PUCSpe-JC127(5'-TCATCATACTAGTAACGACACCCGCCAACACCC-3') and M13-JC118 (5'-AAGCTTATGATGTCTAGAGCTGTTTCCTGTGTGAA-3'). A pair of annealed oligonucleotides designed to encode a 6×His tag were ligated into the HindIII digested plasmid to complete pAbHIS. The selected PfNPNA-1 VH/κ gene was excised from the rf JC-M13-88 DNA by digestion with XbaI and HindIII and ligated into similarly digested pAbHIS. An additional 6×His-coding pair of oligonucleotides was ligated into the PfNPNA-1 VH/κ linker sequence as NotI-NcoI insert. The expression of PfNPNA-1 VH/κ in E. coli D29A1 cells at 25°C, and the isolation of bacterial periplasmic material was performed as described [16] with modifications; Dnase I n(1 μg/ml) and MgCl2 (20 mM) were added, the bacterial suspension was incubated on ice for a further 20 min before final centrifugation step. The periplasmic extract was passed over Ni-NTA resin (Qiagen), washed and the PfNPNA-1 VH/κ was eluted with 300 mM imidazole. SDS PAGE and western blotting were used to asses purity and integrity of the expressed VH/κ polypeptide during the purification procedure (data not shown). Purified PfNPNA-1 VH/κ was quantified spectrophotometrically assuming an OD at 280 nm of 1 = 0.72 mg/ml protein. ELISA affinity and specificity determination ELISA Plates (Dynatech Immunlon I) were coated with (NPNA)3C-BSA (10 μg/ml). Dilutions of the peptide (NPNA)3 were made in dimethyl formamide (DMF) before mixing with the PfNPNA-1 VH/κ diluted in PBST. Aliquots of 0.1 ml were added to duplicate wells, incubated for 2 h at 37°C. In all wells the final concentration of DMF was 1% (v/v). After washing 4 times with PBST, anti-human kappa chain alkaline phosphatase conjugate diluted 1:1000 in PBST was added and incubated as before. The wells were washed 4 × with PBST and rinsed 1× with PBS and substrate p-nitrophenyl phosphate was added, the absorbance was determined at 405 nm The binding of immune serum (WR5), non-immune serum and PfNPNA-1 VH/κ to R32tet32, recombinant hepatitis core containing (NANP)4 peptide sequence and (NPNA)3C-BSA conjugate coated microtiter plate well was determined by ELISA essentially as described above. The serum(s) and the recombinant PfNPNA-1 VH/κ were diluted 1/16 and 1/10 respectively. Phage ELISA Phage at 1 × 1012 pfu/ml in dilution buffer were applied (0.1 ml/well) to duplicate wells coated with (NPNA)3-C-BSA or BSA (10 μg/ml). After incubation at ambient temperature for 4 h, plates were washed with PBST. The bound phage was detected with sheep anti-M13 antibodies (5'-prime 3'-prime), followed by rabbit anti-sheep alkaline phosphatase antibodies in PBST added sequentially for 1 h at 37°C. Plates were washed and developed as described above. Indirect immunofluorescence assay (IFA) on P. falciparum sporozoites The PfNPNA-1 VH/κ was compared with a well-characterized murine monoclonal anti-Pf repeat antibody 2A10 [17,18] in IFA. All incubations were at 37°C in a humid container. Printed multiwell slides coated with Plasmodium falciparum NF54 strain sporozoites were either fixed in ice cold acetone for 10 min or used unfixed. Slides were first blocked with 4%BSA in PBS for 1 h. Antibodies diluted in PBST were applied for 2 h, then slides were washed 4× with PBS and fluoroscein-conjugated anti-human kappa chain or anti-mouse immunoglobulin (Sigma) was applied, diluted 1:25 in PBST. After 2 h slides were washed as above and mounted in SlowFade anti-fade reagent (Molecular Probes, Eugene, OR) and viewed by fluorescence microscopy. Other antibodies The murine mAb 2A10 [17,18] (IgG2b, κ), which recognizes the (NANP)3 sequence of the P. falciparum CSP was provide as whole ascitic fluid (a kind gift from Dr P. Sinnis New York University). Concentration of the whole IgG was estimated using a standard antibody capture ELISA. Immune IgG (denoted (Vol-IgG) was purified from serum of the immune volunteer (WR5), donated at the time of lymphophoresis using Protein A Sepharose (Pharmacia) and quantified assuming OD at 280 nm of 1.0 represents 0.8 mg/ml IgG. Within the Vol-IgG, the proportion of (NPNA)3 specific IgG with κ or λ light chains were determined by ELISA (data not shown). Results Library construction Sera from the protected individual (WR5) [7] contained antibodies against the PfCSP, which were predominantly IgG/κ and against the structural repeat peptide as determined by ELISA. Gene fragments encoding VH/κ single chain antibodies were amplified and assembled by PCR from cDNA derived from the peripheral blood lymphocytes of the immune donor WR5 (as outlined in Figure 1). The library of PCR amplified VH/κ sequences were inserted into pORFES [14] and an aliquot compared for number of functional inserts by selecting in the presence of either chloramphenicol (total transformation events) or chloramphenicol and carbenicillin (functional inserts). Approximately half of the initial library contained non-functional domains (data not shown). The remainder of the library was selected on 100 μg/ml carbenicillin, yielding a primary library of 1.3 × 106 members, these VH/κ sequences were transferred to the phage display vector JC-M13-88 [15] with ten fold over representation of the primary library. Panning Samples of the VH/κ-phage library were subjected to four rounds of panning on (NPNA)3C-BSA coated wells. Both the acid and peptide elution strategies yielded significantly greater numbers of phage after four cycles of panning on (NPNA)3C-BSA when compared to panning on BSA alone (Table 1). Analysis of fifteen individual phage after the fourth round of panning on (NPNA)3C-BSA eluted with free peptide revealed, twelve kappa positive phage, of these three clones (NP 04, 12, 13) were positive in the phage ELISA for binding to (NPNA)3C-BSA and were encoded by an identical sequence, henceforth denoted PfNPNA-1. Prior to panning ten kappa positive clones were randomly selected for sequencing (R 01-10; Table 2). The PfNPNA-1 VH and VL sequences were members of the VH3 and VκI families respectively and were not found amongst the random sampling of phage prior to panning. In an independent experiment with phage propagated at 30°C, but otherwise an identical panning procedure 12 out of 12 selected phage clones were identical to PfNPNA-1. Likewise, phage selected by acid elution and evaluated by ELISA for binding to (NPNA)3C-BSA were all identical to PfNPNA-1. Despite extensive sampling of phage that were positive in the phage ELISA for binding to (NPNA)3C-BSA (n = 25), only the PfNPNA-1 sequence was observed. Table 1 Phage panning experiments ELISA plates (Dynatech Immulon I) were coated with BSA or (NPNA)3C-BSA and used in phage panning experiments. To the blocked antigen coated wells a total of 4 × 1010 pfu of the phage library in dilution buffer were added 1 × l010 pfu per well. After 4 h the wells were washed and phage eluted by applying either 0.1 M glycine-HCl pH 2.2 or a solution of the free peptide (~8 μM) (NPNA)3 dissolved in dilution buffer for 15 min at ambient temperature. An aliquot of the phage eluate was titered and the output determined. Eluate after Coating antigen / Elution method (×l05 pfu)* panning rounds BSA / acid BSA /(NPNA)3 (NPNA)3C BSA /acid (NPNA)3C BSA /(NPNA)3 1 2.9 (0.38) 0.82 (0.032) 3.0 (0.34) 0.51 (0.024) 2 1.4(0.03) 0.24 (0.020) 3.5 (0.24) 1.5 (0.028) 3 1.2(0.06) 0.47 (0.020) 4.3 (0.024) 12 (0.68) 4 13 (0.70) 1.0(0.032) 170 (30) 370 (20) * Figures represent the mean of the total plaque forming units eluted by either acid or excess free peptide, after repeated panning against BSA or (NPNA)3C-BSA. Values for the standard deviation are shown in brackets (). Table 2 VH and VL assignments and alignment of CDR 3 sequences The selected (NP 04, 12, 13 designated Pf NPNA-1 bind to the repeat epitope), all other NP clones were randomly picked after the panning procedure and were subsequently shown not to be reactive with the repeat epitope. Non-selected (R01-10) were randomly picked from the library prior to initiating panning. The peptide sequence of the heavy and light chain complementarity-determining region 3 (CDR3) is shown below. VH/VL families, segments and the number of differences from germline segments were determined by using the V BASE sequence directory (Tomlinson, I. M., Williams, S. C., Corbett, S. J., Cox, J. P. L. & Winter, G., MRC Centre for Protein Engineering, Cambridge, UK) and the DNAPLOT alignment package (Müller, W. & Althaus, H.-H., Köln University) clone code* VH family VH Segment Differences from germline VHCDR3 VL family VL Segment Differences from germline VLCDR3 PfNPNAl VH3 DP46 10 DRDSSSYFDS VkI L12a 15 QQYNSYSGLT NP04, NP12, NP13 VH3 DP46 10 DRDSSSYFDS VkI L12a QQYNSYSGLT R01 VH1 4M28†‡ 28(+6)* §- DSESVAQWRY VkIV DPK24 43 QQSLSPVWT R02 VH3 COS-3‡ 27 (+3)_ GVNWCSDY VkI DPK9 10 QQSYSTSWT R03 VH5 DP73 35 LYTSIYYFDS VkIV DPK24 7 QQYYSTPLT R04 VH3 DP46 8 DRVTNFWSGYFDY VkIII DPK22 13 QQYGSSPGFT R05 VH3 DP58 23 DSTVKTVTKMRYGLD V VkIII DPK22 8 QQYGSSPFT R06 VH1 4M28† 12 DNYGDPGGGFDI VkIII DPK22 11 QQYGNSPRT R07 VH5 DP73 9 RFWFGELYDAFDI VkIV DPK24 16 HQYYSTPQT R08 VH5 DP73 34 LYTSIYYFDS VkIII DPK22 14 QQYGRSPWT R09 VH3 V3-21† 34 DQGGGWSSEVDS VkIII Vg 5 QQRSNWPLT R10 VH1 DP7‡ 21 (+9)** ALYGHDAFDI VkI DPK4 12 PKYNSALHT NP02 VH3 DP47 36 ERPYDAFDS VkIII DPK22 23 QQYSTSPPMYN NP03 VH5 DP73 40 LYTSIYYFDS VkIII Vg 17 KQRSKWPPIT NP05 VH3 V3-48 14 EPRGAGTTLYFDY VkIII DPK22 22 QQYGGSPGYN NP08 VH4 4.30† 18 DRGVSSGWTFDC VkII DPK16 32 MQLTAFPWT NP09 VH4 DP71 17 FRGGVAAGYDY VkIII DPK22 24 QHYRESCS NP10 VH4 DP78 29 DRVRVPYYYIDV VkIII DPK22 15 QQYGTSPYS NP11 VH3 VH3-8† 12 DTTVTHYFDY VkI DPK9 21 QQSFSSPRT NP14 VH1 DP88 20 GPGATIHYYYMDV VkI DPK8 18 QQLDNYPLT NP15 VH5 DP73 36 LYTSIYYFDS VkIII DPK22 28 QQYGNSPPT *Phage clones were either selected from the library at random (prefix R) or after four rounds of panning against (NPNA)3C-BSA, eluting with free (NPNA)3 peptide (prefix NP). † The segment given the best DNAPLOT match, although the segment sequence has not been verified by duplication. ‡ Aligned after removal of the unusual sequence additions (see§,-, ‡,-, **). § Figure in brackets indicates an unusual sequence addition. - Sequence has two additional codons in CDR1. - Sequence has one additional codon in CDR1. ** Sequence has three additional codons in CDR2. Expression and evaluation of the recombinant antibody fragment The PfNPNA-1 sequence was transferred to the expression vector pAbHIS (as outlined in Figure 2. Purification of the VH/κ polypeptide was carried out on Ni-NTA agarose beads, yielding 0.5 mg of the 38 kDa VH/κ polypeptide/L bacterial culture. Fine specificity and affinity determination Anti-sporozoite activity of the PfNPNA-1 VH/κ molecule was clearly evident in an immunofluorescence assay (IFA) with P. falciparum sporozoites (Figure 3). The human single chain monoavalent antibody (panel A) was compared with a known in vitro protective whole murine antibody 2A10 (panel B). The murine antibody and the recombinant PfNPNA-1 VH/κ molecule both labelled the parasites. Figure 3 Indirect immunofluorescence assay (IFA) on Plasmodium falciparum sporozoites. Panel (A) PfNPNA-1 VH/κ, (B) 2A10 MAb. Competitive ELISA was carried out and the IC50 value used to approximate the affinity of binding. Binding affinity of the monovalent PfNPNA-1 for (NPNA)3 compared favourably with values previously reported for a panel of conventional murine monoclonal antibodies directed against the repeat epitope [18], which also have affinities in the μM range (Figure 4). Figure 4 Competition ELISA. Analysis of the fine specificity of the antibody PfNPNA-1 revealed weak binding to the repeat based [NVDP(NANP)15]2, R32tet32 [19], whilst binding to the (NANP)4 epitope contained within the hepatitis B virus nucleocapsid (C75CS2) [20] was strong. This activity profile pattern was mirrored in the protected donor serum (Figure 5). The very high binding observed with WR5 immune serum with the (NPNA)3C-BSA conjugate is probably due to the multivalent array of the capture ligand (i.e. multiple peptides coupled per BSA molecule), favouring more efficient retention of the antibody. Figure 5 Determination of specificity of PfNPNA-1. The binding of immune serum (WR5), non-immune serum and PfNPNA-1 VH/κ to R32tet32, recombinant hepatitis core containing (NANP)4 peptide sequence and (NPNA)3C-BSA conjugate coated microtiter plate well was determined by ELISA essentially as described in Figure 4. The serum(s) and the recombinant PfNPNA-1 VH/κ were diluted 1/16 and 1/10 respectively. Discussion The recombinant antibody library construction differed from conventional antibody phage display library assembly [10-13], a pre-selection step was introduced to remove antibody inserts that were either; prematurely terminated, intact but did not translate well or were intact, translated well but failed to translocate into the bacterial periplasmic space, a prerequisite for functional display. Previously an approach towards developing a vector to select for fully intact functional sequences for antibody or peptide display had shown promise with model sequences [21], but had not been applied for large-scale random antibody library assembly. A "clean-up" vector, plasmid open reading frames expression secretion (pORFES) [14] was developed and used to remove these non-functional sequences. Up to 50% of the clones from the initial transformed library were non-functional. Some of the non-functional antibody fragments could in part be due to errors introduced during PCR amplification resulting in frame shifts. However it may be that some sequences either did not express well or did not translocate into the periplasmic space. Irrespective of the explanation, the size of the functional library was half of the total transformation events. An initial enhancement of the initial library by removing most non-functional inserts may at first appear to be a minor improvement. However, in conventional phage display the initial expansion of the library prior to panning results in a preferential growth of phage that do not make and display encoded inserts, moreover phage that lack an insert have a greater growth advantage. This results in a phage population that is greatly biased towards non-productive elements, which impacts directly on the panning efficiency. Incorporation of the pORFES step assured that only the functional (1.3 × l06) sequences were subsequently transferred to the phage display vector. Panning with a functionally enhanced library resulted in very efficient enrichment and recovery. Previously it had been demonstrated that manipulating the conditions of phage production results in modulation of the density of antibody display on phage [15]. The phage library was expanded using parameters that would result in either monovalent display (0-1 antibody/phage) or multivalent display (0–5 antibodies/phage) [15] prior to initiating panning. It was anticipated that a range of antibodies with varying affinities would be present in the library, and modulating antibody display on phage would permit capture antibodies with a range of affinities and sequence diversity. Induction of protective immunity against sporozoite challenge by exposure to radiation attenuated malaria sporozoite has been demonstrated in humans [4,7,22]. Protection is thought by most investigators to be primarily cellular in nature [23], but there is no question that antibodies with significant sporozoite neutralizing activity are elicited [22] and may play a role in protection. The antibody response is primarily directed against the repeat region of the PfCSP. Studies of subunit vaccines which induce antibodies only against the repeat region demonstrate that protective immunity can be induced in some individuals [24,25]. At the onset of this study it was proposed that the dissection of the anti-P. falciparum sporozoite antibody response by combinatorial antibody library phage display would permit individual selected antibodies to be evaluated for protective potential and the information generated could be used in vaccine design. In particular, attention was focused on antibodies against the structural motif (NPNA)n. Despite using two different strategies for the elution of repeat region peptide specific antibodies (acid and peptide specific) it would appear that the anti-structural repeat response by this protected individual is restricted to a single VH/VL combination observed in the panel of selected phage (n = 25). Sequencing of randomly picked phage prior to panning revealed that a diverse range of VH and VL families were represented in the library as shown in Table 2. Moreover the PfNPNA-1 VH/VL was not represented in the sampling and was only detected after enrichment. Comparison of the monovalent PfNPNA-1 molecule with the conventional bivalent murine mAb, such as the in vitro inhibitory 2A10 against P. falciparum sporozoites indicates that they recognize the repeat epitope(s) with equivalent affinities [18]. The sequence revealed extensive somatic hyper mutations in both the VH and VL genes suggesting antigen driven affinity maturation. Based on these observations, PfNPNA-1 may be a good candidate to develop and evaluate as a protective antibody. Analysis of field samples in rural Gambia [26], Thailand [27] Indonesia [28] and Kenya [29], suggest that anti-sporozoite antibody is poorly developed under natural conditions of exposure and does not protect against clinical malaria. In contrast to exposure to P. falciparum sporozoites under natural conditions in the field, immunization with irradiated P. falciparum sporozoites induces in general higher levels of antibodies against the PfCSP repeats, and does induce sterile protective immunity [4,7,30-38]. In the study by Egan et al., 3 of the 4 volunteers were protected against challenge with P. falciparum sporozoites. The generally accepted explanation for the lack of protection in the one volunteer is that the volunteer did not receive an adequate immunizing dose of irradiated sporozoites (less than 1000 infective bites [4,7]). However, it is of interest that this non-protected volunteer (WR1, [22])had significantly lower levels of antibodies against the PfCSP repeat than did the protected volunteer who donated cells for this study (WR5, [22]) (2.4 μg/ml vs 50 μg/ml of specific antibody). This raises the question as to whether the antibodies are markers for adequate immunization or are actually major mediators of protection. Regardless, this anti-repeat response in this protected individual appeared to be restricted to a single antibody. This does not preclude that antibodies directed against non-repeat epitopes on PfCSP and other sporozoite proteins [39] play a role in protection. It is not possible to conclude that the response against the structural repeat epitope is restricted to a single antibody of moderate affinity, since only a single protected donor has been used in this study. One may speculate that in concordance with the argument put forward by Saul [40] that the inability to recover high affinity antibody, may reflect that high affinity antibodies may not be required for protection. Due to the repetitive nature of the antigen one can further speculate that only limited affinity maturation is required to obtain physiologically relevant efficacy. The restricted recovery of antibodies is unlikely to be a technical limitation on the phage technology since others have generated panels of very high affinity human antibodies against a range of antigens [13]. Very few examples of different approaches of generating human antibodies from immune donors are described in the literature, in particular when attempting to make antibodies against the same antigen. Currently it is not possible to fully understand the limitations of a technology. Using an alternative technology of engrafting immune human PBL's directly into SCID mice from donors vaccinated against anthrax vaccine adsorbed, boosting with protective antigen (PA), recovering immortalizing antibody-producing cells via conventional hybridoma technology [41] resulted in a panel of very high affinity potent neutralizing antibodies against anthrax toxin. Independently, an antibody phage display library from a similar (not identical) immune donor PBL's was constructed and panned against PA [42] also resulted in a panel of high affinity anti-anthrax PA antibodies. This would suggest that the methodology is not limiting. However in this example, unlike CSP, the PA antigen does not contain repeating epitopes. Further it is speculated that antibodies directed against the structural (NPNA)n repeat play a role in conferring protection against P. falciparum sporozoites in some of the protected volunteers and this protection may be associated with circulating levels of this specific antibody against the structural repeat. Efforts are being directed towards producing a fully human IgG based on the PfNPNA-1 VH and VL domains for further in vitro and in vivo evaluation. The use of a human monoclonal antibody as a preventive measure against P. falciparum malaria, would be independent of factors which hinder active vaccination, such as adjuvant effects, the requirement to be effectively presented in a diverse range of human leukocyte class I and II molecules, and immunlogical antagonism [43,44]. In practice, the utility of monoclonal antibodies as anti-infectious agents is often negated by the presence and or the inevitable emergence of variants with altered surface epitopes (in particular with viral targets). Fortunately, there has never been a P. falciparum isolate that does not contain the (NPNA)n repeats on the PfCSP [45], and the number of tandem array of repeats on the PfCSP reduces the likelihood of variants arising which evade antibody recognition. This would suggest that an effective antibody directed against the repeats would be effective against all P. falciparum. If this restricted antibody response to the repeat epitope plays a role in preventing P. falciparum infection, PfNPNA-1 may be a useful prophylactic agent. Moreover, if PfNPNA-1 is shown to be protective in passive immunization in humans or monkeys as previously demonstrated for anti-P. vivax CSP murine mAb, NVS3 [46], it would provide a template that could be used in defining the precise conformation of the structural repeat required for the induction of desired antibodies that can neutralize parasites. Conclusions Over the past 25 years the antibody response against the PfCSP repeat epitope has been pursued as a target for active vaccination, with encouraging results [47]. Our attempt to dissect the protective antibody response against the structural PfCSP repeat revealed that the response was restricted to a single VH/VL pairing, designated PfNPNA-1 encoded by VH3 and Vκ I families (with evidence of somatic mutations). The affinity for the ligand was in the μM range, which in the context of a whole antibody may be more than sufficient for retention on a polyvalent surface such as the P. falciparum CSP. It is speculated that the induction and the maintenance of high circulating levels of antibodies against the structural PfCSP repeat may be more important than intrinsic high affinity for the ligand for protection against P. falciparum infection. The absence of high affinity anti-repeat antibodies is in concordance with the expected response against a multivalent antigen (i.e. sporozoite surface). Under physiological conditions a whole IgG antibody and a multimeric ligand result in bivalent binding. Such complexes can have avidities estimated to be approaching the product of two independent monomeric interactions. In this case, the 1 × 10-6M monovalent affinity of PfNPNA-1 may approach a theoretical higher avidity (1 × 10-12 M) in the context of a whole antibody. This implies that further affinity maturation either in vivo or in vitro may not necessarily increase physiological effectiveness of the whole IgG antibody. Public health officials have acknowledged the urgency for development of an effective anti-P. falciparum malaria vaccine. One of the key criteria of such a putative vaccine may be the induction and maintenance of high levels of anti-(NPNA)n antibodies. The fully human PfNPNA-1 IgG could be used as a positive control in evaluating sera from immunized donors, or possibly be developed as a prophylactic agent that could be used alone or in combination with various vaccination strategies. One immediate hurdle for the development of such an antibody as a prophylactic would be the anticipated high cost of commercial manufacture in mammalian cells. However, advances in alternative antibody production technology may one day provide some more cost effective solutions [48,49]. With the availability of an antibody phage display library constructed from a protected individual immunized via bites of irradiated P. falciparum infected Anopheles mosquitoes, it should be possible to further dissect the antibody response against "other" sporozoite antigens [39]. Authors' contributions JAC was the postdoctoral researcher on this project. WOR and SLH co-investigators. ASK was the PI and recipient of the Department of Army award. All authors read and approved the final manuscript Disclaimer The views and opinions expressed herein are those of the author and do not purport to reflect those of the U.S. Navy or the Department of Defense, Sanaria Inc or Avanir Pharmaceuticals Inc. Acknowledgements Ms. Kiyoko Shimizu and Ms. Yan Su are thanked for administrative and technical assistance respectively and Dr Ritsuko-Sawada-Hirai for comments on the manuscript. The staff at Walter Reed Army Research Institute (WRAIR) and the Naval Medical Research Center (NMRC) (in particular donor WR5), Dr. Dan Gordon and his colleagues at WRAIR and NMRC carried out the immunizations of the volunteer, Dr. Robert Wirtz provided P. falciparum sporozoite slides and Dr. Ripley Ballou supplied R32tet32 and continued support, advice and guidance. Dr. David Milich (TSRI) provided the recombinant hepatitis nucleocapsid protein C75CS2. ASK was a recipient of an Investigators Award from the Cancer Research Institute/Partridge Foundation and this work was supported by the Department of the Army ARL No DAAL03-92-G-0215 and the Naval Medical Research and Development Command Work Unit 61102A3M161102BK13AK111. 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==== Front Ann Clin Microbiol AntimicrobAnnals of Clinical Microbiology and Antimicrobials1476-0711BioMed Central London 1476-0711-3-141528386410.1186/1476-0711-3-14ResearchEmerging resistance among bacterial pathogens in the intensive care unit – a European and North American Surveillance study (2000–2002) Jones Mark E 1mjones@focustechnologies.comDraghi Deborah C 1ddraghi@focustechnologies.comThornsberry Clyde 1cthornsberry@focustechnologies.comKarlowsky James A 1jkarlowsky@focustechnologies.comSahm Daniel F 1dsahm@focustechnologies.comWenzel Richard P 2rwenzel@mail2.vcu.edu1 Focus Technologies, Herndon, Virginia, USA 201712 Virginia Commonwealth University, Richmond, Virginia, USA2004 29 7 2004 3 14 14 4 6 2004 29 7 2004 Copyright © 2004 Jones et al; licensee BioMed Central Ltd.2004Jones et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background Globally ICUs are encountering emergence and spread of antibiotic-resistant pathogens and for some pathogens there are few therapeutic options available. Methods Antibiotic in vitro susceptibility data of predominant ICU pathogens during 2000–2 were analyzed using data from The Surveillance Network (TSN) Databases in Europe (France, Germany and Italy), Canada, and the United States (US). Results Oxacillin resistance rates among Staphylococcus aureus isolates ranged from 19.7% to 59.4%. Penicillin resistance rates among Streptococcus pneumoniae varied from 2.0% in Germany to as high as 20.2% in the US; however, ceftriaxone resistance rates were comparably lower, ranging from 0% in Germany to 3.4% in Italy. Vancomycin resistance rates among Enterococcus faecalis were ≤ 4.5%; however, among Enterococcus faecium vancomycin resistance rates were more frequent ranging from 0.8% in France to 76.3% in the United States. Putative rates of extended-spectrum β-lactamase (ESBL) production among Enterobacteriaceae were low, <6% among Escherichia coli in the five countries studied. Ceftriaxone resistance rates were generally lower than or similar to piperacillin-tazobactam for most of the Enterobacteriaceae species examined. Fluoroquinolone resistance rates were generally higher for E. coli (6.5% – 13.9%), Proteus mirabilis (0–34.7%), and Morganella morganii (1.6–20.7%) than other Enterobacteriaceae spp (1.5–21.3%). P. aeruginosa demonstrated marked variation in β-lactam resistance rates among countries. Imipenem was the most active compound tested against Acinetobacter spp., based on resistance rates. Conclusion There was a wide distribution in resistance patterns among the five countries. Compared with other countries, Italy showed the highest resistance rates to all the organisms with the exception of Enterococcus spp., which were highest in the US. This data highlights the differences in resistance encountered in intensive care units in Europe and North America and the need to determine current local resistance patterns by which to guide empiric antimicrobial therapy for intensive care infections. Intensive-care unitantibiotic susceptibility ==== Body Background Antimicrobial resistance has emerged as an important factor in predicting outcomes and overall resource use after infections in intensive care units (ICU) [1]. Globally ICUs are encountering emergence and spread of antibiotic-resistant pathogens. For some pathogens there are few therapeutic options available, e.g., vancomycin-resistant Enterococcus faecium. Awareness of these problems has been underscored with data from a number of surveillance studies aimed at improving the use of empiric therapy. In the United States there have been several national programs, which have focused on both the etiology of infections and resistance patterns of nosocomial or ICU infections including the National Nosocomial Infections Surveillance (NNIS) [2] and more recently an ICU-specific study examining the epidemiology of antimicrobial resistance, Project ICARE [3,4]. Stephen et al. collected strains from 28 ICUs from across the United States as part of the SENTRY Antimicrobial Surveillance Program in 2001 [5]. European data on the antimicrobial resistance of ICU pathogens has also been collected in several recent surveillance studies. A large prevalence survey of nosocomial infections in ICUs in 17 countries was published in 1995 [6], and more recently a number of nation-specific surveys were reported [7-9]. Several key points emerge: first, antimicrobial resistance among ICU pathogens is generally increasing, but variations do exist among different countries, probably due to individual antimicrobial use patterns; second, when new medical practices and alternative antimicrobials are introduced changes in the dominant microbial etiologies may emerge prompting novel empiric selections; and third, the standards of hygiene and infection control also vary across countries. Finally, appropriate therapy of ICU infections directed by local resistance data can have significant consequences for both patient and the healthcare system. It is against this background that local resistance surveillance programs are of most value in developing appropriate therapeutic guidelines for specific infections and patient types. For example, the recent modification to the American Thoracic Society guidelines for the treatment of hospital-acquired pneumonia [10] considered contemporary resistance data. Local surveillance data can be applied to other infections to assist in local formulary policy such as those governing treatment of nosocomial urinary tract infections [11]. This study using TSN program reports the antimicrobial resistance profiles of bacterial isolates from ICU patients in five countries during the period 2000–2002. The relevance of these recent nation-specific data will be discussed on a country-by-country basis, as part of improving and updating empiric therapeutic approaches to specific pathogens causing infections in the ICU setting according to each country. These surveillance programs help to maintain current knowledge of susceptibilities and relevant treatment options. Methods TSN Database – United States and Europe TSN is a queriable, real-time database that electronically assimilates daily antimicrobial susceptibility testing and patient demographic data from a network of geographically dispersed laboratories in the United States (283 hospital sites), France (63 hospital sites), Germany (169 hospital sites), Italy (48 hospital sites) and Canada (87 hospital sites) [12]. Laboratories included in TSN include those servicing university, community, and private hospitals with bed sizes ranging from 100 to >1000 beds. Routine diagnostic susceptibility testing results are collected daily from each participating laboratory. The methods used by these laboratories include VITEK (bioMérieux, St. Louis, MO), MicroScan (Dade-Microscan, Sacramento, CA), Sceptor and Pasco MIC/ID (Becton Dickinson, Sparks, MD) and Etest (AB Biodisk, Solna, Sweden), as well as manual broth microdilution MIC, disk diffusion and agar dilution. TSN reflects current testing in participant laboratories and represents the data reported to physicians from the respective laboratories [13]. Although some European countries have alternate breakpoints, all data forwarded to TSN Databases are derived from hospitals that utilized NCCLS standards and definitions (United States, Canada, Italy, and Germany) [14] or the Comité de L'Antibiogramme de La Societé Français de Microbiologie (France) [15] thus standardizing datasets. Results were interpreted as susceptible, intermediate (if available), or resistant in TSN, based upon the NCCLS interpretative guidelines in place during 2001 [16]. In addition, a series of quality-control filters (i.e., critical rule sets) were used in TSN to screen susceptibility test results for patterns indicative of testing error and suspect results were removed from analysis for laboratory confirmation. In TSN, any result from the same patient with the same organism identification and the same susceptibility pattern received within five days was considered a repeat culture and was counted only once in the database. Bacterial species and antimicrobials tested For this study, data from TSN results for each individual database from January 1, 2000 through to December 31, 2002 were included in the analysis to determine the proportion of species and their susceptibility to antimicrobial agents commonly tested in clinical laboratories throughout the participating regions. Only isolates derived from patients located in hospital ICUs were considered in the analysis. Gram-positive species included in the analysis were comprised of S. aureus, coagulase negative staphylococci, Enterococcus faecalis,Enterococcus faecium, Streptococcus pyogenes, Streptococcus pneumoniae and viridans group streptococci. Gram-negative species studied comprised the predominantly encountered enteric species (Escherichia coli, Klebsiella oxytoca, Klebsiella pneumoniae, Proteus mirabilis, Morganella morganii and Serratia marcescens), and Pseudomonas aeruginosa and Acinetobacter spp. The antibiotics studied are listed in Tables 2,3,4,5. Among E. coli, putative ESBL production was defined as those isolates that were intermediate or resistant (non-susceptible) to ceftazidime [17]. Given the large number of isolate results included in the majority of analyses in this study, statistical analysis was not performed, as even subtle differences in percent resistance (<1%) to an antimicrobial agent for any time period or demographic parameters would be reported as highly significant (P <0.001). Table 2 S. aureus, Coagulase-negative staphylococci, E. faecalis, and E. faecium isolated from ICU patients during 2000–2002 United States Canada Italy Germany Francea Organism Agent Total n %S %R Total n %S %R Total n %S %R Total n %S %R Total n %S %R Staphylococcus aureus Ampicillin 19,703 6.7 93.3 3,792 12.6 87.4 1,665 5.6 94.4 2,867 16.2 83.8 15 6.7 93.3 Cefepime 1,260 52.9 46.9 NTb NT NT 304 15.8 84.2 483 80.5 17.0 <10 NAc> NA Cefotaxime 6,898 50.2 49.7 220 55.5 44.5 671 36.4 63.6 729 92.0 8.0 490 63.9 36.1 Ceftriaxone 5,914 45.6 54.3 153 69.3 30.7 1,048 28.1 71.8 220 88.6 11.4 23 73.9 26.1 Ciprofloxacin 24,350 47.4 51.0 5,958 74.5 24.1 4,600 39.7 58.6 5,243 73.4 26.1 316 57.0 40.5 Gentamicin 35,034 85.6 13.7 6,641 89.4 10.3 5,531 40.9 58.0 5,735 90.0 9.7 10,100 90.4 9.4 Oxacillin 44,939 47.7 52.3 10,105 80.3 19.7 6,147 40.6 59.4 6,475 79.0 21.0 10,512 59.4 40.6 Teicoplanin NT NT NT NT NT NT 5,868 100 0 4,632 99.8 0.2 8,232 100 0 Vancomycin 43,245 100 0 7,882 100 0 5,937 100 0 5,276 100 0 9,453 100 0 Staphylococcus aureus OSSA Ampicillin 9,047 14.5 85.5 3,055 15.7 84.3 741 12.6 87.4 2,414 19.3 80.7 10 0 100 Cefepime 672 99.1 0.4 NT NT NT 49 98.0 2.0 387 99.5 0.3 NT NT NT Cefotaxime 3,451 99.7 0.2 122 100 0 244 100 0 653 100 0 312 100 0 Ceftriaxone 2,707 99.5 0.2 106 100 0 295 99.0 0.3 194 100 0 16 100 0 Ciprofloxacin 11,827 91.2 6.5 4,692 93.5 4.8 1,902 91.4 4.9 4,171 91.4 8.0 188 90.4 6.4 Gentamicin 16,951 98.3 1.4 5,384 98.1 1.8 2,223 95.1 4.5 4,527 98.4 1.5 5,958 99.4 0.5 Oxacillin 21,416 100 0 8,110 100 0 2,495 100 0 5,115 100 0 6,244 100 0 Teicoplanin NT NT NT NT NT NT 2,402 100 0 3,593 99.9 0.1 5,018 100 0 Vancomycin 20,110 100 0 6,046 100 0 2,430 100 0 4,002 100 0 5,580 100 0 Staphylococcus aureus ORSA Ampicillin 10,656 0 100 737 0 100 924 0 100 453 0 100 <10 NA NA Cefepime 588 0 100 NT NT NT 255 0 100 96 4.2 84.4 <10 NA NA Cefotaxime 3,447 0.6 99.3 98 0 100 427 0 100 76 23.7 76.3 178 0.6 99.4 Ceftriaxone 3,207 0 100 47 0 100 753 0.3 99.7 26 3.8 96.2 <10 NA NA Ciprofloxacin 12,523 6.1 93.1 1,266 3.9 95.5 2,698 3.3 96.4 1,072 3.3 96.6 128 7.8 90.6 Gentamicin 18,083 73.7 25.2 1,257 52.0 46.8 3,308 4.5 94.0 1,208 58.7 40.5 4,142 77.5 22.2 Oxacillin 23,523 0 100 1,995 0.2 99.8 3,652 0 100 1,360 0 100 4,268 0 100 Teicoplanin NT NT NT NT NT NT 3,466 100 0 1,039 99.7 0.3 3,214 100 0 Vancomycin 23,135 100 0 1,836 100 0 3,507 100 0 1,274 100 0 3,873 100 0 Staphylcoccus species, coagulase-negative Ampicillin 16,288 5.7 94.3 3,533 6.3 93.7 2,142 10.6 89.4 4,075 8.1 91.9 <10 NA NA Cefepime 991 11.8 88.1 <10 NA NA 116 0 100 625 11.0 73.1 <10 NA NA Cefotaxime 5,538 17.7 82.3 240 17.9 82.1 335 16.7 83.3 625 37.4 62.4 174 28.7 69.0 Ceftriaxone 3,471 14.8 84.8 116 22.4 77.6 512 11.7 88.3 412 25.0 74.8 <10 NA NA Ciprofloxacin 18,829 40.2 58.3 5,366 44.4 54.7 5,102 42.7 54.0 6,197 29.5 67.6 198 44.4 53.0 Gentamicin 27,248 51.5 38.1 5,571 40.6 47.3 5,241 33.8 60.7 6,848 41.5 51.7 9,422 46.8 51.5 Oxacillin 35,135 15.8 84.2 9,172 20.6 79.4 5,961 15.2 84.8 7,442 18.6 81.4 9,884 30.1 69.9 Teicoplanin NT NT NT NT NT NT 5,797 93.7 2.4 5,096 95.6 0.7 7,670 84.6 3.1 Vancomycin 34,424 100 0 8,239 100 0 5,937 100 0 6,953 100 0 8,300 100 0 Staphylcoccus species, coagulase-negative Oxacillin susceptible Ampicillin 2,582 35.7 64.3 638 34.6 65.4 437 51.7 48.3 824 39.6 60.4 <10 NA NA Cefepime 117 100 0 NT NT NT NT NT NT <10 NA NA NT NT NT Cefotaxime 978 99.5 0.2 42 100 0 56 100 0 128 100 0 54 92.6 0 Ceftriaxone 523 98.3 0.4 26 100 0 59 100 0 103 100 0 <10 NA NA Ciprofloxacin 2,844 82.4 16.6 988 91.8 7.6 779 87.7 10.1 1,103 89.5 9.2 78 83.3 14.1 Gentamicin 4,424 93.5 4.2 1,068 91.9 5.3 698 94.3 5.3 1,263 96.5 2.7 2,822 93.9 5.4 Oxacillin 5,565 100 0 1,886 99.9 0.1 904 100 0 1,383 100 0 2,980 100 0 Teicoplanin NT NT NT NT NT NT 890 99.1 0.3 691 98.4 0.3 2,454 95.8 0.2 Vancomycin 5,240 100 0 1,587 100 0 897 100 0 981 100 0 2,467 100 0 Staphylcoccus species, coagulase-negative Oxacillin resistant Ampicillin 13,706 0.1 99.9 2,895 0 100 1,705 0 100 3,251 0.2 99.8 <10 NA NA Cefepime 874 0 99.9 <10 NA NA 116 0 100 624 10.9 73.2 <10 NA NA Cefotaxime 4,560 0.1 99.9 198 0.5 99.5 279 0 100 497 21.3 78.5 120 0 100 Ceftriaxone 2,948 0 99.8 90 0 100 453 0.2 99.8 309 0.0 99.7 <10 NA NA Ciprofloxacin 15,985 32.7 65.8 4,378 33.7 65.3 4,323 34.7 61.9 5,094 16.5 80.2 120 19.2 78.3 Gentamicin 22,824 43.3 44.7 4,503 28.5 57.3 4,543 24.5 69.2 5,585 29.1 62.8 6,600 26.6 71.3 Oxacillin 29,570 0 100 7,286 0 100 5,057 0 100 6,059 0 100 6,904 0 100 Teicoplanin NT NT NT NT NT NT 4,907 92.7 2.8 4,405 95.1 0.8 5,216 79.3 4.5 Vancomycin 29,184 100 0 6,652 100 0 5,040 100 0 5,972 100 0 5,833 100 0 Enterococcus faecalis Ampicillin 7,865 98.8 1.2 1,000 99.4 0.6 1,289 95.3 4.7 1,902 99.6 0.4 1,183 99.5 0.2 Ciprofloxacin 3,311 56.9 38.7 625 45.3 50.4 1,159 64.0 31.1 2,012 39.7 39.5 559 78.5 17.0 Gentamicin (HL Testing) 5,503 65.1 34.8 706 63.0 36.8 1,156 62.9 37.1 965 64.8 35.2 1,563 63.6 13.4 Teicoplanin NT NT NT <10 NA NA 1,248 97.1 2.4 1,294 99.7 0.2 1,747 99.9 0.1 Vancomycin 7,656 95.1 4.5 1,005 98.3 0.9 1,303 96.7 2.8 1,636 99.4 0.3 1,811 99.7 0.2 Enterococcus faecium Ampicillin 3,896 9.7 90.3 383 17.2 82.8 260 21.5 78.5 481 12.3 87.7 151 41.7 49.7 Ciprofloxacin 1,846 5.3 92.5 221 10.9 85.5 234 10.3 77.4 591 6.9 73.9 66 21.2 39.4 Gentamicin (HL Testing) 2,512 57.5 42.5 291 59.5 40.5 223 67.7 32.3 349 60.2 39.8 263 65.4 12.2 Teicoplanin 23 8.7 87.0 <10 NA NA 234 86.3 13.7 517 97.9 2.1 266 99.6 0.4 Vancomycin 4,066 23.2 76.3 415 85.1 14.5 264 75.4 24.2 628 93.9 4.8 247 98.4 0.8 aNCCLS breakpoints were used for all countries, except (CA-SFM) bNot tested cNot applicable if <10 isolates were tested Table 3 S. pneumoniae, S. pyogenes, S. agalactiae, and Viridans group streptococci isolated from ICU patients during 2000–2002 United States Canada Italy Germany Francea Organism Agent Total n %S %R Total n %S %R Total n %S %R Total n %S %R Total n %S %R Streptococcus pneumoniae Amoxicillin 120 91.7 2.5 31 100 0 60 93.3 6.7 17 100 0 1,328 71.2 2.3 Cefepime 22 90.9 4.5 25 60.0 12.0 66 90.9 7.6 NTb NT NT <10 NAc NA Cefotaxime 1,571 82.2 6.3 145 93.8 0.7 108 93.5 4.6 63 100 0 1,181 77.1 0.8 Ceftriaxone 2,373 88.3 3.2 145 91.7 0.7 145 91.7 3.4 29 100 0 544 80.1 0.6 Clarithromycin 184 71.7 25.5 56 69.6 30.4 90 64.4 31.1 <10 NA NA NT NT NT Erythromycin 3,029 67.9 30.5 539 78.5 20.8 313 69.6 28.1 405 88.6 9.4 1,567 59.0 38.8 Levofloxacin 2,133 99.1 0.4 356 98.6 1.1 174 98.3 0.6 340 99.4 0.3 62 98.4 1.6 Penicillin 3,096 51.5 20.2 325 59.1 7.1 198 77.3 7.6 102 96.1 2.0 1,387 45.5 17.9 Vancomycin 2,865 100 -c 271 100 - 231 100 - 190 100 - 1,479 100 - Streptococcus pyogenes Amoxicillin NT NT NT NT NT NT NT NT NT NT NT NT 58 100 0 Cefepime <10 NA NA NT NT NT NT NT NT NT NT NT NT NT NT Cefotaxime 32 100 - 29 100 - <10 NA NA 11 100 - 30 100 - Ceftriaxone 75 100 - <10 NA NA <10 NA NA <10 NA NA <10 NA NA Clarithromycin 19 84.2 5.3 <10 NA NA 17 88.2 11.8 NT NT NT NT NT NT Erythromycin 118 92.4 6.8 102 81.4 11.8 59 74.6 23.7 63 84.1 11.1 170 82.9 14.7 Levofloxacin 71 97.2 1.4 <10 NA NA <10 NA NA 61 77.0 4.9 NT NT NT Penicillin 140 100 - 97 100 - 58 100 - 64 100 - 139 100 - Vancomycin 121 100 - 42 100 - 12 100 - 34 100 - 162 100 - Streptococcus agalactiae Amoxicillin NT NT NT NT NT NT NT NT NT NT NT NT 165 100 0 Cefepime 28 100 - NT NT NT <10 NA NA NT NT NT NT NT NT Cefotaxime 71 100 - 17 100 - 24 100 - 50 100 - 50 100 - Ceftriaxone 184 100 - <10 NA NA 38 100 - 37 100 - <10 NA NA Clarithromycin 21 81.0 9.5 <10 NA NA 21 71.4 28.6 NT NT NT <10 NA NA Erythromycin 489 76.3 21.7 222 82.9 14.9 121 77.7 18.2 192 83.9 10.9 588 79.9 16.2 Levofloxacin 333 97.9 1.2 <10 NA NA 51 98.0 0 180 91.1 1.7 173 99.4 0 Penicillin 518 100 - 226 100 - 145 100 - 184 100 - 369 100 - Vancomycin 463 100 - 179 100 - 143 100 - 65 100 - 526 100 - Streptococcus viridans group Amoxicillin NT NT NT NT NT NT NT NT NT NT NT NT 268 92.9 0.7 Cefepime 23 95.7 4.3 NT NT NT 12 66.7 33.3 NT NT NT NT NT NT Cefotaxime 434 83.6 11.1 101 92.1 4.0 31 90.3 9.7 75 97.3 2.7 56 94.6 0 Ceftriaxone 678 87.3 7.7 130 89.2 3.8 99 81.8 18.2 40 97.5 2.5 <10 NA NA Clarithromycin 34 52.9 38.2 21 76.2 19.0 21 71.4 23.8 <10 NA NA NT NT NT Erythromycin 959 57.2 37.7 289 71.6 23.2 192 64.6 32.8 796 88.1 9.2 626 59.9 31.6 Levofloxacin 331 96.1 2.7 <10 NA NA 16 87.5 0 93 89.2 4.3 <10 NA NA Penicillin 1,047 63.7 6.2 303 79.2 0 61 78.7 8.2 <10 NA NA 452 69.0 3.1 Vancomycin 1,095 100 - 276 100 - 180 100 - 277 100 - 580 100 - aNCCLS breakpoints were used for all countries, except France (CA-SFM) bNot tested cBreakpoints do not currently exist to interpret as S (susceptible) or R (resistant) Table 4 Enterobacteriaceae isolated from ICU patients during 2000–2002 United States Canada Italy Germany Francea Organism Agent Total n %S %R Total n %S %R Total n %S %R Total n %S %R Total n %S %R Escherichia coli Cefepime 10,356 98.1 1.5 207 98.1 1.9 1,426 98.1 1.4 2,830 98.6 1.2 4,358 98.9 0.6 Cefotaxime 9,086 96.5 2.2 3,231 96.3 2.5 1,748 94.5 3.8 5,828 97.8 1.8 9,362 98.8 0.6 Ceftazidime 14,574 95.3 3.0 4,438 97.7 1.6 2,548 94.7 3.7 3,924 97.9 1.6 9,164 97.8 1.2 Ceftriaxone 15,897 97.4 1.7 3,829 96.8 2.2 1,423 94.4 4.2 534 99.8 0.2 834 98.6 1.0 Ciprofloxacin 17,294 89.0 10.7 5,028 90.3 9.5 2,616 87.0 12.7 4,615 86.7 12.4 8,577 93.1 6.5 Gentamicin 20,581 92.4 6.5 6,654 92.8 5.3 2,650 92.2 6.6 4,825 94.3 5.2 9,442 95.4 4.2 Imipenem 15,353 100 0 3,386 100 0 2,254 100 0 5,172 100 0 8,994 100 0 Levofloxacin 14,920 88.2 11.6 776 85.1 13.9 496 86.5 13.3 3,137 88.2 11.0 NTb NT NT Piperacillin-tazobactam 13,573 93.1 3.6 4,305 95.1 2.4 1,879 95.8 2.4 5,637 93.6 3.4 7,255 95.4 1.1 Trimethoprim-sulfamethoxazole 20,296 79.2 20.7 6,737 84.6 15.3 2,440 75.0 24.9 5,598 73.1 26.6 9,028 78.2 21.1 Klebsiella oxytoca Cefepime 1,476 96.2 3.3 19 100 0 255 99.6 0 566 96.8 2.7 478 97.1 0.4 Cefotaxime 1,324 92.7 4.7 486 94.2 4.5 230 96.5 1.7 1,117 93.8 4.4 865 96.3 0.8 Ceftazidime 1,909 91.7 7.0 661 94.9 4.1 361 83.4 15.2 749 95.3 4.5 870 98.3 0.5 Ceftriaxone 2,035 89.9 6.6 536 93.8 2.8 197 81.7 2.0 83 97.6 0 79 87.3 2.5 Ciprofloxacin 2,226 92.5 5.9 745 96.0 3.0 368 96.7 3.0 905 90.1 7.8 815 94.5 4.8 Gentamicin 2,569 89.9 8.3 857 95.0 4.9 366 89.6 3.0 1,016 98.2 1.2 865 97.1 2.4 Imipenem 2,061 100 0 516 100 0 337 100 0 1,062 100 0 845 100 0 Levofloxacin 1,754 93.3 3.4 159 96.9 1.3 133 97.0 3.0 560 94.6 3.2 NT NT NT Piperacillin-tazobactam 1,801 82.7 13.9 624 91.2 7.1 313 81.8 11.2 1,113 78.9 18.1 742 88.3 10.4 Trimethoprim-sulfamethoxazole 2,467 92.5 7.5 863 96.3 3.6 308 95.1 4.9 1,084 93.7 6.3 802 94.1 5.7 Klebsiella pneumoniae Cefepime 7,276 95.8 3.4 98 100 0 552 93.5 5.6 1,068 95.7 3.5 840 95.6 3.0 Cefotaxime 6,243 91.0 6.1 1,411 97.9 1.5 850 76.7 16.4 2,414 93.1 6.0 1,553 94.4 1.9 Ceftazidime 9,597 88.5 10.1 2,238 97.5 2.2 1,142 69.8 28.5 1,665 90.0 8.2 1,591 92.5 5.2 Ceftriaxone 10,337 92.7 4.7 1,736 97.9 1.1 816 75.2 15.0 166 98.8 0.6 112 86.6 5.4 Ciprofloxacin 11,089 89.9 8.4 2,484 91.8 7.2 1,190 88.2 9.9 2,128 85.4 9.4 1,473 89.5 8.7 Gentamicin 13,012 91.6 7.0 2,906 96.7 2.9 1,211 81.4 14.5 2,065 91.6 6.1 1,553 97.1 2.7 Imipenem 10,263 100 0 1,766 100 0 1,066 100 0 2,351 100 0 1,567 100 0 Levofloxacin 9,626 91.0 6.4 485 93.4 3.7 287 78.4 21.3 1,228 92.6 4.4 NT NT NT Piperacillin-tazobactam 9,359 85.9 7.4 2,160 91.5 2.7 746 82.2 14.6 2,408 84.9 8.3 1,286 89.4 5.1 Trimethoprim-sulfamethoxazole 12,641 88.6 11.1 2,924 92.8 7.1 1,103 82.0 18.0 2,324 82.2 17.2 1,443 88.2 10.9 Morganella morganii Cefepime 566 95.9 2.3 <10 NA NA 121 97.5 2.5 262 94.7 5.0 412 96.1 0.2 Cefotaxime 499 78.8 8.4 156 91.0 3.8 144 74.3 6.3 437 86.7 3.9 678 81.1 5.9 Ceftazidime 715 73.6 17.3 256 79.7 10.9 213 75.6 15.0 313 84.0 7.7 673 78.6 8.0 Ceftriaxone 806 91.1 2.2 219 96.3 1.4 125 91.2 3.2 22 86.4 0 57 84.2 5.3 Ciprofloxacin 841 78.1 20.7 292 94.2 4.5 220 87.3 9.5 344 97.7 2.0 634 88.6 8.5 Gentamicin 967 84.0 14.1 329 94.5 4.6 222 90.1 8.6 378 96.8 2.1 679 95.6 3.4 Imipenem 784 100 0 196 100 0 206 100 0 402 100 0 649 99.8 0 Levofloxacin 725 78.1 19.3 42 95.2 4.8 55 90.9 9.1 251 98.0 1.6 NT NT NT Piperacillin-tazobactam 725 91.2 5.1 254 97.2 1.6 150 94.0 3.3 430 94.2 3.5 564 91.0 4.6 Trimethoprim-sulfamethoxazole 936 75.1 24.7 329 91.8 8.2 193 79.8 20.2 435 93.1 6.9 627 83.9 14.2 Proteus mirabilis Cefepime 1,964 98.2 1.0 20 100 0 395 87.6 11.4 599 99.2 0.8 736 99.0 0.1 Cefotaxime 1,794 99.1 0.5 295 99.7 0 441 69.4 23.4 1,209 98.8 0.7 1,503 99.5 0.1 Ceftazidime 2,684 98.0 1.1 463 99.4 0.2 630 86.0 9.4 821 98.5 1.0 1,505 99.3 0.2 Ceftriaxone 3,034 99.4 0.3 392 99.5 0 385 80.5 13.8 77 98.7 0 72 100 0 Ciprofloxacin 3,169 85.2 12.7 504 95.2 4.6 657 70.6 22.7 980 92.9 5.1 1,424 90.9 6.8 Gentamicin 3,796 91.5 7.7 698 92.6 7.2 670 61.6 37.2 992 92.9 5.9 1,509 91.3 7.9 Imipenem 2,850 100 0 367 100 0 580 100 0 1,020 100 0 1,319 100 0 Levofloxacin 2,825 87.8 10.5 94 100 0 202 61.9 34.7 688 96.5 2.3 <10 NAc NA Piperacillin-tazobactam 2,715 97.7 0.8 449 98.2 0.2 465 95.7 2.8 1,201 98.6 0.8 1,231 99.3 0.2 Trimethoprim-sulfamethoxazole 3,706 85.2 14.7 708 89.4 10.6 615 61.6 38.0 1,159 80.8 19.1 1,411 79.7 18.6 Serratia marcescens Cefepime 3,653 96.7 2.3 52 96.2 1.9 497 96.8 2.2 546 94.1 3.5 509 98.6 0.2 Cefotaxime 3,134 87.0 5.7 670 92.8 2.7 470 79.6 9.8 951 84.0 7.5 809 81.5 3.3 Ceftazidime 4,718 89.7 7.9 1,113 95.2 3.0 738 81.4 13.3 851 89.7 7.5 812 94.7 3.0 Ceftriaxone 4,710 90.5 4.6 846 95.4 1.7 444 86.7 6.3 160 45.6 0 115 77.4 4.3 Ciprofloxacin 5,006 91.0 6.7 1,292 85.0 11.7 757 83.5 4.5 978 72.6 12.4 787 78.9 10.5 Gentamicin 5,905 92.9 5.9 1,313 94.6 5.2 758 97.4 2.1 665 92.9 6.3 808 91.6 6.6 Imipenem 4,960 100 0 880 100 0 727 100 0 1,018 100 0 805 100 0 Levofloxacin 4,356 94.3 4.2 264 92.4 4.2 266 95.5 1.5 595 87.6 6.6 <10 NA NA Piperacillin-tazobactam 4,337 88.1 5.1 1,155 91.6 3.3 547 92.7 3.8 1,053 77.6 3.1 749 82.6 2.4 Trimethoprim-sulfamethoxazole 5,697 95.9 3.9 1,325 94.9 5.1 646 81.4 18.6 908 88.1 10.9 699 84.1 13.6 aNCCLS breakpoints were used for all countries, except France (CA-SFM) bNot tested cNot applicable if <10 isolates were tested Table 5 P. aeruginosa and Acinetobacter spp isolated from ICU patients during 2000–2002 United States Canada Italy Germany France Organism Agent Total n %S %R Total n %S %R Total n %S %R Total n %S %R Total n %S %R Acinetobacter species Cefepime 5,162 43.8 40.2 97 67.0 23.7 475 17.9 73.7 623 74.2 10.8 857 28.0 40.3 Cefotaxime 3,830 23.3 49.9 705 36.7 34.9 555 11.0 78.7 1,254 34.9 24.6 671 15.4 38.7 Ceftazidime 5,954 42.2 40.8 1,162 70.8 22.9 692 25.6 68.5 988 66.7 14.5 1,106 34.9 35.5 Ceftriaxone 4,709 16.3 55.9 874 32.4 28.7 452 8.8 72.6 104 42.3 11.5 81 9.9 51.9 Ciprofloxacin 5,808 39.7 58.0 1,156 72.1 25.9 686 21.1 76.7 1,126 74.8 22.9 1,038 37.7 61.2 Gentamicin 6,618 47.2 47.2 1,185 72.8 22.8 768 23.3 72.4 979 82.0 14.1 936 49.3 43.5 Imipenem 6,006 87.0 7.5 918 95.8 1.9 569 77.9 19.0 1,253 96.2 3.4 1,088 93.8 3.8 Levofloxacin 5,099 43.8 52.2 489 61.1 25.6 295 13.9 75.3 840 82.0 10.5 NTb NT NT Meropenem 2,154 66.3 26.5 348 93.7 4.9 455 74.5 13.6 1,024 96.0 3.4 147 68.0 28.6 Piperacillin 4,658 35.4 45.9 959 66.5 19.5 635 19.5 69.9 1,171 59.7 12.9 805 35.0 50.3 Piperacillin-tazobactam 3,429 53.6 28.5 903 70.7 23.1 425 35.1 46.4 1,225 81.8 7.5 878 74.5 10.5 Trimethoprim-sulfamethoxazole 5,697 51.4 48.4 1,155 74.8 25.2 750 44.1 55.7 1,234 83.6 15.6 93 45.2 52.7 Pseudomonas aeruginosa Cefepime 20,220 72.5 12.4 371 73.3 12.4 5,056 58.9 28.9 3,483 80.3 7.8 7,967 52.6 16.2 Cefotaxime 11,283 9.2 50.4 1,836 13.3 47.5 4,181 6.0 70.7 2,689 7.7 52.2 NT NT NT Ceftazidime 26,353 71.2 17.4 6,036 73.7 13.4 7,640 56.7 31.3 5,141 76.2 14.9 8,547 70.2 14.9 Ceftriaxone 14,066 12.1 56.4 2,847 11.3 59.7 3,383 8.4 70.4 154 26.6 7.8 NT NT NT Ciprofloxacin 26,700 62.8 33.1 5,924 67.2 30.2 7,388 58.4 38.8 4,746 68.6 24.4 8,560 55.3 40.6 Gentamicin 29,268 69.4 21.5 5,951 72.2 15.9 7,522 52.2 41.7 3,913 74.0 14.3 7,327 44.0 46.1 Imipenem 26,076 73.5 22.1 3,775 77.9 18.2 7,057 59.7 27.8 4,412 70.5 19.0 8,575 69.5 21.4 Levofloxacin 21,059 62.7 31.7 713 56.8 33.5 2,427 44.9 51.0 2,953 68.0 23.9 NT NT NT Meropenem 7,540 76.0 18.2 1,266 80.3 14.5 4,082 57.3 32.7 4,351 77.8 13.8 1,818 81.1 6.4 Piperacillin 22,855 77.7 22.2 5,520 80.9 18.8 7,004 63.1 36.7 4,554 81.7 14.1 8,454 64.1 24.1 Piperacillin-tazobactam 21,848 85.5 14.4 4,190 91.0 9.0 5,252 77.7 22.0 4,746 85.8 10.7 8,256 69.6 15.9 Trimethoprim-sulfamethoxazole 15,618 3.6 96.4 4,283 4.0 96.0 7,054 4.1 95.8 3,375 4.2 95.8 NT NT NT aNCCLS breakpoints were used for all countries, except France (CA-SFM) bNT = not tested Results In vitro susceptibility data from over 220,000 isolates from ICUs in five countries over the period 2000–2002 were assimilated. The most frequent species isolated from infections in the ICU was S. aureus, being most common in three of the five countries (Table 1). The oxacillin resistance rates among S. aureus varied markedly across countries from 19.7% in Canada to 59.5% in Italy. E. coli (7.7%–15.5%) and P. aeruginosa (10.8%–22.3%) were the most frequent Gram-negative organisms encountered. The Gram-positive genus Enterococcus, either as E. faecalis, E. faecium or non-speciated isolates accounted for <10% of isolates in most countries with E. faecalis being the most common species <4.3%. Community-acquired respiratory pathogens such as Streptococcus pneumoniae and Haemophilus influenzae were relatively uncommon in all five countries. Table 1 Incidence of pathogens isolated from ICU patients by country (%) United States Canada Italy Germany France Organism Incidence (%) Organism Incidence (%) Organism Incidence (%) Organism Incidence (%) Organism Incidence (%) S. aureusa 20.2 S. aureusa 17.4 P. aeruginosa 22.3 CNS 16.4 S. aureus1 17.2 CNSb 15.9 CNS 16.1 CNS 18.7 S. aureusa 13.6 CNS 16.7 P. aeruginosa 13.1 E. coli 12.6 S. aureusa 18.1 E. coli 12.3 E. coli 15.5 E. coli 9.2 P. aeruginosa 11.3 E. coli 7.7 P. aeruginosa 10.8 P. aeruginosa 13.8 K. pneumoniae 5.8 Enterococcus spp 7.6 E. faecalis 3.9 Enterococcus spp 7.4 S. pneumoniae 3.3 Enterococcus spp 5.4 K. pneumoniae 5.5 K. pneumoniae 3.5 K. pneumoniae 5.4 E. cloacae 3.3 E. cloacae 4.3 E. cloacae 4.2 Enterococcus spp 3.3 E. cloacae 4.7 E. faecalis 3.0 E. faecalis 3.7 S. marcenscens 2.5 E. cloacae 2.6 E. faecalis 4.3 K. pneumoniae 2.7 S. marcescens 2.7 H. influenzae 2.1 S. marcescens 2.2 P. mirabilis 2.6 P. mirabilis 2.5 A. baumanii 2.6 E. faecalis 2.1 P. mirabilis 1.9 K. oxytoca 2.4 Enterococcus spp 2.3 Enterobacteriaceaec (all species combined) 29.5 Enterobacteriaceae (all species combined) 33.0 Enterobacteriaceae (all species combined) 30.2 Enterobacteriaceae (all species combined) 36.0 Enterobacteriaceae (all species combined) 32.1 Total (n) 26,624 Total (n) 54,445 Total (n) 34,609 Total (n) 48,385 Total (n) 62,459 aProportion of S. aureus testing as MRSA was USA (52.3%), Canada (19.7%), Italy (59.4%), Germany (21.0%), and France (40.6%) bCNS = Coagulase-negative staphylococci cEnterobacteriaceae includes all species of genera occurring at >0.1% Tables 2,3,4,5 show the antimicrobial susceptibility profiles of various Gram-positive and Gram-negative pathogens isolated from ICU patients against a range of relevant antimicrobials. Specifically notable susceptibility patterns include the vancomycin susceptibility of all strains of staphylococci. Generally, there was a low proportion of vancomycin resistant E. faecalis <5%, whereas vancomycin-resistant E. faecium was more prevalent ranging from 0.8% in France to 76.3% in the United States, with a wide inter-country variation (Table 2). Penicillin resistance rates varied among S. pneumoniae, from 2.0% in Germany to 20.2% in the US with concurrent ceftriaxone resistance rates of 0% in Germany to 3.4% in Italy (Table 3). β-lactam activity was assessed by comparing four different cephalosporins and a β-lactam/β-lactamase inhibitor combination, piperacillin-tazobactam. Overall, the putative production of ESBLs among E. coli was low, <6%, but ceftazidime resistance was reported at higher rates in K. pneumoniae and S. marcescens, with the highest rates seen in M. morganii, from 16.0% in Germany to 26.4% in the United States (Table 4). Among the gram-negative organisms tested, ceftriaxone resistance rates were usually lower than ceftazidime, with the exception among P. aeruginosa and Acinetobacter spp. Cefepime, a fourth generation cephalosporin with anti-pseudomonal activity was also more active than ceftazidime (Table 5). Against the Enterobacteriaceae, the β-lactam combination agent piperacillin-tazobactam was generally less active than ceftriaxone. These species showed a wide variation in fluoroquinolone susceptibility among both species and countries. Gentamicin resistance rates among the Enterobacteriaceae varied from 1.2% among K. oxytoca from Germany to 37.2% in P. mirabilis from Italy. Ciprofloxacin resistance rates among E. coli ranged from 6.5% in France to 12.7% in Italy. Variable fluoroquinolone resistance rates among S. marcescens were also demonstrated, with a range of resistance from 4.5% in Italy to 12.4% in Germany. Discussion Data derived from international surveillance studies, such as those presented here, can provide a unique contemporary perspective on the susceptibility of commonly encountered organisms to commonly used antibiotics. Such surveillance systems play a crucial role in detecting emerging trends in resistance. Comparisons of these with data of other recent surveillance programs show the wide variations in susceptibility profiles and the need for ongoing unit-specific surveys. In Germany the prevalence of resistance among gram-positive organisms remained comparatively low with an incidence of 21% MRSA. In 2000, Frank et al. reported that 96% of German isolates of S. marcescens and M. morganii were susceptible to ceftazidime, yet in this study we found 89.7% and 84.0%, respectively [9]. A similar decrease in activity was noted with E. coli and ciprofloxacin between the two studies, 91% in 1996–1997 compared with 86.7% in this study. Marked decreases in susceptibility of P. aeruginosa in Germany were also evident, with no agent showing >85.8% susceptibility (piperacillin-tazobactam) compared with most agents having 85%–94% susceptibility in 1996–1997. Changes of 15–20% have been reported with ceftazidime, imipenem, ciprofloxacin and meropenem, while piperacillin-tazobactam has shown the smallest decrease in susceptibility with <6% over the 4-year period. Piperacillin plus or minus tazobactam and cefepime were the most active agents, based on susceptibility, against P. aeruginosa in Germany. Conversely, ceftriaxone and imipenem were the most active agents, based on susceptibility, against Klebsiella spp., which account for almost 8% of ICU isolates. Staphylococcal species from French ICU isolates showed a high proportion of oxacillin resistance, 40.6% and 69. 9% of S. aureus and coagulase-negative staphylococci spp., respectively. S. pneumoniae showed penicillin resistance of 17.9%, higher than the other four countries, although the activity of third-generation cephalosporins, ceftriaxone and cefotaxime, showed only 0.6% and 0.8% resistance, respectively. Despite a lower ceftazidime susceptibility breakpoint compared to NCCLS standards (MIC 4 μg/ml instead of 8 μg/ml) putative ESBL expression were slightly lower in France than in Germany in 2000–2002. Ceftazidime non-susceptibility rates among E. coli, K. oxytoca, and P. mirabilis were ≤ 2.2%; however, ceftazidime non-susceptibility rates among K. pneumoniae, M. morganii and S. marcescens were 7.5%, 21.4%, and 5.3%, respectively. Imipenem was active against all Enterobacteriaceae. Against P. aeruginosa and Acinetobacter spp., imipenem resistance rates were 21.4% and 3.8%, respectively. Previously, a lower imipenem resistance of 24% among French isolates of P. aeruginosa was reported [7]. Among the Italian isolates of staphylococci, oxacillin resistance occurred in 59.4% of S. aureus and 84.8% of coagulase-negative isolates. This MRSA rate was similar to that reported by Frank et al. from bacteremic isolates in Italy; however, they reported an increase in MRSA from 25% to 55% over the period 1997 to 2001 [18]. Vancomycin resistance rates of 2.8% for E. faecalis and 24.2% for E. faecium are some of the highest rates recorded in Europe, although still modest compared to rates experienced in the United States; however, teicoplanin was more active with 2.4% and 13.7% of strains being resistant, respectively. Pneumococcal resistance to penicillin and erythromycin was 7.6% and 28.1%, respectively. The impact of alterations in penicillin-binding protein that reduce penicillin susceptibility have less effect on the activity of third-generation cephalosporins such as ceftriaxone with 3.4% and cefotaxime with 4.6% resistance, respectively. S. pyogenes was fully susceptible to penicillin; however, 11.8% of isolates were resistant to clarithromycin and 23.7% were resistant to erythromycin. The proportion of ESBLs was slightly higher in Italy with E. coli showing ceftazidime non-susceptibility of 5.3%, whereas K. pneumoniae and K. oxytoca demonstrated 30.2% and 16.6% ceftazidime non-susceptibility, respectively. Fluoroquinolone resistance rates among the Enterobacteriaceae, using ciprofloxacin as a marker, varied from 3.0% for K. oxytoca to 22.7% for P. mirabilis, and 12.7% for E. coli. Thus, among Enterobacteriaceae, ciprofloxacin was generally less active than the third-generation cephalosporin, ceftriaxone. P. aeruginosa and Acinetobacter spp. strains from Italian ICUs demonstrated significant resistance rates. Isolates of P. aeruginosa showed resistance rates of >28% for all agents tested except piperacillin-tazobactam. Thus empiric therapy for possible pseudomonal infections will require combination therapy. Acinetobacter spp. showed a similar lack of susceptibility except to imipenem and meropenem (19.0% and 13.6% resistant). An increase in fluoroquinolone resistance in E. coli and K. pneumoniae in bacteremic isolates from Italy was observed during 1997–2001, with rates of 26.7% and 24%, respectively [9]. An increase in ureidopenicillin resistance was noted in P. aeruginosa isolates in Italy from 30% to 37% in a 4-year period [9]. This study showed 22.0% piperacillin-tazobactam and 36.7% piperacillin resistance among ICU P. aeruginosa isolates. In Canada oxacillin-resistance among S. aureus was noted in 19.7% and coagulase-negative staphylococci in 79.4%. Vancomycin resistance was reported among 0.9% and 14.5% of E. faecalis and E. faecium, respectively. The lowest rate of penicillin resistance in S. pneumoniae in this study was noted from Canada at 7.1%; however, clarithromycin resistance was 30.4%. Ceftriaxone showed 0.7% resistance whereas cefepime exhibited 12.0% resistance among pneumococci from the ICU. Overall the susceptibility rates for Gram-negative isolates from Canadian ICUs were higher than those in the other four countries examined. A low rate of ESBLs was reported, but there was variable activity of piperacillin-tazobactam which showed >9% resistance among Klebsiella spp. and S. marcescens tested. The rate of fluoroquinolone resistance was similar to those of other countries with E. coli showing 13.9% levofloxacin resistance. Among Enterobacteriaceae, <10% of most species were resistant to third-generation cephalosporins tested with the exception of ceftazidime and M. morganii. Resistance among P. aeruginosa and Acinetobacter spp. was generally lower than in other countries apart from Germany. Only piperacillin-tazobactam showed reliable activity against P. aeruginosa (9% resistant), while resistance to all other agents was >19%. Acinetobacter spp. remained susceptible to only the carbapenems, imipenem and meropenem. Comparison of the data from Canadian isolates with those from the United States shows some significant differences. This demonstrates the limitations of pooling Canadian and United States data since the differences between the two regions, such as the rate of MRSA, may have some impact on empiric therapy. Data from the NNIS system has previously reported an increasing trend towards resistance within ICUs in the United States [19]. Oxacillin resistance among staphylococci from ICUs in the United States was 52.3% and 84.2% for S. aureus and coagulase-negative species, respectively. This value is identical to that of S. aureus and very similar to the CNS data reported by the 1999 NNIS system. The NNIS highlighted a 37% increase in MRSA over the period 1994–98 to 1999, but only a 2% increase among CNS strains [4]. Vancomycin resistance in the United States was observed in 4.5% of E. faecalis; however, over 76% E. faecium were vancomycin non-susceptible. Although streptococci are uncommon ICU pathogens they can be rapidly invasive and possibly fatal unless adequate therapeutic approaches are adopted. S. pneumoniae in the United States has acquired a range of resistance mechanisms with resistance to penicillin and the macrolides, clarithromycin and erythromycin, being common, 20.2% and 25.5%–30.5% respectively. The newer generation cephalosporins, ceftriaxone, cefotaxime and cefepime showed good activity against pneumococci, 3.2%, 6.3% and 4.5% resistant, respectively. Less than 1.0% of isolates were resistant to levofloxacin. These data are similar to other recent reports [20]. For Enterobacteriaceae which account for approximately 30% of all isolates from ICU infections, the incidence of putative ESBLs was low in E. coli, 4.7% but ceftazidime non-susceptibility was higher in K. oxytoca 8.3%,K. pneumoniae 11.5%,S. marcescens 10.3% and M. morganii 26.4%. These data are consistent with other recent reports [21]. Fluoroquinolone resistance was observed in all Enterobacteriaceae tested, in the US for example, resistance rates were as follows, using ciprofloxacin as a marker: E. coli 10.7%, K. oxytoca 5.9%, K. pneumoniae 8.4%, M. morganii 20.7%, P. mirabilis 12.7% and S. marcescens 6.7%. These data show increased fluoroquinolone resistance compared with recent reports [21]. Jones et al. previously reported susceptibility data on ICU pathogens isolated over the period 1998–2001 [22]. Specifically, enteric bacteria showed changes over this time. Fluoroquinolone resistance doubled among E. coli isolates from 3.3–5.5% to 10.8–11.4% [22]. This study showed a generally higher level of activity among third-generation cephalosporins than other reports [23], with ceftriaxone showing <10% resistance rates against most species tested. Piperacillin-tazobactam showed less consistent activity with some species being >14% resistant, e.g. Klebsiella spp.,P. aeruginosa, and Acinetobacter spp. present significant therapeutic challenges in ICUs in the United States. With the exception of cefepime, all other tested antimicrobials demonstrated >12% resistance to P. aeruginosa, many considerably higher. Piperacillin-tazobactam showed the next lowest resistance rate, 14.4%, with all other agents having rates of 17% or higher. Non-susceptibility to ciprofloxacin among P. aeruginosa was 37.2%, higher than in the Neuberger report. Sahm et al. reported a 10% increase in fluoroquinolone resistance among P. aeruginosa in the United States, whereas resistance emerged more slowly with the other classes of antimicrobials tested [12]. Acinetobacter infections continue to present significant therapeutic challenges due to the extensive resistance mechanisms demonstrated by the >25% resistance shown in Table 5. Only imipenem has any reliable activity against Acinetobacter spp. with an 87% susceptibility rate. There are several implications of these data. It is essential that local surveillance programs be maintained in each country's ICU setting. The local data are vital to the formulary committees as they select appropriate agents to treat infections. There are clear differences among the five countries studied in this report. Although the predominant pathogens are similar, ongoing surveillance is essential to detect the emergence of resistant species. It is clear that certain classes of compounds are losing activity against the ICU pathogens tested. For example, the fluoroquinolones have reduced susceptibility among many Gram-negative species as well as staphylococci; however, the newer class members have enhanced activity against pneumococci. Advanced-generation cephalosporins have variable activity, with ceftriaxone showing consistently good activity against the Enterobacteriaceae and some staphylococci. Ceftazidime has lost potency due to the emergence of ESBL enzymes and also has diminished activity against P. aeruginosa. Piperacillin-tazobactam is generally active against P. aeruginosa in ICUs. The aminoglycoside, gentamicin has shown continued activity against most Enterobacteriaceae in all five countries, and modest activity against S. aureus but not against CNS strains. The gentamicin susceptibility of P. aeruginosa ranged from 44.0% in France to 74.0% in Germany, whereas Acinetobacter spp . showed more variable gentamicin susceptibility varying from 23.3% in Italy to 82.0% in Germany. These local data should be considered when treating infections in the ICU. Use of agents with anti-pseudomonal activity such as cefepime, piperacillin-tazobactam or the carbapenems should preferably be reserved for patient types or infections where this pathogen is present or risk factors exist, as per the ATS Community acquired-pneumonia guidelines [24]. A combination of a third-generation cephalosporin such as ceftriaxone with vancomycin may be appropriate for bloodstream infections based upon the NNIS etiology data from 1992–1999. Conclusions The current study confirmed the emergence of fluoroquinolone resistance among various Gram-negative species and staphylococci, which may be increasing due to the heightened use of these drugs; however the reported ESBL rates among Enterobacteriaceae was lower than noted in other studies and appeared to be stable. The prevalence of MRSA, perhaps the most significant resistant hospital pathogen, varied among the five countries and appeared to be increasing. Parenteral cephalosporins such as ceftriaxone and cefotaxime remained quite active against Enterobacteriaceae. Up-to-date susceptibility data should be made available as rapidly as possible to physicians so that appropriate targeted empirical therapy can be instituted, this approach can assist in maintaining the activity of the current antimicrobials. While local surveillance studies remain crucial, national surveillance studies such as this can provide an invaluable data source to provide guidance in formulary decision-making. Authors Contributions MJ conceived the study, provided data interpretation and drafted the manuscript. DD analyzed the study data; JK and DS provided expert microbiological analysis and interpretation of study data; RW provided clinical expertise in interpretation of data and drafting manuscript. All authors read and approved the final manuscript. Acknowledgments We thank F. Hoffmann-La Roche Ltd., Basel, Switzerland for financial support of this study. Additionally, we thank the many clinical microbiology laboratories around the world that contribute data to TSN Databases, without whom such studies would not be possible. ==== Refs Kollef MH Fraser VJ Antibiotic resistance in the Intensive Care Unit Ann Intern Med 2001 134 298 314 11182841 CDC NNIS system National nosocomial infections surveillance (NNIS) system report, data summary from January 1992-April issued August 2001 Amer J Infect Contr 2001 29 400 421 Correction 2002, 30:74 10.1067/mic.2001.118408 NNIS system report Intensive Care Antimicrobial Resistance Epidemiology (ICARE) Surveillance report, data summary from January 1996 through December 1997 Amer J Infect Contr 1999 27 279 284 10.1053/ic.1999.v27.a98878 Fridkin SK Steward CD Edwards JR Pryor ER McGowan JE Archibald LK Gaynes RP Tenover FC Surveillance of antimicrobial use and antimicrobial resistance in United States hospitals: Project ICARE Phase 2. Project Intensive Care Antimicrobial Resistance Epidemiology (ICARE) Hospitals Clin Infec Dis 1999 29 245 252 10476720 Stephen J Mutnick A Jones RN Assessment of pathogens and resistance (R) patterns among intensive care unit (ICU) in North America (NA): initial report from the SENTRY antimicrobial surveillance program (2001) Presented at the 42nd Interscience Conference on Antimicrobial Agents and Chemotherapy, San Diego, CA 2002 Abstract C2-297 Vincent JL Bihari DJ Suter PM Bruining HA White J Nicloas-Chaoin MH Wolff M Spencer RC Hemmer M The prevalence of nosocomial infection in intensive care units in Europe. Results of the European Prevalence of Infection in Intensive Care (EPIC) Study EPIC International Advisory Committee J Amer Med Assoc 1995 274 639 644 10.1001/jama.274.8.639 Hanberger H Garcia-Rodriguez JA Gobernado M the French and Portuguese ICU Study Groups Antibiotic susceptibility among aerobic Gram-negative bacilli in Intensive Care Units in 5 European countries JAMA 1999 281 67 71 9892453 10.1001/jama.281.1.67 Garcia-Rodriguez JA Jones RN the MYSTIC study group Antimicrobial resistance in gram-negative isolates from European intensive care units: data from the Meropenem Yearly Susceptibility Test Information Collection (MYSTIC) programme J Chem 2002 14 25 32 Frank U Jonas D Lupke T Ribeiro-Ayeh B Schmidt-Eisenlohr E Ruden H Daschner FD National Reference Centre Study Group on Antimicrobial Resistance Antimicrobial susceptibility among nosocomial pathogens isolated in intensive care units in Germany Eur J Clin Microbiol Infect Dis 2000 19 888 891 11152319 10.1007/s100960000389 Fiel S Guidelines and critical pathways for severe hospital-acquired pneumonia Chest 2001 119 412 418S 10.1378/chest.119.2_suppl.412S Laupland KB Zygun DA Davies HD Church DL Louie TJ Doig CJ Incidence and risk factors for acquiring nosocomial urinary tract infection in the critically ill J Crit Care 2002 17 50 57 12040549 10.1053/jcrc.2002.33029 Sahm DF Draghi DC Master RN Thonsberry C Jones ME Karlowsky JA Critchley IA Pseudomonas aeruginosa antimicrobial resistance update: US resistance trends from 1998 to 2001 Presented at the 42nd Interscience Conference on Antimicrobial Agents and Chemotherapy, San Diego, CA 2002 Abstract C2-305 Sahm DF Marsilio MK Piazza G Antimicrobial resistance in key bloodstream bacterial isolates: electronic surveillance with the surveillance network database – USA Clin Infect Dis 1999 29 259 263 10476722 National Committee for Clinical Laboratory Standards Methods for dilution antimicrobial tests for bacteria that grow aerobically; M7-A5 National Committee for Clinical Laboratory Standards, Wayne PA 2000 5 Société Française de Microbiologie, Institut Pasteur Comité de L' Antibiogramme De La Societé Française de Microbiologie Communiqué 2000-2001 (edition Janvier 2001) Société Française de Microbiologie, Institut Pasteur, 28, rue du Dr Roux, F 75724 Paris Cedex 15, France 2001 National Committee for Clinical Laboratory Standards Performance standards for antimicrobial susceptibility testing; Eleventh Informational Supplement, M100-S11 National Committee for Clinical Laboratory Standards, Wayne PA, USA 2001 Hadziyannis E Tuohy M Thomas L Procop GW Washington JA Hal GS Screening and confirmatory testing for extended spectrum β-lactamases (ESBL) in E. coli, Klebsiella pneumoniae and Klebsiella oxytoca clinical isolates Diagn Microbiol Infect Dis 2000 36 113 117 10705053 10.1016/S0732-8893(99)00117-0 Frank UK Daschner FD Leibovici L Antimicrobial susceptibility patterns of bacteremic isolates from university hospitals in Denmark, Germany, Italy and Israel Presented at the 42nd Interscience Conference on Antimicrobial Agents and Chemotherapy, San Diego, CA 2002 Abstract C2-301 Fridkin SK Increasing prevalence of antimicrobial resistance in intensive care units Crit Care Med 2001 29 64 68 10.1097/00003246-200104001-00002 Jones ME Blosser-Middleton RS Critchley IA Thornsberry C Karlowsky JA Sahm DF The activity of levofloxacin and comparator agents against clinical isolates of Streptococcus pneumoniae during 1999–2000 Chemotherapy 2002 48 232 237 12476039 10.1159/000066769 Neuberger MM Weinstein RA Rydman R Danzinger LH Quinn JP Antibiotic resistance among Gram-negative bacilli in US intensive care units. Implications for fluoroquinolone use J Amer Medical Assoc 2003 289 885 888 10.1001/jama.289.7.885 Jones ME Draghi DC Master RN Thornsberry C Karlowsky JA Critchley IA Sahm DF Trends in resistance among Enterobacteriaceae (isolated from in-patients and intensive-care unit patients in the US from 1998 to 2001 Presented at the 42nd Interscience Conference on Antimicrobial Agents and Chemotherapy, San Diego, CA 2002 Abstract C2-311 Friedland I Stinson L Ikaiddi M Harm S Woods G Resistance in Enterobacteriaceae: results of a multicenter US ICU surveillance study (ISS), 1995-2000 Presented at the 42nd Interscience Conference on Antimicrobial Agents and Chemotherapy, San Diego, CA 2002 Abstract C2-313 Guidelines for the Management of Adults with Community-acquired Pneumonia Am J Respir Crit Care Med 2001 163 1730 1754 11401897

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Ann Clin Microbiol Antimicrob. 2004 Jul 29; 3:14

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Ann Clin Microbiol Antimicrob

10.1186/1476-0711-3-14

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==== Front Ann Clin Microbiol AntimicrobAnnals of Clinical Microbiology and Antimicrobials1476-0711BioMed Central London 1476-0711-3-151528798810.1186/1476-0711-3-15ResearchActivity of telithromycin and comparators against bacterial pathogens isolated from 1,336 patients with clinically diagnosed acute sinusitis Dohar Joseph 1Joseph.Dohar@chp.eduCantón Rafael 2rafael.canton@smmc.esCohen Robert 3robert.cohen@wanadoo.frFarrell David John 4d.farrell@grmicro.co.ukFelmingham David 4d.felmingham@grmicro.co.uk1 Department of Pediatric Otolaryngology, Children's Hospital of Pittsburgh, Pittsburgh, USA2 Hospital Ramon y Cajal, Madrid, Spain3 Department of Microbiology, Intercommunal Hospital of Creteil, Creteil, France4 GR Micro Limited, London, United Kingdom2004 2 8 2004 3 15 15 15 4 2004 2 8 2004 Copyright © 2004 Dohar et al; licensee BioMed Central Ltd.2004Dohar et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background Increasing antimicrobial resistance among the key pathogens responsible for community-acquired respiratory tract infections has the potential to limit the effectiveness of antibiotics available to treat these infections. Since there are regional differences in the susceptibility patterns observed and treatment is frequently empirical, the selection of antibiotic therapy may be challenging. PROTEKT, a global, longitudinal multicentre surveillance study, tracks the activity of telithromycin and comparator antibacterial agents against key respiratory tract pathogens. Methods In this analysis, we examine the prevalence of antibacterial resistance in 1,336 bacterial pathogens, isolated from adult and paediatric patients clinically diagnosed with acute bacterial sinusitis (ABS). Results and discussion In total, 58.0%, 66.1%, and 55.8% of S. pneumoniae isolates were susceptible to penicillin, cefuroxime, and clarithromycin respectively. Combined macrolide resistance and reduced susceptibility to penicillin was present in 200/640 (31.3 %) of S. pneumoniae isolates (128 isolates were resistant to penicillin [MIC >= 2 mg/L], 72 intermediate [MIC 0.12–1 mg/L]) while 99.5% and 95.5% of isolates were susceptible to telithromycin and amoxicillin-clavulanate, respectively. In total, 88.2%, 87.5%, 99.4%, 100%, and 100% of H. influenzae isolates were susceptible to ampicillin, clarithromycin, cefuroxime, telithromycin, and amoxicillin-clavulanate, respectively. In vitro, telithromycin demonstrated the highest activity against M. catarrhalis (MIC50 = 0.06 mg/L, MIC90 = 0.12 mg/L). Conclusion The high in vitro activity of against pathogens commonly isolated in ABS, together with a once daily dosing regimen and clinical efficacy with 5-day course of therapy, suggest that telithromycin may play a role in the empiric treatment of ABS. ==== Body Introduction The incidences of both the acute and chronic forms of sinusitis have been increasing, and between 10 and 15% of the population of central Europe are affected annually [1]. There are an estimated 30 million cases of ABS in the USA each year [2-4]. Acute sinusitis accounts for 0.5–2.0% of all upper respiratory tract infections in adults and between 5–10% in children and therefore is a common reason for visits to primary care physicians [5]. Although usually mild in severity, complications can be life threatening, including meningitis, brain abscess, orbital cellulitis and abscess, subempyema, osteomyelitis, and nasal polyposis [6-9]. S. pneumoniae is the most common pathogenic bacterium responsible for ABS, isolated in 30–50% of cases, followed by H. influenzae, isolated in 20–40% of cases. Moraxella catarrhalis is isolated in 5–10% of cases, beta haemolytic streptococci in less than 5%, and Staphylococcus aureus in less than 10% although it is often found co-infecting with other bacteria [10]. Treatment options for ABS are controversial as up to 40% of patients recover spontaneously, however, studies have shown that treatment with an antibacterial reduces the time to recovery from sinusitis, improves symptoms, and helps to prevent complications [11,12]. Guidelines on antibacterial use for ABS vary, possibly because of different regulations, antibacterial resistance patterns, and etiology in different countries, however, the choice of first-line antibacterial is similar across treatment guidelines [3,13-17]. Nearly all recommend amoxicillin, as it is active against the major causative pathogens of AMS and is generally well tolerated. For patients with penicillin allergy, the recommended first-line agents vary in different countries. Trimethoprim or trimethoprim-sulfamethoxazole is commonly recommended [3,14]. In addition, the French guidelines have recently been reviewed and telithromycin has been included as an alternative first-line agent [15]. Macrolides are not included in the French guidelines due to the high macrolide resistance prevalence in France [15,18]. Second line, or alternative antibacterial agents of choice, are clarithromycin or second-generation cephalosporins such as cefuroxime and cefpodoxime, third-generation cephalosporins such as cefdinir, and trimethoprim-sulphamethoxazole [3,5,16,17]. Telithromycin has been recommended as an alternative agent in Germany [13,16]. High-dose amoxicillin-clavulanate should be used if the patient does not improve [3,16,17]. In France, anti-pneumococcal fluoroquinolones are recommended after bacterial confirmation or if the patient is at high risk of complications [15]. A single dose of ceftriaxone can be used in a child who cannot be treated orally, i.e. vomiting [17]. However, due to increasing levels of resistance in bacterial respiratory tract pathogens to these commonly used antibacterials (particularly the rapid emergence of penicillin-and macrolide-resistant strains of pneumococci), new agents are required that have high in vitro activity and demonstrated clinical efficacy against bacterial pathogens causing community-acquired respiratory tract infections (RTI's) [19-22]. Telithromycin is the first ketolide approved for clinical use. The ketolides are semisynthetic derivatives of the 14-membered ring macrolide erythromycin and have high in vitro activity against the common community-acquired RTI pathogens [23]. Clinical trials have demonstrated the efficacy and tolerability of telithromycin therapy in ABS [24-26]. The PROTEKT (Prospective Resistant Organism Tracking and Epidemiology for the Ketolide Telithromycin) study is a longitudinal, global multicentre surveillance study designed in part to determine the activity of telithromycin against community-acquired RTI isolates, in relation to the frequency of prescribing, in the regions where the study is conducted [27]. The aim of this paper is to focus on the data gathered in the PROTEKT surveillance study to determine the in vitro efficacy of the new ketolide telithromycin and comparator agents against bacterial pathogens isolated from the subset of patients with clinically diagnosed ABS collected in PROTEKT (2000–2001, and 2001–2002). Materials and Methods Patients and bacterial isolates Detailed study design, including patient selection and methodology for isolate identification and storage in the PROTEKT study has been described previously [27]. The isolates in this sub-study of PROTEKT were selected from those patients presenting with clinically diagnosed ABS in which the isolates were determined clinically to be the pathogenic organism and the specimen type was sinus aspirate or nasopharyngeal swab/aspirate only. Methodology for sinus aspiration was that used routinely by the investigator. Antimicrobial testing MIC susceptibility status was determined, using the National Committee of Clinical and Laboratory Standards (NCCLS) breakpoints, at a central laboratory (GR Micro Ltd, London, UK) from a panel of existing and new antibacterials, using the NCCLS broth microdilution method and lyophilised microtitre plates (Sensititre, Trek Diagnostics) [28]. NCCLS breakpoints were used for interpretation of MIC's [29]. Tentative NCCLS breakpoints for telithromycin are: S. pneumoniae and S. aureus, ≤ 1 μg/ml is susceptible, 2 μg/ml is intermediate, and ≥ 4 μg/ml is resistant; for Haemophilus influenzae, ≤ 4 μg/ml is susceptible, 8 μg/ml is intermediate, and ≥ 16 μg/ml is resistant [29]. Statistical analysis Statistical analysis was performed using a χ2 test. Results A total of 1,336 bacterial pathogens in all were collected from 25 countries within Western Europe (n = 652), North America (n = 14), Latin America (n = 207), Asia (n = 464), Eastern Europe (n = 68), Australia (n = 2), and South Africa (n = 126) in the PROTEKT study from years 2000–2001 and 2001–2002 for analysis of the susceptibility of bacterial pathogens isolated from patients with acute sinusitis. Gender distribution was 52.2% male (695 patients), 46.7% female (624 patients); gender was not provided for 1.3% of patients. Almost two thirds (66.3%) of patients were in the 0–12 year age group, one third (29.7%) in the 13–65 year age group, 2.7% in the over 65 year age group and age was not specified in 1.3% of patients. S. pneumoniae was the pathogen most frequently isolated (47.9% of isolates) followed by H. influenzae (24.6% of isolates) (Table 1). Table 1 Distribution of species by specimen type for the 1336 bacterial pathogens causing acute sinusitis [n (%)] Specimen S. pneumoniae H. influenzae M. catarrhalis S. aureus S. pyogenes Total Sinus 272 (47.5) 148 (25.9) 67 (11.7) 64 (11.2) 21 (3.7) 572 (42.8) Nasopharynx1 368 (48.1) 181 (23.7) 145 (19.0) 52 (6.8) 18 (2.4) 764 (57.2) Total 640 (47.9) 329 (24.6) 212 (15.9) 116 (8.7) 39 (2.9) 1336 (100) 1Aspirate or swab MIC data for isolates from patients with ABS demonstrated that the in vitro activity of telithromycin against gram-positive cocci was similar to amoxicillin-clavulanate and was higher and more potent than clarithromycin and beta-lactams tested such as cefuroxime (Table 2). In total, 99.5 % of streptococcal isolates were susceptible to telithromycin. With the exception of S. aureus isolates more than 90% of gram-positive cocci were inhibited at a telithromycin MIC of 0.25 mg/L (Table 2). Table 2 In vitro activity of antibacterial agents and percent susceptible against 1336 bacterial pathogens isolated from patients with clinically diagnosed acute sinusitis Organism N (total, SA1, NP2) Antibiotic MIC (mg/L) Percent susceptible (Total, SA, NP) Range 50 90 S. pneumoniae 640, 272, 368 Penicillin 0.008 – 8 0.06 2 58.0, 64.7, 53.0 Amoxicillin-clavulanate 0.015 – 8 0.03 2 95.5, 95.2, 95.7 Cefuroxime 0.015 – 16 0.12 8 66.1, 73.2, 60.9 Cefpodoxime 0.12 – 32 0.12 2 65.0, 71.7, 60.1 Trimethoprim-sulphamethoxazole 0.12 – 32 0.5 8 56.3, 58.1, 54.9 Erythromycin 0.03 - >64 0.06 >64 55.9, 60.7, 52.5 Clarithromycin 0.015 - >32 0.06 >32 55.8, 60.7, 52.2 Azithromycin 0.03 - >64 0.12 >64 55.8, 60.7, 52.2 Telithromycin 0.008 – 8 0.015 0.12 99.5, 98.9, 100 H. influenzae 329, 148, 181 Ampicillin 0.12 – 32 0.25 8 88.2, 91.2, 85.6 Amoxicillin-clavulanate 0.12 – 4 0.5 1 100, 100,100 Cefuroxime 0.12 – 16 1 2 99.4, 99.3, 99.5 Cefpodoxime 0.015 – 4 0.06 0.25 99.4, 100, 98.9 Cefdinir 0.06 – 4 0.25 0.5 97.3, 96.0, 98.3 Trimethoprim-sulphamethoxazole 0.03 – 16 0.06 4 84.5, 82.4, 86.2 Erythromycin 0.25 – 16 4 8 -3 Clarithromycin 0.25 – 32 8 16 87.5, 87.2, 87.9 Azithromycin 0.06 – 4 1 2 100, 100,100 Telithromycin 0.06 – 4 1 2 100, 100,100 M. catarrhalis 212, 67, 145 Ampicillin 0.12 – 32 4 16 - Amoxicillin-clavulanate 0.12 – 0.5 0.12 0.25 - Cefuroxime 0.12 – 16 1 4 - Cefpodoxime 0.06 – 4 0.5 1 - Cefdinir 0.06 – 1 0.12 0.25 - Trimethoprim-sulphamethoxazole 0.03 – 2 0.12 0.25 - Erythromycin 0.25 – 1 0.25 0.25 - Clarithromycin 0.25 – 0.5 0.25 0.25 - Azithromycin 0.06 – 0.25 0.06 0.06 - Telithromycin 0.004 – 0.5 0.06 0.12 - S. aureus 116, 64, 52 Methicillin - - - 90.5, 92.2, 88.5 Amoxicillin-clavulanate 0.06 – 8 0.5 4 90.5, 92.2, 88.5 Cefuroxime 0.5 – 16 1 2 90.5, 92.2, 88.5 Cefpodoxime 1 – 32 2 4 88.8, 92.2, 84.6 Trimethoprim-sulphamethoxazole 0.12 – 32 0.12 0.12 96.6, 95.3, 98.1 Erythromycin 0.03 - >64 0.25 >64 69.0, 73.4, 63.5 Clarithromycin 0.015 - >32 0.25 >32 69.8, 75.0, 63.5 Azithromycin 0.03 - >64 0.5 >64 69.0, 75.0, 61.5 Telithromycin 0.015 - >32 0.06 2 89.7, 89.1, 90.4 S. pyogenes 39, 21, 18 Penicillin 0.008 – 0.008 0.008 0.008 100, 100,100 Amoxicillin-clavulanate 0.008 – 0.03 0.015 0.015 100, 100,100 Cefuroxime 0.015 – 0.015 0.015 0.015 100, 100,100 Cefpodoxime 0.12 – 0.12 0.12 0.12 100, 100,100 Trimethoprim-sulphamethoxazole 0.12 – 0.5 0.12 0.25 - Erythromycin 0.03 – 4 0.06 0.25 92.3, 100, 83.3 Clarithromycin 0.015 – 2 0.03 0.25 92.3, 100, 83.3 Azithromycin 0.03 – 16 0.12 0.25 92.3, 100, 83.3 Telithromycin 0.008 – 0.12 0.015 0.015 - 1Sinus aspirate 2Nasopharyngeal aspirate or swab 3No NCCLS interpretive guidelines available or pending Resistance to most antibiotics was slightly greater in nasopharyngeal specimens than sinus aspirates (Table 2). Considerable variation in in vitro antibiotic activity was apparent between geographical regions as observed in the key examples shown in Table 3. Insufficient data were available for analysis by country. Table 3 Key example of regional variation in in vitro antibiotic activity Streptococcus pneumoniae Haemophilus influenzae REGION1 N Penicillin susceptible Erythromycin susceptible N Beta-lactamase positive Eastern Europe 40 70.0% 82.5% 13 0.0% Far East 185 24.9% 15.7% 96 13.5% Latin America 108 63.0% 73.1% 31 6.5% South Africa 61 37.7% 59.0% 34 2.9% Western Europe 246 83.7% 73.6% 153 11.8% Grand Total 640 58.0% 55.9% 329 10.3% 1Australasia and North America not included due to insufficient data Combined macrolide resistance and reduced susceptibility to penicillin was present in 200/640 (31.3 %) of S. pneumoniae isolates (128 isolates were resistant to penicillin [MIC >= 2 mg/L], 72 intermediate [MIC 0.12–1 mg/L]). Of note, 3 isolates of S. pneumoniae were non-susceptible to telithromycin (2 isolates intermediate with an MIC of 2 mg/L, 1 isolate resistant with an MIC of 8 mg/L). This represented 0.5% of isolates, a value that is significantly (p < 0.001) lower than those obtained by erythromycin (44.1%), clarithromycin (44.2%) and cefuroxime (33.9%). Of the 329 H. influenzae isolates, 34 (10.3 %) were positive for β-lactamase production. All isolates of H. influenzae were susceptible to amoxycillin-clavulanate and telithromycin with an MIC90 of 1 and 2 mg/L, respectively. Amoxycillin-clavulanate and telithromycin were more potent and had greater activity than clarithromycin (MIC90 = 16 mg/L, 87.5% susceptible). This activity was comparable to azithromycin (MIC90 = 2 mg/l, 100% susceptible). Although the number of S. aureus isolated from the total number of specimens was small (116/1366 isolates), telithromycin was as efficacious as comparators. Of the 116 isolates, 11 were resistant to methicillin (MRSA) and 105 were methicillin susceptible (MSSA). Ninety-nine (94.3%) of the MSSA isolates and 5 of the 11 MRSA isolates were susceptible to telithromycin. Of note, all of the S. pyogenes isolates were inhibited by ≤ 1 mg/L telithromycin, despite 17.7% resistance to erythromycin and clarithromycin. Telithromycin was the most potent antimicrobial against M. catarrhalis with an MIC50 of 0.06 mg/L and MIC90 of 0.12 mg/L. β-lactamase production was detected in 97.6% of these isolates. Discussion The data in this analysis demonstrates that telithromycin has high in vitro activity against bacterial pathogens isolated from a large, globally distributed population of patients diagnosed with ABS. Telithromycin was the most active and potent agent against all isolates of the pathogens isolated from patients with ABS with 99.4% of isolates susceptible. Not surprisingly, high levels of penicillin resistance, macrolide resistance, and combined penicillin and macrolides resistance were prevalent in S. pneumoniae although prevalence varied widely between geographical regions. Amoxicillin has been the treatment of choice in ABS because of its general effectiveness, safety, tolerability, low cost and narrow spectrum [17]. The high prevalence of beta-lactamase in H. influenzae and M. catarrhalis found in the present study demonstrate compromised in vitro efficacy of amoxicillin against these isolates. Although the cephalosporins (cefuroxime, cefpodoxime and cefdinir) showed high activity against H. influenzae (including beta-lactamase positive strains), resistance to these agents was high in S. pneumoniae: >30% for cefuroxime and cefpodoxime – cefdinir was not tested against pneumococci in PROTEKT, however susceptibility is usually similar to the other cephalosporins reported here [30]. Similarly, macrolides are prescribed in various countries for ABS and an overall resistance rate for S. pneumoniae of 44.1% to erythromycin, azithromycin, and clarithromycin was found. Trimethoprim-sulfamethoxazole activity was low for S. pneumoniae (56.3% susceptible) and decreased for H. influenzae (84.5% susceptible). Respiratory fluoroquinolones are recommended second-line treatment options in some countries (references needed to support this statement). However, recent evidence suggests that resistance to fluoroquinolones is rapidly developing in pneumococci and other pathogens (including gram-positive and gram-negative [31-34]. To preserve the long-term utility of fluoroquinolones, including their use in the treatment of serious non-respiratory infections, it has been recommended that respiratory fluoroquinolones be reserved for treating severe (e.g. hospitalized) community-acquired RTIs only [35,36]. The high prevalence of beta-lactam, macrolide, TMP-SMX resistance demonstrated in the large number of isolates from patients with clinically diagnosed sinusitis in our study demonstrates the need to be exploring new therapeutic options, especially in geographical regions of high prevalence such as the Far East. The high in vitro activity of telithromycin against ABS pathogens reported in this study, regardeless of geographical region, also demonstrates its potential as an empiric therapeutic option for ABS. There are several other reasons to consider this option – 1) High rates of clinical cure and bacteriological eradication have been demonstrated using telithromycin against sinus isolates of S. pneumoniae, H. influenzae, M. catarrhalis and S. aureus [24-26]. 2) Telithromycin has been shown to have a targeted spectrum of activity against the major bacterial respiratory tract pathogens and has less effect on normal bacterial ecology [37-39]. 3) The pharmacokinetic profile of oral telithromycin allows it to be prescribed with a dosing regime of 800 mg once daily for 5 days [40,41]. This contrasts favourably with its comparators, where a 10 – 14 day course with administration either 2 or 3 times daily, depending on the chosen antibacterial, is generally prescribed. Studies have shown that the once daily dosing regime affords greater patient treatment compliance, thereby avoiding clinical failure and the ensuing development of antibacterial resistance [41-43]. 5) Telithromycin has been shown to have high penetration levels in paranasal sinuses, and it is preferentially absorbed by polymorphonuclear neutrophils (PMNs) within the azurophil granules allowing effective delivery to phagocytized intracellular bacteria [44,45]. Although this study provides valuable information on the overall antimicrobial profile of bacteria causing ABS care should be taken when interpreting data related to specific demographics. A major limitation of this study, inherent to most surveillance studies, is the requirement for collecting centers to fulfill a specified quota of isolates over a defined time period (1 year). If, for instance, 1 center manages to fulfill their quota for S. pneumoniae isolates from patients with community-acquired pneumonia, they may then only send H. influenzae from patients with ABS to fulfill their quota for this organism. Thus, the potential exists to over or under estimate the prevalence of a species in a particular disease. A further limitation of this study is it is restricted to the major bacterial pathogens causing sinusitis and does not therefore assess anaerobic bacteria, which are also known to be involved in this disease. However, a recent study of sinus puncture specimens demonstrated that telithromycin had good in vitro activity against anaerobes involved in sinusitis [46]. The inclusion of nasopharyngeal specimens is a potential limitation of this study and the higher rate of resistance compared to sinus aspirates may indicate some isolates were nasopharyngeal flora rather than pathogens. However, the difference in resistance prevalence between nasopharyngeal specimens and sinus aspirates was not great for any species/antibiotic combination, and assuming the majority of isolates were the responsible pathogen, significant bias of resistance patterns is unlikely. The treatment of ABS is complicated by a difficulty in establishing the causative pathogen(s). Sampling of infected fluid using sinus puncture is a painful and rare procedure [47]. Nasopharyngeal culture is a painless and reliable method that can help identify patients that may benefit from antibacterial therapy [48] and hence, could be useful in determining antibiotic resistance implicated in sinusitis – particularly Streptococcus pneumoniae and Haemophilus influenzae. Additionally, there are regional differences in the susceptibility patterns observed and, as therapy is usually empirical, choosing an effective therapy can be challenging [18,20,49]. In summary, the data presented here demonstrates that telithromycin has good in vitro activity against S. pneumoniae, H. influenzae, M. catarrhalis and S. aureus respiratory pathogens commonly isolated in ABS. It is as active as or more active than antibacterial agents that are currently used in this clinical setting. The development of resistance will always be a threat to the usefulness of antibacterial compounds, however surveillance studies such as PROTEKT allow the rapid detection and characterization of resistance mechanisms and highlight the need for and examine the in vitro efficacy of newer antibacterial agents. Providing careful surveillance for the development of resistance is maintained telithromycin currently offers a useful therapeutic option in the treatment of AS. Authors' contributions JD, RCa and RCo reviewed the data and provided clinical and microbiological interpretation and discussion. DF and DJF participated in the design of the study, supervised the scientific testing, and provided data analysis, microbiological interpretation and discussion. All authors drafted the manuscript. All authors read and approved the final manuscript. Acknowledgements We are grateful to our colleagues worldwide for the supply of bacterial isolates as part of the PROTEKT study and the GR Micro PROTEKT team who performed the testing. Aventis is acknowledged for their financial support of the PROTEKT study. ==== Refs Grevers G Klemens A [Rhinosinusitis. Current diagnostic and therapeutic aspects] MMW Fortschr Med 2002 144 31 35 12494595 Schwartz R The diagnosis and management of sinusitis Nurse Pract 1994 19 58 63 7532290 Antimicrobial treatment guidelines for acute bacterial rhinosinusitis. 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NCCLS document M100-S14 2004 Wayne, Pennsylvania 19807 - 1898, USA, NCCLS Sader HS Fritsche TR Mutnick AH Jones RN Contemporary evaluation of the in vitro activity and spectrum of cefdinir compared with other orally administered antimicrobials tested against common respiratory tract pathogens (2000-2002) Diagn Microbiol Infect Dis 2003 47 515 525 14596971 10.1016/S0732-8893(03)00165-2 Quale J Landman D Ravishankar J Flores C Bratu S Streptococcus pneumoniae, Brooklyn, New York: fluoroquinolone resistance at our doorstep Emerg Infect Dis 2002 8 594 597 12023915 Morrissey I Farrell DJ Bakker S Buckridge S Felmingham D Molecular Characterization and Antimicrobial Susceptibility of Fluoroquinolone-Resistant or -Susceptible Streptococcus pneumoniae from Hong Kong Antimicrob Agents Chemother 2003 47 1433 1435 12654686 10.1128/AAC.47.4.1433-1435.2003 Chen DK McGeer A de Azavedo JC Low DE Decreased susceptibility of Streptococcus pneumoniae to fluoroquinolones in Canada. 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Clin Infect Dis 2002 35 721 727 12203170 10.1086/341900 BTS Guidelines for the Management of Community Acquired Pneumonia in Adults Thorax 2001 56 1iv 64 11120894 Heffelfinger JD Dowell SF Jorgensen JH Klugman KP Mabry LR Musher DM Plouffe JF Rakowsky A Schuchat A Whitney CG Management of community-acquired pneumonia in the era of pneumococcal resistance: a report from the Drug-Resistant Streptococcus pneumoniae Therapeutic Working Group Arch Intern Med 2000 160 1399 1408 10826451 10.1001/archinte.160.10.1399 Cremieux AC Muller-Serieys C Panhard X Delatour F Tchimichkian M Mentre F Andremont A Emergence of Resistance in Normal Human Aerobic Commensal Flora during Telithromycin and Amoxicillin-Clavulanic Acid Treatments Antimicrob Agents Chemother 2003 47 2030 2035 12760893 10.1128/AAC.47.6.2030-2035.2003 Edlund C Beyer G Hiemer-Bau M Ziege S Lode H Nord CE Comparative effects of moxifloxacin and clarithromycin on the normal intestinal microflora Scand J Infect Dis 2000 32 81 85 10716083 10.1080/00365540050164272 Low DE Brown S Felmingham D Clinical and bacteriological efficacy of the ketolide telithromycin against isolates of key respiratory pathogens: a pooled analysis of phase III studies Clin Microbiol Infect 2004 10 27 36 14706083 10.1111/j.1469-0691.2004.00752.x Aventis Pharma 2001. KetekTM. Telithromycin. Briefing document for the FDA Anti-infective DrugProducts Advisory Committee Meeting, April 2001 p62 63 [Section 5.6- Dose Determination] Nicolau DP Pharmacodynamic rationale for short-duration antibacterial therapy J Infect 2002 44 Suppl A 17 23 12150491 Claxton AJ Cramer J Pierce C A systematic review of the associations between dose regimens and medication compliance Clin Ther 2001 23 1296 1310 11558866 10.1016/S0149-2918(01)80109-0 Sclar DA Tartaglione TA Fine MJ Overview of issues related to medical compliance with implications for the outpatient management of infectious diseases Infect Agents Dis 1994 3 266 273 7866659 Miossec-Bartoli C Pilatre L Peyron P N'Diaye EN Collart-Dutilleul V Maridonneau-Parini I Diu-Hercend A The new ketolide HMR3647 accumulates in the azurophil granules of human polymorphonuclear cells Antimicrob Agents Chemother 1999 43 2457 2462 10508024 Miyamoto N Pharmocokinetic study of a new ketolide antimicrobial telithromycin (HMR3647) in otorhinolaryngology. 40th Interscience Conference on Antimicrobial Agents and Chemotherapy 2000 Toronto Goldstein Ellie J. C. Citron Diane M. Merriam C. Vreni Warren Yumi Tyrrel Kerin L. Fernandez Helen In Vitro Activities of Telithromycin and 10 Oral Agents against Aerobic and Anaerobic Pathogens Isolated from Antral Puncture Specimens from Patients with Sinusitis Antimicrob Agents Chemother 2003 47 1963 1967 12760875 10.1128/AAC.47.6.1963-1967.2003 Brooks I Gooch W. M., 3rd Jenkins SG Pichichero ME Reiner SA Sher L Yamauchi T Medical management of acute bacterial sinusitis. Recommendations of a clinical advisory committee on pediatric and adult sinusitis Ann Otol Rhinol Laryngol Suppl 2000 182 2 20 10823486 Kaiser L Morabia A Stalder H Ricchetti A Auckenthaler R Terrier F Hirschel B Khaw N Lacroix JS Lew D Role of nasopharyngeal culture in antibiotic prescription for patients with common cold or acute sinusitis Eur J Clin Microbiol Infect Dis 2001 20 445 451 11561799 10.1007/s100960100544 Hoban DJ Doern GV Fluit AC Roussel-Delvallez M Jones RN Worldwide prevalence of antimicrobial resistance in Streptococcus pneumoniae, Haemophilus influenzae, and Moraxella catarrhalis in the SENTRY Antimicrobial Surveillance Program, 1997-1999 Clin Infect Dis 2001 32 Suppl 2 S81 93 11320449 10.1086/320181

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==== Front Lipids Health DisLipids in Health and Disease1476-511XBioMed Central London 1476-511X-3-191528798710.1186/1476-511X-3-19ResearchIncreased contractile responses to 5-hydroxytryptamine and Angiotensin II in high fat diet fed rat thoracic aorta Ghatta Srinivas 12Srinivas.Ghatta@ndsu.nodak.eduRamarao Poduri 2ramaraop@yahoo.com1 Department of Pharmaceutical Sciences, North Dakota State University, Fargo, North Dakota 58105, USA2 Department of Pharmacology and Toxicology, National Institute of Pharmaceutical Education and Research, Sector 67, Phase-X, S.A.S. Nagar 160 062, Punjab, India2004 2 8 2004 3 19 19 23 6 2004 2 8 2004 Copyright © 2004 Ghatta and Ramarao; licensee BioMed Central Ltd.2004Ghatta and Ramarao; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background Feeding normal rats with high dietary levels of saturated fat leads to pathological conditions, which are quite similar to syndrome X in humans. These conditions such as hypertriglyceridemia, hypercholesterolemia, obesity, and hyperglycemia might induce hypertension through various mechanisms. Metabolic syndrome and the resulting NIDDM represent a major clinical challenge because implementation of treatment strategies is difficult. Vascular abnormalities probably contribute to the etiology of many diabetic complications including nephropathy, neuropathy, retinopathy, and cardiomyopathy. It has been shown that in Streptozotocin induced diabetic animals there is an increase in maximal responses to 5-Hydroxytryptamine and Angiotensin II. The purpose of this study was to evaluate High fat diet fed rats for the development of hypertriglyceridemia, hypercholesterolemia, hyperinsulinemia and hyperglycemia and to assess their vascular responses to 5-Hydroxytryptamine and Angiotensin II. Methods Male Sprague Dawley rats were used for this study and were divided into two equal groups. One of the groups was fed with normal pellet diet and they served as the control group, whereas the other group was on a high fat diet for 4 weeks. Body weight, plasma triglycerides, plasma cholesterol, and plasma glucose were measured every week. Intraperitoneal glucose tolerance test was performed after 4 weeks of feeding. At the end of fourth week of high fat diet feeding, thoracic aortae were removed, and cut into helical strips for vascular reactivity studies. Dose-response curves of 5-Hydroxytryptamine and Angiotensin II were obtained. Results There was no significant difference in pD2, with 5-Hydroxytryptamine and Angiotensin II in both groups but Emax was increased. Conclusions These results suggest that hypertension in high fat diet rats is associated with increased in vitro vascular reactivity to 5-HT and Ang II. ==== Body Background Syndrome X comprises a plethora of conditions such as obesity, dyslipidemia, impaired glucose tolerance, insulin resistance and hypertension [1]. It places stress on multiple organ systems and plays a significant role in the development of other related cardiovascular disorders. Western style diet, which contains high levels of fat, is also considered to be one of the main factors in the development of obesity and insulin resistance. The most common reason for the development of hyperinsulinemia (decreased hepatic insulin clearance and/or increased insulin secretion) from insulin resistance is obesity. Excess fat deposits in the white adipose tissue affects insulin mediated glucose metabolism in non adipose tissues, causes disordered insulin response and increases lipid deposition [2]. However, pathophysiologies of vascular complications in syndrome X have not been fully understood. 5-hydroxytryptamine (5-HT) is shown to be related to pathogenesis of vasculopathy in diabetes. Various studies in humans and rabbits have reported increased plasma 5-HT levels and enhanced contraction to 5-HT in diabetes mellitus [3-5]. Another vasopressor peptide, Angiotensin II (Ang II) is involved in cardiovascular complications of diabetes mellitus. Many have reported that the vascular Renin angiotensin system is one of the key systems in the etiology of vascular alterations in early stages of diabetes. It is already established that 5-HT and Ang II responses are altered in the aortic rings of streptozotocin (STZ) induced diabetic rats [6,7] and high fructose diet fed rats [8]. However, very little information is available in the literature regarding the vascular contractile responses to vasopressor agents such as 5-HT and Ang II in HFD fed rats. The aim of this study was to elucidate the contractile responses to 5-HT and Ang II in HFD fed rat thoracic aorta which will provide an avenue for further exploratory studies. We have selected HFD fed rat model for our study because it is a useful model of the putative effects of excess fat intake in humans and it represents the major sub type of diabetes mellitus, non insulin dependent diabetes mellitus (NIDDM). Results Biochemical measurements HFD fed rats showed significant increase in body weight as compared to NPD fed rats (Table 2). In addition, the rats fed HFD showed significant elevation in the basal plasma glucose, triglyceride, total cholesterol and insulin levels at the end of four weeks of dietary manipulation as compared to NPD fed control groups (Table 2). The HFD fed rats exhibited significant elevation in basal fasting glucose and showed significant impairment in glucose tolerance to exogenously administered glucose (Fig 1). Estimation of AUC values indicated 28.4 % increase in plasma glucose of HFD fed when compared to NPD fed rats. Table 2 Various parameters of NPD and HFD fed rats Parameter NPD fed HFD fed Body weight (gm) 259.2 ± 5.3 315.0 ± 6.5*** plasma glucose (mg/dl) 87.5 ± 2.5 111.0 ± 0.9*** Plasma triglycerides (mg/dl) 41.3 ± 1.7 89.7 ± 7.2*** Plasma cholesterol (mg/dl) 48.9 ± 3.7 87.5 ± 2.6*** Plasma Insulin (ng/ml) 1.90 ± 0.15 3.05 ± 0.21* pD2 of 5-HT 5.74 ± 0.09 6.00 ± 0.06 Emax of 5-HT 30.0 ± 1.8 49.0 ± 2.0** pD2 of Ang II 7.69 ± 0.08 7.31 ± 0.18 Emax of Ang II 25.0 ± 3.4 34.0 ± 3.0* Each point is represented as mean ± SEM *p < 0.05, **p < 0.01 and ***p < 0.001 Vs NPD fed group Figure 1 Effect of HFD on intra peritoneal glucose tolerance test (IPGTT) in rats, as compared to NPD fed group. All values are expressed as mean ± SEM (n = 8) *p < 0.05, **p < 0.01, ***p < 0.001 Vs NPD fed group Vascular Responses Cumulative concentration response curves of 5-HT and Ang II for both HFD fed rat thoracic aortae showed an increase in Emax (Fig 2 and 3) with out any change in pD2 values when compared to NPD fed rats (Table 2). There was no significant change in both Emax and pD2 values with KCl in both groups (data not shown). The order of potency of agonists in both groups was Ang II>5-HT>KCl. Figure 2 Cumulative concentration response curve to 5-HT in helically cut aortic strip preparations obtained from NPD fed and HFD fed rats. Each point is represented as mean ± SEM (n = 5) *p < 0.05, **p < 0.01 Vs NPD fed group Figure 3 Cumulative concentration response curve to Ang II in helically cut aortic strip preparations obtained from NPD fed and HFD fed rats. Each point is represented as mean ± SEM (n = 5) *p < 0.05, **p < 0.01 Vs NPD fed group Discussion Obesity is a major risk factor for several metabolic diseases, frequently clustering to form the metabolic syndrome or syndrome X [9]. Obese people have increased incidence of NIDDM with high percentage of mortality and morbidity [10]. Western style diet, which is abundant with calorically dense and saturated fatty foods, is considered to be the main factor in the development of obesity and insulin resistance. Our studies have shown that HFD causes increase in bodyweight when compared to NPD after four weeks of dietary manipulation in rats. Hyperglycemia is observed in insulin resistance where glucose utilization is reduced. We saw significant elevations in blood glucose levels. Intraperitoneal glucose tolerance tests confirm severe glucose intolerance. Oversupply of dietary lipids causes insulin resistance in rats [11]. Randle glucose fatty acid cycle suggested that the body prefers excess lipid stores to glucose for metabolic oxidation in insulin resistance [12]. Our HFD model also exhibited high plasma triglyceride levels. Hence studies on our experimental model in compliance with Randle et al findings suggested that HFD feeding causes insulin resistance [13]. Insulin resistance with compensatory hyperinsulinemia is a prominent feature of metabolic syndrome. The most common reason for the development of hyperinsulinemia in insulin resistance is obesity. It stands as one of the major cardiovascular risk factors in patients with obesity. The present study on HFD rats demonstrated higher plasma insulin levels than control values. This marked hyperinsulinemia could be due to a combination of increased β-cell mass and decreased insulin clearance, as well as failure of insulin to suppress hepatic gluconeogenesis [14]. Elevated cholesterol is also observed in insulin resistant individuals. For this reason we measured plasma cholesterol levels which were found to be more than normal values. Previous studies have reported a down regulation of LDL receptors and associated decrease in LDL clearance, increased total cholesterol levels [15]. According to National Cholesterol Education Program's Adult Treatment Panel III (Third report) easily measured clinical findings for syndrome X includes increased abdominal circumference, elevated triglycerides, low high-density lipoprotein-cholesterol, and elevated fasting blood glucose and/or elevated blood pressure. Three of these five are required for diagnosis. Our study demonstrated three of the clinical parameters indicating conditions of syndrome X in HFD fed rats [16]. Insulin resistance along with other conditions of syndrome X might induce hypertension by a host of mechanisms involving insulin itself, increased sodium reabsorption and/or enhanced intra cellular concentration of free calcium in vascular smooth muscle [17]. Although the etiology of vascular disorders in metabolic syndrome has not completely been revealed, it is suggested that alterations in the reactivity of blood vessels to neurotransmitters and circulating hormones are responsible for the functional abnormalities of blood vessels. In order to elaborate the pathways that connect syndrome X to hypertension we have studied the contractile responses to 5-HT and Ang II in both HFD and NPD fed rat thoracic aortae. Previously we have demonstrated increased contractile responses with synthetic alpha adrenoceptor agonist, phenylephrine, in HFD fed rat thoracic aorta [18]. This enabled us to explore the role of these endogenous mediators in the same animal model. The present vascular studies demonstrated that the magnitude of responses to 5-HT and Ang II was significantly enhanced in HFD fed animals without change in pD2 value. Endothelial denudation obviates any related mechanisms such as impairment of NO release, increased destruction of EDRF and substrate availability for the production of EDRF. Hence, the probable reasons for these enhanced 5-HT and Ang II responses may be due to receptor mediated or non-receptor mediated pathways. The role of non-receptor mediated contraction can be ruled out for there was no change in contractile response to KCl. Vascular studies have also shown functional evidence that hypertension developed in HFD fed rats may be associated with enhanced vasoreactivity to various vasoconstrictor agents. Further the enhanced responses to 5-HT in HFD fed rats could be due to increased PKC as previously reported with STZ and alloxan (ALL) induced diabetic animals [19]. Increased contractions to 5-HT can also be related to 5-HT2A upregulation as observed in spontaneously hypertensive rats or due to serotonin acting through alpha adrenoceptors [20]. Increased Ang II responses in HFD fed rats are may be due to upregulation of Ang II receptors as observed in hyperinsulinemia or via amplified secondary messenger systems [21]. A proposed scheme of events is given in Fig 4. Figure 4 Proposed events underlying syndrome X in HFD rats. HFD leads to condition, in rats, similar to syndrome X. This includes obesity, insulin resistance, hyperglycemia and dyslipidemia which all are interrelated. These events are the initial steps in the cascade towards hypertension. This could be mediated via increased contractile responses to various endogenous mediators such as 5-HT and Ang II. In summary, the present study has shown that HFD feeding in rats produces conditions similar to syndrome X. Increased vasocontractile responses observed in the model are not only mediated via alpha adrenoceptors but also due to 5-HT and Ang II (see Figure 4). More robust studies on the secondary messenger systems of 5-HT and Ang II will provide valuable insights into the mechanisms underlying increased vascular contractility in insulin resistance. Materials and Methods Tissue Preparation Male Sprague-Dawley rats (central animal facility, National Institute of Pharmaceutical Education and Research (NIPER), India), 160–200 g, were kept in controlled environmental conditions with room temperature 22 ± 2°C, humidity 55 ± 5% and 12-h light/dark cycles. All the animals had free access to food and water. The rats were divided into two dietary groups and fed with standard rat normal pellet diet (NPD) (3.8 kcal/g, carbohydrate 67%, protein 21%, fat 12% kcal) and HFD (5.3 kcal/g, carbohydrate 17%, protein 25%, fat 58% kcal). Composition of HFD is described in Table 1. Table 1 Composition of HFD (g) Powdered pellet diet 364 Lard 310 Casein 250 Cholesterol 10 DL-Methionine 3 Yee-sac powder 1 Vitamin and mineral mix powder 60 Sodium chloride 2 Biochemical measurements Blood samples from the retro orbital plexus of anaesthetized rats (Pentobarbitone 45 mg/kg, i.p.,) were collected into the heparinized tubes and immediately centrifuged at 5000 rpm for the separation of plasma. Plasma was stored at -20°C until assayed. The plasma was used for the estimation of glucose (Qualigens, Mumbai, India), triglycerides, and cholesterol (Chema diagnostica, Jesi, Italy) by commercial kits. Plasma insulin was determined by radioimmuno assay using rat insulin as standard (Linco research, St. Charles, MO, USA) Intra peritoneal glucose tolerance test (IPGTT) Glucose tolerance tests were carried out after four weeks of feeding of both NPD and HFD. After an overnight fast, blood samples were collected from the retro orbital plexus. Glucose levels were measured at time zero (0 min) and glucose was injected into the rats (2 g/Kg/4 ml, i.p.,). Additional blood samples were taken at 15, 30, 60 and 120 min. following the glucose load. Plasma glucose levels were measured by the glucose oxidase reaction (GOD/POD) using commercial kit (Qualigens, Mumbai, India). Area under the curve (AUC) was calculated for both NPD and HFD fed rats. Vascular Studies After 4 weeks of feeding, rats were sacrificed by cervical dislocation. The section of the aorta from between the aortic arch and the diaphragm was removed from the euthanized rats and placed in oxygenated, modified Krebs-Henseleit solution (KHS; in mM: 118 NaCl, 4.7 KCl, 25 NaHCO3, 2.6 CaCl2 2H2O 1.2 NaH2PO4, 1.2 MgCl2 6H2O, 5.5 glucose). With the help of a steel rod, aortic endothelium was deliberately denuded. The aorta was cut into helical strips 3 mm wide, 20 mm long and then placed in a well-oxygenated (95% O2-5% CO2) bath of 10-ml KHS with one end connected to a tissue holder and the other to an isotonic transducer (Bio Devices, Ambala, India). The tissue was equilibrated for 60 min under a resting tension of 1.0 g. At the beginning of each experiment, aortic strips were primed with depolarizing concentration (90 mM) potassium chloride (KCl). After the equilibration period, contractile responses to various concentrations of 5-HT (10 nM-30 μM) and Ang II (1 nM-300 nM) were recorded. Data analysis Contraction responses are expressed as percentage. For each contractile agent, both the maximal contraction (Emax) and the concentration necessary to produce 50% of its maximal response (EC50) were determined. The EC50 values were converted to the negative logarithms and expressed as pD2. Results were shown as mean ± SEM; n refers to the number of animals from which vessels were taken. Agonist potencies and maximal effects were compared by student's t test by using statistical software (GraphPad Prism 3.01). Values were considered significantly different at p < 0.05. Drugs and solutions The following drugs were used in this study: 5-HT (RBI, USA), Ang II (Bachem, Switzerland), All drugs were dissolved in KHS. Drugs were added to the organ chambers in volumes not greater than 0.2 ml. List of abbreviations HFD – High fat diet NPD – Normal pellet diet NIDDM – Non insulin dependent diabetes mellitus STZ – Streptozotocin 5-HT – 5-Hydroxytryptamine Ang II – Angiotensin II KHS – Krebs-Henseleit solution GOD/POD – Glucose oxidase/peroxidase AUC – area under the curve Emax – Maximal response EC50 – Concentration required producing 50% of maximal response pD2 – -log EC50 Authors' contributions SG carried out the all experimentations. PR has conceived the study and participated in its design and coordination. Authors read and approved the final manuscript. Acknowledgements This work was supported by a grant from NIPER. The authors thank Dr. Srinivasan for help in Radioimmunoassay of insulin. We thank Ms. Deepthi Nimmagadda for help in preparation of the manuscript. ==== Refs Chisholm DJ Campbell LV Kraegen EW Pathogenesis of the insulin resistance syndrome (syndrome X) Clin Exp Pharmacol Physiol 1997 24 782 784 9315389 Faraj M Lu HL Cianflone K Diabetes, lipids, and adipocyte secretagogues Biochem Cell Biol 2004 82 170 190 15052336 10.1139/o03-078 Pietraszek MH Takada Y Takada A Fujita M Watanabe I Taminato A Yoshimi T Blood serotonergic mechanisms in type2 (non-insulin-dependent) diabetes mellitus Thromb Res 1992 66 765 774 1519234 10.1016/0049-3848(92)90052-C Miranda FJ Alabadi JA Llorens S Ruiz de Apodaca RF Centeno JM Alborch E Diabetes-induced changes in endothelial mechanisms implicated in rabbit carotid arterial response to 5-hydroxytryptamine Eur J Pharmacol 2000 401 397 402 10936499 10.1016/S0014-2999(00)00469-6 Miranda FJ Alabadi JA Llorens S Ruiz de Apodaca RF Centeno JM Alborch E Experimental diabetes induces hyperreactivity of rabbit renal artery to 5-hydroxytryptamine Eur J Pharmacol 2002 439 121 127 11937101 10.1016/S0014-2999(02)01438-3 Cinar MG Ulker S Alper G Evinc A Effect of vitamin E supplementation on vascular reactivity of thoracic aorta in streptozotocin-diabetic rats Pharmacology 2001 62 56 64 11150923 10.1159/000056072 Orie NN Aloamaka CP Duration-dependent variability in the responses of diabetic rat aorta to noradrenaline and 5-hydroxytryptamine Gen Pharmacol 1993 24 243 246 8482502 10.1016/0306-3623(93)90042-V Iyer SN Katovich MJ Vascular reactivity to phenylephrine and angiotensin II in hypertension associated with insulin resistance Clin Exp Hypertens 1996 18 227 242 8869002 Evans RM Barish GD Wang YX PPARs and the complex journey to obesity Nat Med 2004 10 355 361 15057233 10.1038/nm1025 Blackman S The Enormity of obesity The Scientist 2004 18 20 24 Kim JK Wi JK Youn JH Metabolic impairment precedes insulin resistance in skeletal muscle during high-fat feeding in rats Diabetes 1996 45 651 658 8621018 Randle PJ Garland PB Hales CN Newsholme EA The glucose fatty acid cycle: Its role in insulin sensitivity and in metabolic disturbances in diabetes mellitus Lancet 1963 1 785 789 13990765 10.1016/S0140-6736(63)91500-9 Shibata T Matsui K Yonemori F Wakitani K Triglyceride-lowering effect of novel insulin-sensitizing agent, JTT-501 Eur J Pharmacol 1999 373 85 91 10408254 10.1016/S0014-2999(99)00256-3 Michael MD Kulkarni RN Postic C Previs SF Shulman GI Magnuson MA Kahn CR Loss of insulin signaling in hepatocytes leads to severe insulin resistance and progressive hepatic dysfunction Mol Cell 2000 6 87 97 10949030 10.1016/S1097-2765(00)00010-1 Kushwaha RS McMahan CA Mott GE Carey KD Reardon CA Getz GS McGill HC Jr Influence of dietary lipids on hepatic mRNA levels of proteins regulating plasma lipoproteins in baboons with high and low levels of large high density lipoproteins J Lipid Res 1991 32 1929 1940 1687745 ATP III Guidelines Reaven GM Lithell H Landsberg L Hypertension and associated metabolic abnormalities – The role of insulin resistance and the sypathoadrenal system New Engl J Med 1996 334 374 381 8538710 10.1056/NEJM199602083340607 Ghatta S Srinivasan K Kaul CL Ramarao P A study on α-adrenoceptor mediated contractile responses of high fat diet fed rat thoracic aorta Die Pharmazie Hattori Y Kawasaki H Kanno M Fukao M Enhanced 5-HT2 receptor mediated contractions in diabetic rat aorta: participation of Ca2+ channels associated with protein kinase C activity J Vasc Res 1995 32 220 229 7654879 Doggrell SA Chen Y Responsiveness, affinity constants and receptor reserves for serotonin on aortae of aged normotensive and hypertensive rats J Pharm Pharmacol 2001 53 1403 1408 11697549 10.1211/0022357011777756 Fang TC Huang WC Role of angiotensin II in hyperinsulinemia-induced hypertension in rats J Hypertens 1998 16 1767 1774 9869010 10.1097/00004872-199816120-00009

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Lipids Health Dis. 2004 Aug 2; 3:19

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==== Front Clin Mol AllergyClinical and molecular allergy : CMA1476-7961BioMed Central London 1476-7961-2-101528798610.1186/1476-7961-2-10Case ReportAutoimmune progesterone dermatitis in a patient with endometriosis: case report and review of the literature Baptist Alan P 1abaptist@umich.eduBaldwin James L 1jbaldwin@umich.edu1 Division of Allergy/Immunology, Department of Internal Medicine, University of Michigan, 3918 Taubman Center, #0380, 1500 E Medical Center Drive, Ann Arbor, MI 48109-0380, USA2004 2 8 2004 2 10 10 15 6 2004 2 8 2004 Copyright © 2004 Baptist and Baldwin; licensee BioMed Central Ltd.2004Baptist and Baldwin; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Autoimmune progesterone dermatitis (APD) is a condition in which the menstrual cycle is associated with a number of skin findings such as urticaria, eczema, angioedema, and others. In affected women, it occurs 3–10 days prior to the onset of menstrual flow, and resolves 2 days into menses. Women with irregular menses may not have this clear correlation, and therefore may be missed. We present a case of APD in a woman with irregular menses and urticaria/angioedema for over 20 years, who had not been diagnosed or correctly treated due to the variable timing of skin manifestations and menses. In addition, we review the medical literature in regards to clinical features, pathogenesis, diagnosis, and treatment options. ==== Body Introduction While many women complain of worsening acne and water retention during their menstrual cycle, there exist a small number in whom the menstrual cycle is associated with a variety of other skin manifestations such as urticaria, eczema, folliculitis, and angioedema. This condition is known as autoimmune progesterone dermatitis (APD) due to the fact that progesterone is most frequently identified as the etiologic agent. In women with irregular menses, the diagnosis may remain elusive for years. We present a case of APD, and review the current literature in regards to clinical features, pathogenesis, diagnosis, and treatment options. Case A 33y/o woman with a history of endometriosis presented with complaints of chronic urticaria. The patient noted that the urticaria began at the age of 12, and did not seem to have any obvious trigger. Each individual lesion would last from 12–24 hours, and the entire episode would last 5–10 days. Lesions would usually start on the chest and then spread over the entire body. She had seen multiple physicians, including allergists and dermatologists, and had been treated with a variety of medications including certirizine, desloratadine, hydroxyzine, montelukast, ranitidine, and diphenhydramine without relief. Prednisone at high doses would provide temporary relief, and she had required multiple courses of prednisone over the past 20 years. In addition, she complained of occasional angioedema, usually at the same time as the hives but occasionally occurring when hives were not present. The patient also had acne that had been very difficult to control since her teenage years, and she noted that the acne would also respond to prednisone. Multiple lab tests over the years had been unremarkable. These included SSA/SSB, anti-Smith, ACE level, C3/C4, hepatitis B, ANA, anti double-stranded DNA, immunoglobulins, SPEP, C1 esterase inhibitor level and function, chemistry panel, liver tests, TSH, T4, thyroid antibodies, rheumatoid factor, ESR, and CBC. Skin biopsy of a lesion had been read as "chronic urticaria". Upon further questioning, it was learned that due to the patient's endometriosis, she had very irregular menstrual cycles in terms of length and timing. It was determined that the hives and/or angioedema would begin approximately 4 days prior to the onset of menses, and would last about 2 days into menses. The symptoms would not occur with every episode of menses. The patient's acne would often occur on her face during the urticarial episodes. Of note, the patient had 2 children, and during each pregnancy her hives, acne, and angioedema had been markedly improved. Because of her endometriosis, she had been started on Depo-Provera (medroxyprogesterone acetate) in her twenties. After 1 injection, she developed severe hives that lasted over 2 months and required multiple courses of prednisone. Due to the urticaria, Depo-Provera was discontinued after one injection. As the patient complained of acne, Ortho Tri-Cyclen (norgestimate/ethinyl estradiol) was initiated by her dermatologist. This treatment modality did not have any effect on the urticaria, angioedema, or acne. The patient was evaluated in our clinic. Physical examination was essentially normal, and no hives were noted. Allergy skin testing was performed with progesterone 50 mg/mL in normal saline. Prick test was normal, but a full strength intradermal test revealed a 7 mm wheal with erythema. The histamine control showed a 9 mm wheal with erythema, and saline control was negative for wheal and erythema. Two healthy controls also underwent intradermal testing to exclude irritant reaction, and were found to be negative Based on the above results, the patient was diagnosed with autoimmune progesterone dermatitis. The patient was started on a GnRH agonist (nafarelin acetate nasal spray, 200 mcg twice a day). Within one month, she noted dramatic improvement in her urticaria and angioedema. Acne was still occasionally present, but much improved. She did complain of mild hot flashes, but felt these were tolerable. Discussion In a small group of women, the menstrual cycle has been associated with a spectrum of dermatologic diseases including eczema, erythema multiforme, stomatitis, papulopustular lesions, folliculitis, angioedema, urticaria, and others (Table 1) [1-8]. As progesterone sensitivity has been the most commonly identified cause, dermatologic diseases associated with the menstrual cycle have been labeled autoimmune progesterone dermatitis (APD) [4]. The first documented case of APD was in 1921, in which a patient's premenstrual serum caused acute urticarial lesions. In addition, it was shown that the patient's premenstrual serum could be used to desensitize and improve her symptoms [9]. Since 1921, approximately 50 cases of APD have been published in the medical literature. Table 1 Dermatologic manifestations of autoimmune progesterone dermatitis - Urticaria - Angioedema - Eczema - Erythema multiforme - Stomatitis - Folliculitis - Papulopustular/papulovesicular lesions - Stephens-Johnson syndrome - Vesiculobullous reactions - Dermatitis herpetiformis-like rash - Mucosal lesions Clinical Features The clinical symptoms of APD (eczema, urticaria, angioedema, etc.) usually begin 3–10 days prior to the onset of menstrual flow, and end 1–2 days into menses. Severity of symptoms can vary from nearly undetectable to anaphylactic in nature, and symptoms can be progressive [10,11]. There are no specific histological features on biopsy in APD [12]. The age of onset is variable, with the earliest age reported at menarche [13]. Some studies have noted that a majority of patients had taken an oral contraceptive (OCP) prior to the onset of APD [14], but multiple cases exist in which women have never been exposed to exogenous progesterone [15-17]. The symptoms of APD correlate with progesterone levels during the luteal phase of the menstrual cycle. Progesterone begins to rise 14 days prior to the onset of menses, peaks 7 days prior to menses, and returns to a low baseline level 1–2 days after menses begins. In studies where an etiologic agent has been sought, progesterone has been found most frequently. However, estrogen, prostacyclin, and gonadotropin levels have correlated with symptoms in some cases [18-21]. Symptoms may first appear, improve, or worsen during pregnancy and the peripartum period [2,22-24]. In addition, APD during pregnancy has been associated with spontaneous abortions [2,25]. Pregnancy is associated with an increase of maternal progesterone levels, which may explain the initiation or worsening of symptoms. In regards to an improvement of symptoms during pregnancy, a number of theories have emerged. Explanations include a slow rise of progesterone during pregnancy that acts as a method of desensitization, a decrease in maternal immune response during pregnancy, or an increased production of anti-inflammatory glucocorticoids [13,25,26]. Pathogenesis The exact pathogenesis of APD is unknown. If exogenous progesterones (i.e. OCPs) are initially used, it is conceivable that uptake by antigen presenting cells and presentation to TH2 cells could result in subsequent IgE synthesis; however this mechanism would not explain the pathogenesis in patients such as ours who have the onset of APD prior to exogenous progesterone exposure. Some authors have suggested that hydrocortisone or 17-α-hydroxyprogesterone have cross-sensitivity with progesterone and may cause initial sensitization, but this has not been observed in all studies [27,28]. To further delineate the pathogenesis, antibodies against progesterone have been investigated. Using immunofluorescent techniques and basophil degranulation tests, studies have found that such antibodies do exist in certain patients with APD [1,13,29]. However, negative results looking for antibodies have also been reported [24]. In addition, skin test results with progesterone have shown immediate reactions (within 30 minutes), delayed reactions (24–48 hours later), and reactions with features of both immediate and delayed features [13,14,30,31]. This presumably indicates both type I and type IV hypersensitivity reactions. Progesterone has also been reported to have a direct histamine releasing effect on mast cells, yet very little research has been done to support this hypothesis [32]. Additionally, one study found an in vitro increase of an interferon-γ release assay, possibly implying a role for TH1-type cytokines in APD [33]. Eosinophils may also be involved in the pathogenesis of APD. Eosinophilia has been correlated with cutaneous symptoms in some cases, and studies have found a decrease in total eosinophil count after therapy [13,29,34]. Whether increased eosinophils are a response to cytokines from lymphocytes or play a primary mechanistic role in APD remains to be determined. Diagnosis The diagnosis of APD requires an appropriate clinical history accompanied by an intradermal injection test with progesterone. An aqueous suspension or aqueous alcohol solution of progesterone is the preferable vehicle of testing as progesterone in oil can cause an irritant reaction [35], though many published case reports have used progesterone in oil for testing. Various authors have advocated different amounts of progesterone or medroxyprogesterone to be used for testing [12,33,36]. As had been done in some prior studies, the patient presented here was tested with progesterone in aqueous solution at a concentration of 50 mg/mL. As mentioned above, APD may be due to an immediate or delayed hypersensitivity reaction. Therefore, intradermal testing may not become positive until 24–48 hours later [14,24]. In addition, some authors have advocated patch testing with progesterone to further evaluate for a hypersensitivity reaction [33]. Of note, intradermal testing has been negative in some patients with typical clinical symptoms of APD and who improved after APD treatment [2,3,24]. Some authors have recommended further tests to evaluate the immunologic evidence in APD. These include circulating antibodies to progesterone, basophil granulation tests, direct and indirect immunofluorescence to luteinizing cells of the corpus luteum, in vitro interferon-γ release, and circulating antibodies to 17-α-hydroxyprogesterone [1,7,13,29,33,36]. However, most case reports in the medical literature do not routinely check for serologic evidence of APD, and when checked these markers have not always been found to be reliable. This is most likely due to the fact that, as mentioned above, the pathogenesis of APD is incompletely understood. Treatment Autoimmune progesterone dermatitis is usually resistant to conventional therapy such as antihistamines. The use of systemic glucocorticoids, usually in high doses, has been reported to control the cutaneous lesions of APD is some studies, but not in others [3,10,37]. Early reports of APD describe attempts of progesterone desensitization, and some authors even attempted injections derived from the corpus luteum [18,24,38]. However, results were usually temporary, and such methods of treatment have now fallen out of favor. Current therapeutic modalities often attempt to inhibit the secretion of endogenous progesterone by the suppression of ovulation. Table 2 lists some of the pharmacologic strategies used in APD. Oral contraceptives (OCPs) are often tried as initial therapy, but have had limited success, possibly due to the fact that virtually all OCPs have a progesterone component. Conjugated estrogens have also been used in the treatment of APD. These did show improvement in many of the patients, but often required high doses [2,16,22]. However, due to the increased risk of endometrial carcinoma with unopposed conjugated estrogens, this treatment is not commonly used today [39]. Table 2 Treatment options used in autoimmune progesterone dermatitis Treatment Option Advantages Disadvantages Oral Contraceptives (OCPs) - Usually tried as initial therapy - Limited success due to the progesterone component of OCPs - Fewer side effects than other most other therapies Antihistamines - Well tolerated, few side effects - Rarely effective as monotherapy - Does not address underlying mechanism Conjugated Estrogens - Avoids progesterone component of OCPs - Increased risk of endometrial cancer, not commonly used today - Often require high doses Glucocorticoids - Able to suppress multiple components of the immune system - Usually not effective alone - Can be combined with other therapies - Often require high doses GnRH Agonists - Often used if OCPs and glucocorticoids are not effective - Can cause symptoms of estrogen deficiency (hot flashes, decreased bone mineral density) Alkaylated Steroids - Can be combined with low dose steroids - Can cause symptoms of excess androgens (facial hair, hepatic dysfunction, mood disorders) - Interferes with gonadal hormone receptors Tamoxifen - Has been used successfully in patients unresponsive to conjugated estrogen - Can cause symptoms of estrogen deficiency - Increased risk of venous thrombosis and cataract formation Bilateral oopherectomy - Definitive treatment, used if medical options unsuccessful - Surgical procedure, associated morbidity - Symptoms of estrogen deficiency Various other therapy modalities are currently used in APD, and there is no clear treatment of choice. GnRH agonists, such as buserelin and triptorelin, have been used to induce remission of symptoms by causing ovarian suppression [7,11,15]. However, side effects include symptoms of estrogen deficiency (hot flashes, vaginal dryness, decreased bone mineral density), and estrogen supplementation may be needed [40]. Alkaylated steroids such as stanozol have been used to successfully suppress ovulation, sometimes in combination with chronic low doses of corticosteroids [37]. Side effects of alkaylated steroids include abnormal facial or body hair growth, hepatic dysfunction, and mood disorders, any of which may limit their use. To decrease the risk of side effects, some authors have recommended using the alkaylated steroid only in the perimenstrual period [37]. Another therapeutic option used in APD has been the antiestrogen tamoxifen, which also can suppress ovulation [3,5]. As with GnRH agonists, patients on tamoxifen may experience symptoms of estrogen deficiency. In addition, tamoxifen has been associated with an increased risk of venous thrombosis and cataract formation. In some patients with unremitting symptoms of APD, bilateral oopherectomy has been required [10,15,24]. While this definitive treatment has been successful in controlling symptoms, today it is rarely used before all medical options have been exhausted. Conclusion Autoimmune progesterone dermatitis is a condition seen in a small number of women who present with eczema, erythema multiforme, stomatitis, papulopustular lesions, folliculitis, angioedema, urticaria, and other skin manifestations in relation to the menstrual cycle. It is usually seen 3–10 days prior to the onset of menstrual flow, but may be difficult to recognize in women with irregular menses. The exact pathogenesis is unknown, and is thought to involve a hypersensitivity reaction to progesterone. The diagnosis of APD is made by an appropriate clinical history accompanied by an intradermal injection test with progesterone. Current treatment modalities often attempt to inhibit the secretion of endogenous progesterone, but may be unsuccessful. More research is needed into the pathogenesis of APD to most appropriately care for these patients. ==== Refs Jones WN Gordon VH Auto-immune progesterone eczema. An endogenous progesterone hypersensitivity Arch Dermatol 1969 99 57 59 5761807 10.1001/archderm.99.1.57 Wojnarowska F Greaves MW Peachey RD Drury PL Besser GM Progesterone-induced erythema multiforme J R Soc Med 1985 78 407 408 3989808 Stephens CJ Wojnarowska FT Wilkinson JD Autoimmune progesterone dermatitis responding to Tamoxifen Br J Dermatol 1989 121 135 137 2757950 Stone J Downham T Autoimmune progesterone dermatitis Int J Dermatol 1981 20 50 51 6451592 Moghadam BK Hersini S Barker BF Autoimmune progesterone dermatitis and stomatitis Oral Surg Oral Med Oral Pathol Oral Radiol Endod 1998 85 537 541 9619670 10.1016/S1079-2104(98)90287-6 Wilkinson SM Beck MH Kingston TP Progesterone-induced urticaria--need it be autoimmune? Br J Dermatol 1995 133 792 794 8555037 Yee KC Cunliffe WJ Progesterone-induced urticaria: response to buserelin Br J Dermatol 1994 130 121 123 8305302 Shelley WB Preucel RW Spoont SS Autoimmune progesterone dermatitis Arch Dermatol 1973 107 896 901 4351124 10.1001/archderm.107.6.896 Gerber J Desensitization in the treatment of menstraul intoxication and other allergic symptoms Br J Dermatol 1930 51 265 268 Snyder JL Krishnaswamy G Autoimmune progesterone dermatitis and its manifestation as anaphylaxis: a case report and literature review Ann Allergy Asthma Immunol 2003 90 469 77; quiz 477, 571 12775127 Slater JE Raphael G Cutler G. B., Jr. Loriaux DL Meggs WJ Kaliner M Recurrent anaphylaxis in menstruating women: treatment with a luteinizing hormone-releasing hormone agonist--a preliminary report Obstet Gynecol 1987 70 542 546 3306508 Vasconcelos C Xavier P Vieira AP Martinho M Rodrigues J Bodas A Barros MA Mesquita-Guimaraes J Autoimmune progesterone urticaria Gynecol Endocrinol 2000 14 245 247 11075293 Farah FS Shbaklu Z Autoimmune progesterone urticaria J Allergy Clin Immunol 1971 48 257 261 4398434 Hart R Autoimmune progesterone dermatitis Arch Dermatol 1977 113 426 430 192155 10.1001/archderm.113.4.426 Rodenas JM Herranz MT Tercedor J Autoimmune progesterone dermatitis: treatment with oophorectomy Br J Dermatol 1998 139 508 511 9767301 10.1046/j.1365-2133.1998.02420.x Leech SH Kumar P Cyclic urticaria Ann Allergy 1981 46 201 203 7212388 Moody BR Schatten S Autoimmune progesterone dermatitis: onset in a women without previous exogenous progesterone exposure South Med J 1997 90 845 846 9258316 Meltzer L Hypersensitivity to gonadal hormones South Med J 1963 56 538 542 13934755 Wahlen T Endocrine allergy; a study in 35 cases with premenstrual symptoms of allergic type Acta Obstet Gynecol Scand 1955 34 161 170 14398165 Burstein M Rubinow A Shalit M Cyclic anaphylaxis associated with menstruation Ann Allergy 1991 66 36 38 1987869 Phillips EW Clinical evidence of sensitivity to gonadotropins in allergic women Ann Intern Med 1949 30 364 365 Teelucksingh S Edwards CR Autoimmune progesterone dermatitis J Intern Med 1990 227 143 144 2137160 Pinto JS Sobrinho L da Silva MB Porto MT Santos MA Balo-Banga M Arala-Chaves M Erythema multiforme associated with autoreactivity to 17 alpha-hydroxyprogesterone Dermatologica 1990 180 146 150 2340924 Shelley WB Preucel RW Spoont SS Autoimmune progesterone dermatitis: cure by oopherectomy J Am Med Assoc 1964 190 35 38 Bierman SM Autoimmune progesterone dermatitis of pregnancy Arch Dermatol 1973 107 896 901 4351124 10.1001/archderm.107.6.896 Urbach E Menstruation allergy or menstruation toxicosis Int Clin 1939 160 Wilkinson SM Beck MH The significance of positive patch tests to 17-hydroxyprogesterone Contact Dermatitis 1994 30 302 303 8088149 Schoenmakers A Vermorken A Degreef H Dooms-Goossens A Corticosteroid or steroid allergy? Contact Dermatitis 1992 26 159 162 1505180 Miura T Matsuda M Yanbe H Sugiyama S Two cases of autoimmune progesterone dermatitis. Immunohistochemical and serological studies Acta Derm Venereol 1989 69 308 310 2568048 Katayama I Nishioka K Autoimmune progesterone dermatitis with persistent amenorrhoea Br J Dermatol 1985 112 487 491 3158328 Georgouras K Autoimmune progesterone dermatitis Australas J dermatol 1981 12 109 112 7344688 Slater JE Kaliner M Effects of sex hormones on basophil histamine release in recurrent idiopathic anaphylaxis J Allergy Clin Immunol 1987 80 285 290 2442235 Halevy S Cohen AD Lunenfeld E Grossman N Autoimmune progesterone dermatitis manifested as erythema annulare centrifugum: Confirmation of progesterone sensitivity by in vitro interferon-gamma release J Am Acad Dermatol 2002 47 311 313 12140482 Mittman RJ Bernstein DI Steinberg DR Enrione M Bernstein IL Progesterone-responsive urticaria and eosinophilia J Allergy Clin Immunol 1989 84 304 310 2778236 Zondek B Bromberg YM Endocrine allergy: allergic sensitivity to endogenous hormones J Allergy 1945 16 1 16 Herzberg AJ Strohmeyer CR Cirillo-Hyland VA Autoimmune progesterone dermatitis J Am Acad Dermatol 1995 32 333 338 7829735 10.1016/0190-9622(95)90398-4 Brestel EP Thrush LB The treatment of glucocorticosteroid-dependent chronic urticaria with stanozolol J Allergy Clin Immunol 1988 82 265 269 3403867 Guy WH Jacob FM Guy WB Sex hormone sensitization (corpus luteum) AMA Arch Derm Syphilol 1951 63 377 378 14810200 Ziel HK Finkle WD Increased risk of endometrial carcinoma among users of conjugated estrogens N Engl J Med 1975 293 1167 1170 171569 Matta WH Shaw RW Hesp R Katz D Hypogonadism induced by luteinising hormone releasing hormone agonist analogues: effects on bone density in premenopausal women Br Med J (Clin Res Ed) 1987 294 1523 1524 3111619 Shahar E Bergman R Pollack S Autoimmune progesterone dermatitis: effective prophylactic treatment with danazol Int J Dermatol 1997 36 708 711 9352418 10.1046/j.1365-4362.1997.00105.x

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==== Front Health Qual Life OutcomesHealth and Quality of Life Outcomes1477-7525BioMed Central London 1477-7525-2-391528386310.1186/1477-7525-2-39ResearchA randomised controlled trial to measure the effect of chest pain unit care upon anxiety, depression, and health-related quality of life [ISRCTN85078221] Goodacre Steve 1s.goodacre@sheffield.ac.ukNicholl Jon 1j.nicholl@sheffield.ac.uk1 Medical Care Research Unit, University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK2004 29 7 2004 2 39 39 24 5 2004 29 7 2004 Copyright © 2004 Goodacre and Nicholl; licensee BioMed Central Ltd.2004Goodacre and Nicholl; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background The chest pain unit (CPU) has been developed to provide a rapid and accurate diagnostic assessment for patients attending hospital with acute, undifferentiated chest pain. We aimed to measure the effect of CPU assessment upon psychological symptoms and health-related quality of life. Methods We undertook a single-centre, cluster-randomised controlled trial. Days (N = 442) were randomised in equal numbers to CPU or routine care. Patients with acute chest pain, undiagnosed by clinical assessment, ECG and chest radiograph, were recruited and followed up with self-completed questionnaires (SF-36 and HADS) at two days and one month after hospital attendance. Results Patients receiving CPU assessment had significantly higher scores on the physical functioning (difference 5.1 points; 95% CI 1.1 to 9.0), vitality (4.6; 1.3 to 8.0), and general health (5.7; 2.3 to 9.2) dimensions of the SF-36 at two days, and significantly higher scores on all except the emotional role dimension at one month. They also had significantly lower depression scores on the HADS depression scale at two days (0.93; 0.34 to 1.51) and one month (1.0; 0.36 to 1.66). However, initially lower anxiety scores at two days (0.89; 0.21 to 1.56) were not maintained at one month (0.48; -0.26 to 1.23). CPU assessment was associated with reduced prevalence (OR 0.71; 95% CI 0.52 to 0.97) and severity (6.5 mm on 100 m visual analogue scale; 95% CI 2.2 to 10.8) of chest pain at one month, but no significant difference in the proportion of patients taking time off work (OR 0.82; 95% CI 0.54 to 1.04). Conclusion CPU assessment is associated with improvements in nearly all dimensions of quality of life and with reduced symptoms of depression. ==== Body Background Acute chest pain is a common reason for emergency hospital attendance and admission. Patients with chest pain that remains undiagnosed after clinical assessment, ECG and chest radiograph pose a particular problem. They carry a low, but important risk of an acute coronary syndrome [1]. The potentially life-threatening nature of this diagnosis means that a cautious approach is often taken, with many patients being admitted to hospital for observation and investigation [2]. Yet most patients with undifferentiated chest pain do not have a coronary syndrome, whereas anxiety and psychological morbidity are common [3-5] and appear to be associated with impaired quality of life [6]. It is possible that anxiety could be influenced by the investigation and management of chest pain. If this is so, then decision analysis modelling suggests that the potential health gains that could be achieved by reducing anxiety and improving quality of life among the majority of patients who do not have an acute coronary syndrome substantially outweigh the potential health gains from detecting and treating acute coronary syndromes [7]. The chest pain unit (CPU) was developed to provide rapid and accurate diagnosis for patients presenting with acute undifferentiated chest pain [8]. Patients receive up to six hours of observation and biochemical testing followed by an exercise treadmill test. If these tests are positive then they are admitted to hospital with a clear diagnosis, if negative they are discharged home. Evaluation of CPU care has focussed upon cardiac events, process measures and economic measures [9]. There is some evidence that CPU care is associated with improved diagnostic certainty [10] and patient satisfaction [11], but no data to compare psychological morbidity and quality of life after CPU and routine care, despite substantial data to suggest that this is an important problem for patients [3-5,12-14]. The ESCAPE (effectiveness and safety of chest pain evaluation to prevent emergency admission) trial was a randomised controlled trial and economic evaluation of CPU versus routine care that showed that CPU care was associated with reduced hospital admission [15], improved health utility [15] and improved patient satisfaction [16], and was likely to be considered cost-effective [15]. This paper reports quality of life and psychological measures from the ESCAPE trial. We aimed to measure the effect of CPU care upon anxiety, depression, and health related quality of life, and to determine whether CPU care reduced subsequent symptoms of chest pain. Methods The Northern General Hospital Emergency Department provides adult emergency care to the 530,000 population of Sheffield, United Kingdom. In 1999 a CPU was established in the emergency department, staffed by three specialist chest pain nurses, and able to accommodate up to six patients with acute undifferentiated pain. Patients were selected using validated clinical predictors and received two to six hours of observation and biochemical cardiac testing, followed by, where appropriate, an exercise treadmill test. Full details of the CPU protocol have been published [17]. Routine care, prior to development of the CPU, consisted of assessment by a doctor who had access to biochemical cardiac tests, but not observation facilities or exercise treadmill testing. From 5th February 2001 to 5th May 2002 the CPU was subject to a cluster randomised controlled trial. Days of the week (N = 442) were randomised to CPU or routine care in equal numbers. All patients attending with acute chest pain were screened for eligibility in the trial. Patients were excluded if they had ECG changes diagnostic for an acute coronary syndrome, clinically obvious unstable angina, co-morbidity or alternative pathology requiring hospital admission (e.g. suspected pulmonary embolus), negligible risk of acute coronary syndrome (e.g. age less than 25 years), or if they were unable to consent to participation. Written, informed consent was requested and patients who agreed to participate were followed up in a review clinic at two days, and by postal questionnaire at one month. The study protocol was approved by the North Sheffield Research Ethics Committee. Full details of the ESCAPE trial have been published [15]. Health related quality of life was measured using the SF-36 questionnaire [18]. Anxiety and depression were measured using the Hospital Anxiety Depression Scale (HADS) [19]. Both are widely used, validated, self-completed questionnaires. Both were administered at two days and one month. At two days patients were handed the questionnaires in the review clinic and asked to complete it in their own time and return it to the Medical Care Research Unit. No reminder was sent to non-responders to this questionnaire. Further questionnaires were mailed at one month with one re-mailing for non-responders. A brief additional questionnaire was sent at one month that was designed specifically for the study. This predominantly asked questions about health service use for the economic evaluation, but also asked participants whether they had suffered any further chest pain. If they responded that they had, they were asked to score the severity of the chest pain on a 100 mm visual analogue scale. A further question asked whether the patient had taken time off work since their hospital attendance. The sample size estimate of 988 was based upon the primary outcome measure, the proportion of patients admitted to hospital. Assuming a response rate of 65% to the questionnaires, this sample size would provide 80% power to detect an effect size of 0.25 for these outcomes (alpha = 0.05). Using standard deviations derived from a two-week pilot study, this effect size equates to 1.1 points on the HADS anxiety or depression scores, 11.5 points of the SF-36 physical or emotional role dimensions, and 6 points on the other SF-36 dimensions. Data was analysed using Stata statistical software (version 8.0). Multi-level random effects modelling was used with day of week as a random effect to adjust for clustering by day of week. For the principal analysis no adjustment for confounding was made. For secondary analysis age, gender and past history of coronary heart disease were included as covariates (determined a priori to be important potential confounders), along with any variable that showed significant (p < 0.05) baseline imbalance between the study groups. Results During the 442-day study period there were 6957 attendances with chest pain or a related complaint. Of these, 764 (11.0%) had ECG changes diagnostic for an acute coronary syndrome, 2402 (34.5%) had clinically obvious unstable angina, 869 (12.5%) had co-morbidity or alternative pathology requiring hospital admission, 1291 (18.6%) had negligible risk of acute coronary syndrome, and 513 patients (7.4%) were unable to participate in the trial or provide consent. The remaining 1118 patients (16.1%) were asked to participate in the trial and 972 agreed (86.9%). Response rates were: 717 (73.8%) to the initial questionnaire and 679 (69.9%) to the one-month questionnaire. The CONSORT diagram and full details of exclusions have been published elsewhere [15]. Baseline characteristics of the study groups are shown in Table 1. Source of referral, smoking status, and ECG at presentation showed significant baseline imbalance. Hence secondary analyses adjusted for these covariates, along with age, gender and past history of coronary heart disease. Table 1 Baseline characteristics of the study groups CPU care Routine care Age (years) 49.4 49.6 Male sex (%) 304 (63.5%) 318 (64.5%) Known CHD (%) 16 (3.3%) 27 (5.5%) Hypertension (%) 127 (26.5%) 120 (24.3%) Diabetes (%) 17 (3.5%) 29 (5.9%) Hyperlipidaemia (%) 58 (12.1%) 70 (14.2%) Smoker (%) 169 (35.3%) 143 (29.0%) Family history (%) 189 (39.5%) 200 (40.6%) Pain nature Indigestion / burning 60 (12.5%) 56 (11.4%) Stabbing / sharp 116 (24.2%) 113 (22.9%) Aching / dull / heavy 175 (36.5%) 181 (36.7%) Gripping / crushing 66 (13.8%) 59 (12.0%) Other 57 (11.9%) 71 (14.4%) Pain site Central 317 (66.2%) 335 (68.0%) Left chest 129 (26.9%) 125 (25.4%) Right chest 19 (4.0%) 16 (3.2%) Other 8 (1.7%) 8 (1.6%) Pain radiation None 183 (38.2%) 189 (38.3%) Left arm 118 (24.6%) 142 (28.8%) Right arm 31 (6.5%) 26 (5.3%) Neck 22 (4.6%) 22 (4.5%) Jaw 15 (3.1%) 13 (2.6%) Back 70 (14.6%) 53 (10.8%) Other 27 (5.6%) 30 (6.1%) Pain duration Continuous pain 312 (65.1%) 341 (69.2%) Intermittent pain 93 (19.4%) 95 (19.3%) Other symptoms Nausea 129 (26.9%) 161 (32.7%) Vomiting 25 (5.2%) 31 (6.3%) Dyspnoea 185 (38.6%) 202 (41.0%) Sweating 192 (40.1%) 210 (42.6%) ECG at presentation ECG normal (%) 412 (89.0%) 382 (82.2%) ECG non-specific (%) 38 (8.2%) 64 (13.8%) ECG old change (%) 13 (2.8%) 19 (4.1%) Source of referral GP referral 138 (28.8%) 116 (23.5%) Self referred 173 (36.1%) 155 (31.4%) 999 145 (30.3%) 189 (38.3%) Other 23 (4.8%) 33 (6.7%) Table 2 shows the final diagnosis recorded in the case notes, after hospital attendance and admission, of the most senior clinician to care for the patient. Those receiving routine care were more likely to have received a diagnosis of angina, whereas those receiving CPU care were more likely to have received a non-specific or non-cardiac diagnosis. Table 2 Diagnostic impression after initial hospital attendance Diagnosis CPU care Routine care Non-specific chest pain 144 (30.1%) 125 (25.4%) Anxiety 13 (2.7%) 21 (4.3%) Angina 63 (13.2%) 123 (24.9%) Myocardial infarction 28 (5.8%) 27 (5.5%) Gastro-oesophageal pain 74 (15.4%) 60 (12.2%) Musculo-skeletal pain 122 (25.5%) 106 (21.5%) Other diagnosis 26 (5.4%) 18 (3.7%) Not recorded 9 (1.9%) 13 (2.6%) P < 0.0001 for the difference in distribution across the categories Table 3 shows the mean SF-36 scores for both groups at two days, with the adjusted difference, 95% confidence interval, p-value and intraclass correlation coefficient. Table 4 shows these estimates at one month. At two days, CPU care was associated with significant improvements in physical functioning, vitality and general health. At one month, CPU care was associated with significant improvements in all dimensions of quality of life, except the emotional role dimension. Table 3 Mean SF-36 scores at two days N (% completed) CPU care Routine care Difference 95% CI P-value ρ Unadjusted Adjusted Physical functioning 694 (96.7%) 74.8 69.7 5.1 1.1 to 9.0 0.012 0.002 4.2 0.4 to 7.9 0.029 Social functioning 703 (98.0%) 72.2 69.8 2.4 -1.7 to 6.6 0.252 0 1.5 -2.7 to 5.6 0.49 Role-physical 684 (95.4%) 50.4 46.0 4.4 -2.2 to 11.0 0.191 0.028 3.3 -3.3 to 10.0 0.326 Role-emotional 685 (95.5%) 64.7 59.5 5.2 -1.2 to 11.6 0.113 0 5.1 -1.2 to 11.4 0.111 Mental health 700 (97.6%) 66.9 64.7 2.2 -0.9 to 5.3 0.158 0 2.3 -0.7 to 5.4 0.132 Vitality 697 (97.2%) 52.3 47.6 4.6 1.3 to 8.0 0.007 0 4.6 1.3 to 8.0 0.007 Pain index 701 (97.7%) 50.8 49.0 1.8 -1.9 to 5.5 0.351 0 2.0 -1.7 to 5.7 0.284 General health 688 (96.0%) 60.3 54.5 5.7 2.3 to 9.2 0.001 0 5.4 2.0 to 8.8 0.002 Upper row shows unadjusted analysis (primary analysis) Lower row shows adjusted analysis (secondary analysis) ρ = Intraclass correlation coefficient. This provides a measure of the amount of clustering of each outcome by the unit of randomisation (day). Table 4 Mean SF-36 scores at one month N (% completed) CPU care Routine care Difference 95% CI P-value ρ Unadjusted Adjusted Physical functioning 654 (96.3%) 74.1 66.2 7.8 3.8 to 11.9 <0.001 0.025 7.6 3.6 to 11.5 <0.001 Social functioning 654 (96.3%) 74.6 67.0 7.6 3.2 to 12.0 0.001 0 6.8 2.4 to 11.2 0.002 Role-physical 638 (94.0%) 54.1 46.0 8.2 1.3 to 15.0 0.02 0 7.0 0.4 to 13.6 0.039 Role-emotional 630 (92.8%) 63.9 60.2 3.7 -3.0 to 10.5 0.281 0 3.9 -2.8 to 10.5 0.256 Mental health 653 (96.2%) 69.1 64.4 4.7 1.3 to 8.2 0.007 0 5.2 1.9 to 8.6 0.002 Vitality 649 (95.6%) 52.6 47.1 5.5 1.8 to 9.2 0.003 0 5.8 2.2 to 9.3 0.002 Pain index 655 (96.5%) 66.4 62.0 4.4 0.2 to 8.5 0.04 0 4.3 0.2 to 8.3 0.041 General health 651 (95.9%) 59.7 51.7 8.0 4.6 to 11.5 <0.001 0 8.1 4.6 to 11.5 <0.001 Upper row shows unadjusted analysis (primary analysis) Lower row shows adjusted analysis (secondary analysis) ρ = Intraclass correlation coefficient Table 5 shows the summary HADS data at two days and one month. CPU care was associated with lower depression scores at both two days and one month. An early significant reduction in anxiety associated with CPU care was no longer significant at one month. HADS data is also summarised in the Figure 1, categorised according to severity of anxiety and depression. Scores of zero to seven are normal, eight to ten are mild, eleven to fourteen are moderate, and fifteen to twenty-one are severe. Most participants had normal levels of depression, but only half reported normal levels of anxiety. CPU care was associated with increased prevalence of normal levels of anxiety at two days (53.4% vs 45.1%; p = 0.028) but not at one month (56.7% vs 50.8%; p = 0.129), and increased prevalence of normal levels of depression at two days (81.8% vs 72.9%; p = 0.005) and one month (80.4% vs 73.2%; p = 0.029). Table 5 Mean HADS scores at two days and one month N (% completed) CPU care Routine care Difference 95% CI P-value ρ Unadjusted Adjusted Anxiety- two days 702 (97.9%) 7.73 8.62 0.89 0.21 to 1.56 0.01 0 0.75 0.09 to 1.41 0.027 Depression-two days 701 (97.8%) 4.30 5.23 0.93 0.34 to 1.51 0.002 0 0.84 0.26 to 1.42 0.005 Anxiety-one month 645 (95.0%) 7.29 7.77 0.48 -0.26 to 1.23 0.203 0 0.58 -0.15 to 1.31 0.117 Depression-one month 644 (94.8%) 4.42 5.43 1.00 0.36 to 1.66 0.002 0 1.02 0.37 to 1.66 0.002 Upper row shows unadjusted analysis (primary analysis) Lower row shows adjusted analysis (secondary analysis) ρ = Intraclass correlation coefficient Figure 1 HADS scores categorised according to severity At one-month follow-up, 143 out of 318 participants (45.0%) receiving CPU care reported having further pain, compared to 168 out of 314 (53.5%) receiving routine care (unadjusted OR for further pain if receiving CPU care = 0.71, 95% CI 0.52 to 0.97, p = 0.032; adjusted OR = 0.65, 95% CI 0.10 to 0.76, p = 0.010). For those reporting further pain, the mean score on a 100 mm visual analogue pain score was 36.5 mm among those receiving CPU care and 43.0 mm among those receiving routine care (unadjusted difference = 6.5 mm, 95% CI 2.2 to 10.8, p = 0.003; adjusted difference= 6.8 mm, 95% CI 2.2 to 11.5, p = 0.004). Thus, at one month, CPU care was associated with a reduction in the incidence and severity of subsequent chest pain. One month after hospital attendance, 49 out of 315 participants receiving CPU care (15.6%) reported that they had taken time off work, compared to 58 out of 316 receiving routine care (18.4%). The unadjusted odds ratio for taking time off work after receiving CPU care was 0.82 (95% CI 0.54 to 1.24, p = 0.35; adjusted OR 0.79 (95% CI 0.59 to 1.22, p = 0.287). Discussion Main findings Patients with acute, undifferentiated chest pain who received CPU care had improved quality of life and reduced psychological symptoms. All dimensions of quality of life were improved at one month apart from the emotional role dimension. Anxiety was reduced two days after assessment, but there was no significant difference by one month, whereas reduced symptoms of depression at one month were still significant at one month. Patients receiving CPU care reported that subsequent symptoms of chest pain were less frequent and (if present) less severe. However, these reported differences in symptoms and quality of life were not associated with any significant difference in the need to take time off work. Comparison to other studies Previous studies of CPU care have focussed on cardiac events, process measures and economic measures [9]. One previous randomised trial found that CPU care was associated with greater diagnostic certainty [10] and improved patient satisfaction [11]. Our study suggests a more complicated picture, since more patients in the CPU group received a diagnosis of non-specific chest pain. CPU assessment may allow cardiac disease to be ruled out, but if an alternative diagnosis is not offered then this can hardly be said to increase diagnostic certainty, except in the somewhat convoluted sense that we may be more certain of what we know the cause is not. Nevertheless, CPU assessment was associated with reduced anxiety and improved quality of life. This is consistent with a previous study of diagnostic testing by Sox et al [20] that showed reduced anxiety among patients who were randomised to a more thorough outpatient diagnostic work-up for non-specific chest pain, but inconsistent with the findings of a study of exercise testing by Channer et al [21] that found no evidence of reassurance. Limitations of this study The main limitation of this study relates to our inability to blind participants to the intervention they received and to fact that they were involved in a trial of CPU care. Participants may have been influenced by this knowledge and improvements in psychological symptoms and quality of life may represent a positive response to receiving a novel form of care, rather than improvements specifically related to CPU care. The use of cluster randomisation has substantial advantages for pragmatic evaluation of changes in organisation, particularly if economic evaluation is undertaken [22]. However, the fact that randomisation occurs before recruitment means that there is the potential for selection bias. We attempted to reduce this risk by applying rigorous selection criteria and to address any potential bias by undertaking a secondary, adjusted analysis. Nevertheless it is possible that selection bias may have influenced the results. Although the measures used have been validated, they have not been widely used in the emergency setting. Changes in health status after an episode of chest pain may be very rapid, hence our need to measure outcomes only two days after intervention. Yet the HADS measures anxiety and depression over the previous week, while some SF-36 questions refer to the previous month. A recent episode of chest pain is likely to be an important determinant of reported health, but it may be that, if participants interpreted the questionnaires strictly, the initial questionnaire was recording health status before the intervention. Also, there may be doubts regarding what some of the outcomes are actually measuring. For example, some of the questions in the HADS measure symptoms that are useful markers for depression, such as levels of activity, which may also be changed by other health or social processes. Thus it may be that the reduced scores associated with CPU care measured on the depression scale relate to increased activity in response to the CPU exercise treadmill test, rather than reduced depression. Implications for practice and future research This study suggests that the assessment that patients receive when they present with acute chest pain can have an impact upon their subsequent health, even if this assessment does not, in most cases, provide a definitive diagnosis. It supports the findings of decision analysis modelling [7] that the potential health impact of chest pain assessment lies as much in addressing quality of life and psychological symptoms as in detecting and treating cardiac disease. The CPU assessment simply provides a rigorous and structured evaluation, yet this appears to have a significant effect upon anxiety (although this is not maintained), depression and quality of life. Yet it is not clear how this effect is achieved. It is possible that early, rigorous testing, particularly the exercise treadmill test, has a valuable effect in reassuring the patient that they are healthy and capable of normal physical functioning. Alternatively, it could be that consistent, reliable advice and attention from specialist chest pain nurses, rather than a variety of different doctors, is the key element. A third possibility, as previously discussed, is that bias plays an important role. Future research needs to determine which of these possibilities is the key factor. This is important for the specific issue of determining whether and how CPU care is effective, and thus what elements of CPU care are essential, and for the more general issue of exploring how diagnostic assessment effects subsequent well being. Conclusions CPU care for patients attending hospital with acute, undifferentiated chest pain is associated with reduced initial anxiety, reduced depression over the following month, and improvements in most dimensions of quality of life. Further research is required to establish how this effect is achieved. List of abbreviations OR: odds ratio CI: confidence interval ECG: electrocardiograph CPU: chest pain unit ESCAPE: effectiveness and safety of chest pain assessment to prevent emergency admission HADS: hospital anxiety depression scale Authors' contributions SG conceived and designed the study, analysed the data, drafted the paper, and participated in writing the final paper. JN assisted with study conception and design, supervised data analysis, and participated in writing the final paper. Acknowledgements We would like to thank all the members of the ESCAPE Research Team: Liz Cross, Simon Dixon, Simon Capewell, Deborah Quinney, Jane Arnold, Karen Angelini, Sue Revill, Tom Locker, Stephen Campbell and Francis Morris. ==== Refs Collinson PO Premachandram S Hashemi K Prospective audit of incidence of prognostically important myocardial damage in patients discharged from the emergency department BMJ 2000 320 1702 5 10864545 10.1136/bmj.320.7251.1702 Goodacre S Nicholl JP Beahan J Quinney D Capewell S National survey of the management of acute, undifferentiated chest pain British Journal of Cardiology 2002 10 50 4 Fleet RP Dupuis G Marchand A Burelle D Arsenault A Beitman BD Panic disorder in emergency department chest pain patients: prevalence, comorbidity, suicidal ideation and physician recognition Am J Med 1996 101 371 80 8873507 10.1016/S0002-9343(96)00224-0 Wulsin LR Hillard JR Geier P Hissa D Rouan GW Screening emergency room patients with atypical chest pain for depression and panic disorder Intl J Psychiatry Med 1988 18 315 23 Yingling KW Wulsin LR Arnold LM Rouan GW Estimated prevalences of panic disorder and depression among consecutive patients seen in an emergency department with acute chest pain J Gen Intern Med 1993 8 231 5 8505680 Goodacre S Mason S Arnold J Angelini K Psychological morbidity and health-related quality of life of patients assessed on a chest pain observation unit Ann Emerg Med 2001 38 369 76 11574792 10.1067/mem.2001.118010 Goodacre S Calvert N Cost-effectiveness of diagnostic strategies for acute, undifferentiated chest pain Emerg Med J 2003 20 429 33 12954681 10.1136/emj.20.5.429 Clancy M Chest pain units BMJ 2002 325 116 7 12130592 10.1136/bmj.325.7356.116 Goodacre SW Should we establish chest pain observation units in the United Kingdom? A systematic review and critical appraisal of the literature J Accid Emerg Med 2000 17 1 6 10658981 10.1136/emj.17.1.1 Roberts RR Zalenski RJ Mensah EK Rydman RJ Ciavarella G Gussow L Costs of an emergency department-based accelerated diagnostic protocol vs hospitalization in patients with chest pain. A randomized controlled trial JAMA 1997 278 1670 6 9388086 10.1001/jama.278.20.1670 Rydman RJ Zalenski RJ Roberts RR Albrecht GA Misieswicz VM Kampe L Patient satisfaction with an emergency department chest pain observation unit Ann Emerg Med 1997 29 109 15 8998089 Fleet RP Dupuis G Marchand A Burelle D Beitmen BD Panic disorder, chest pain and coronary artery disease: literature review Can J Cardiol 1994 10 827 34 7954018 Kisely SR The relationship between admission to hospital with chest pain and psychiatric disorder Australian and New Zealand Journal of Psychiatry 1998 32 172 9 9588295 Roll M Kollind M Theorell T Five-year follow-up of young adults visiting an emergency unit because of atypical chest pain J Intern Med 1992 231 59 65 1732400 Goodacre S Nicholl JP Dixon S Cross E Angelini K Arnold J Randomised controlled trial of a chest pain observation unit versus routine care BMJ 2004 328 254 7 14724129 10.1136/bmj.37956.664236.EE Goodacre S Quinney D Revill S Morris FM Capewell S Nicholl JP Patient and primary care physician satisfaction with chest pain unit and routine care Academic Emergency Medicine Goodacre S Morris FP Campbell S Angelini K Arnold J A prospective, observational study and cost analysis of a chest pain observation unit Emerg Med J 2002 19 117 21 11904256 10.1136/emj.19.2.117 Ware JE Snow KK Kosinski M Gandek B SF36 Health Survey: Manual and Interpretation Guide Boston, Massachusetts: The Health Institute, New England 1993 Zigmond AS Snaith RP The Hospital Anxiety and Depression Scale Acta Psychiatr Scand 1983 67 361 70 6880820 Sox HC JrMargulies I Sox CH Psychologically mediated effects of diagnostic tests Ann Intern Med 1981 95 680 5 7305144 Channer KS James MA Papouchado M Russel Rees J Failure of a negative exercise test to reassure patients with chest pain Q J Med 1987 63 315 22 3685244 Ukoumunne OC Gulliford MC Chinn S Sterne JAC Burney PGJ Methods for evaluating area-wide and organisation-based interventions in health and health care: a systematic review Health Technol Assess 1999 3 iii 92 10982317

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Health Qual Life Outcomes

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==== Front World J Surg OncolWorld Journal of Surgical Oncology1477-7819BioMed Central London 1477-7819-2-261528202610.1186/1477-7819-2-26Case ReportSmall B cell lymphocytic lymphoma presenting as obstructive sleep apnea Tsou Yung-An 1tsou121212@yahoo.com.twCheng Yuan-Kai 1keiko56@ms25.hinet.netLin Chia-Der 1chiader@seed.net.twChang Weng-Cheng 1joshua.tsou@msa.hinet.netTsai Ming-Hsui 1david@www.cmuh.org.tw1 Department of Otolaryngology, China Medical University Hospital, Taichung, Taiwan2004 29 7 2004 2 26 26 25 6 2004 29 7 2004 Copyright © 2004 Tsou et al; licensee BioMed Central Ltd.2004Tsou et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background Most lymphomas that involve the tonsil are large B cell lymphomas. Large B-cell lymphoma is a high grade malignancy which progresses rapidly. Tonsillar lymphoma usually presents as either a unilaterally enlarged palatine tonsil or as an ulcerative and fungating lesion over the tonsillar area. Small lymphocytic lymphomas (SLL) of the Waldeyer's ring are uncommon. Case presentation We report a 41-year-old male who presented with a ten-year history of snoring. Physical examination revealed smooth bilateral symmetrically enlarged tonsils without abnormal surface change or cervical lymphadenopathy. Palatal redundancy and a narrowed oropharyngeal airway were also noted. The respiratory disturbance index (RDI) was 66 per hour, and severe obstruction sleep apnea (OSA) was suspected. No B symptoms, sore throat, odynophagia or dysphagia was found. We performed uvulopalatopharyngoplasty (UPPP) and pathological examination revealed incidental small B-cell lymphocytic lymphoma (SLL). Conclusion It is uncommon for lymphoma to initially present as OSA. SLL is an indolent malignancy and is not easy to detect in the early stage. We conclude that SLL may be a contributing factor of OSA in the present case. ==== Body Background Adenotonsillar enlargement is the main cause of obstructive sleep apnea (OSA) in the pediatric population. However, this prevalent syndrome is more complicated in adults [1]. OSA has also been described in cases of benign lymphoid hyperplasia, plasmacytoma, amyloidosis, pharyngeal tumors and diseases that involve the nasopharyngeal structures. A series of careful examinations of the upper airway should be performed in every adult patient to check for anatomic causes related to upper airway obstruction [2]. We report here a patient with severe obstructive sleep apnea treated by uvulopalatopharyngoplasty (UPPP). Case presentation A 41-year-old man presented with complaints of snoring, excessive daytime sleepiness, and pavor nocturnes for more than 10 years. Systemic diseases were denied. Physical examination revealed bilateral symmetric and enlarged palatine tonsils without abnormal surface change. There were no palpable cervical lymph nodes or B symptoms (fever, body weight loss and cold sweats). White and red blood cell counts, biochemistry and chest radiographs were within normal limits. The results of an overnight polysomnography (PSG) showed mean SaO2, 91%, minimal SaO2, 62%, and a desaturation index (≥ 4%) of 61.8/h. The arousal index was 64.8/h and the respiratory disturbance index (RDI) was 66.0/h. Believing that the patient was suffering from severe OSA and hyperplastic palatine tonsils, he received UPPP. The postoperative course was uneventful and sleep apnea improved. PSG performed 4 months after surgery demonstrated that the RDI had reduced to 23.9/h. Pathology indicated small B cell lymphocytic lymphoma (Figure 1,2) with bone marrow involvement. During the whole course, the patient was free from B symptoms and no further abnormal lymphadenopathy was detected even after head and neck computed tomography (CT) and thallium scan (figure 3). Chemotherapy was started after evaluation at the oncology clinic. The patient is doing well and is on regular follow-up in the ENT and oncology clinics. Figure 1 a) surgical specimen of palatine tonsils; b) picture of oropharynx post UPPP 3 months later Figure 2 Photomicrograph a) effacement of normal architecture and infiltration of monotonous small lymphoid cells is visible (Hematoxylin and Eosin 100X); b) Bone marrow showing monotonous small lymphoid cells infiltration (Hematoxylin and Eosin 100X). Figure 3 a):Mild lymphadenopathy over bilateral posterior neck area; b:Gallium scan: gallium-avid lymphoma in bilateral submandibular regions and suspected lesions in the mid-abdomen Discussion Adenotonsillar enlargement is the leading cause of OSA in the pediatric population [1] though it is not so rare disorder in adults as well. The morbidity of OSA includes hypertension, arrhythmia, heart disease, erythrocytosis, and hyperlipidemia. Malignancy should be considered a potential contributing factor that rarely contributes to OSA and has never been shown to be related to it[2]. Small lymphocytic lymphoma (SLL) is an indolent but relentless malignancy, with a median survival of about 10 years. Because It usually presents as neck lymphadenopathy in the later stages, SLL is not easy to diagnose in the early stage. The effectiveness of chemotherapy for treating SLL is controversial. Most studies have found no benefit in treating patients until they develop symptoms [3]. Lymphoma presenting as OSA is extremely rare, but this case report illustrates that malignancy should be considered a potential contributing factor of OSA; a careful oropharyngeal examination in patients with OSA is necessary. Both tonsillectomy and UPPP can improve the patency of upper airway in OSA patients presenting with abnormally enlarged palatine tonsils. However, pathology of unsuspicious tissues can reveal malignancy with specific staining, and structural abnormalities secondary to a hidden malignancy might present initially as OSA. Therefore, a thorough physical examination should be performed and the pathological results should be closely traced. Nolan described a case of adenotonsillar enlargement due to chronic lymphatic leukemia which caused severe OSA [4]. His report highlights the need to consider OSA as a cause of constitutional symptoms in adults with lymphoreticular disease, especially when there is involvement of the Waldeyer's ring. Zorick et al., [5] reported that upper airway sleep apnea was exacerbated by lymphocytic lymphoma but that chemotherapy led to complete remission of well differentiated lymphocytic lymphoma and subsidence of OSA [5]. Abe et al., [6] described a patient with Non-Hodgkin's lymphoma who was successfully treated by tonsillar surgery and chemotherapy. In one published case, complete remission of centrocytic-centroblastic diffuse B cell lymphoma was found after tonsillectomy with UPPP, as in our case [7]. Conclusions Tonsillar surgery should be performed even on patients highly suspected of having lymphoma to improve OSA [8-10]. Neck CT is also suggested as a preoperative examination for patients with OSA and neck lymphadenopathy. Whether the prognosis or the outcome of chemotherapy or radiation therapy will be affected by tonsillar surgery is controversial. We conclude that SLL might be a contributing factor of OSA. Therefore careful neck examination should also be performed on patients complaining of snoring or sleep disturbances. Competing interest None declared. Authors' contributions YT, YC, CL, WC and MT made substantial contributions to the intellectual content of the paper, in the interpretation of results and in drafting the manuscript. All authors read and approved the manuscript Acknowledgement Patient consent was obtained for publication of his case record, scan and specimen photograph. ==== Refs Arens R McDonough JM Costarino AT Mahboubi S Tayag-Kier CE Maislin G Schwab RJ Pack AI Magnetic resonance imaging of the upper airway structure of children with obstructive sleep apnea syndrome Am J Respir Crit Care Med 2001 164 698 703 11520739 Strohl KP Goldman L, Ausiello D Obstructive sleep apnea-hypopnea syndrome Cecil Textbook of Medicine 2000 Philadelphia, W.B. Saunders Company 462 426 Keating MJ Goldman L, Ausiello D Chronic lymphocytic leukemia Cecil Textbook of Medicine 2000 Philadelphia, W.B. Saunders Company 949 953 Nolan P Chronic lymphatic leukemia presenting as severe obstructive sleep apnea Respirology 1996 1 299 301 9441119 Zorick F Roth T Kramer M Flessa H Exacerbation of upper-airway sleep apnea by lymphocytic lymphoma Chest 1980 77 689 690 6892693 Abe K Hori Y Ohtsu SY Koike Y A case of non-Hodgkin's lymphoma with macroglobulinemia Acta Otolaryngol Suppl 1996 523 259 262 9082801 King M Gleeson M Rees J Obstruction sleep apnea and tonsillar lymphoma Br Med J (Chin Res Ed) 1987 294 1605 1606 Ridgway D Wolff LJ Neerhout RC Tilford DL Unsuspected non-Hodgkin's lymphoma of the tonsils and adenoids in children Pediatrics 1987 79 399 402 3822639 Chehal A Haidar JH Jabbour R Yammout B Bazarbachi A Obstructive sleep apnea secondary to chronic lymphocytic leukemia Ann Oncol 2002 13 1833 12419760 10.1093/annonc/mdf277 Darrow DH Siemens C Indications for tonsillectomy and adenoidectomy Laryngoscope 2002 112 6 10 12172229 10.1097/00005537-200208001-00004

15282026

PMC509285

CC BY

2021-01-04 16:38:38

no

World J Surg Oncol. 2004 Jul 29; 2:26

utf-8

World J Surg Oncol

10.1186/1477-7819-2-26

oa_comm

==== Front World J Surg OncolWorld Journal of Surgical Oncology1477-7819BioMed Central London 1477-7819-2-261528202610.1186/1477-7819-2-26Case ReportSmall B cell lymphocytic lymphoma presenting as obstructive sleep apnea Tsou Yung-An 1tsou121212@yahoo.com.twCheng Yuan-Kai 1keiko56@ms25.hinet.netLin Chia-Der 1chiader@seed.net.twChang Weng-Cheng 1joshua.tsou@msa.hinet.netTsai Ming-Hsui 1david@www.cmuh.org.tw1 Department of Otolaryngology, China Medical University Hospital, Taichung, Taiwan2004 29 7 2004 2 26 26 25 6 2004 29 7 2004 Copyright © 2004 Tsou et al; licensee BioMed Central Ltd.2004Tsou et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background Most lymphomas that involve the tonsil are large B cell lymphomas. Large B-cell lymphoma is a high grade malignancy which progresses rapidly. Tonsillar lymphoma usually presents as either a unilaterally enlarged palatine tonsil or as an ulcerative and fungating lesion over the tonsillar area. Small lymphocytic lymphomas (SLL) of the Waldeyer's ring are uncommon. Case presentation We report a 41-year-old male who presented with a ten-year history of snoring. Physical examination revealed smooth bilateral symmetrically enlarged tonsils without abnormal surface change or cervical lymphadenopathy. Palatal redundancy and a narrowed oropharyngeal airway were also noted. The respiratory disturbance index (RDI) was 66 per hour, and severe obstruction sleep apnea (OSA) was suspected. No B symptoms, sore throat, odynophagia or dysphagia was found. We performed uvulopalatopharyngoplasty (UPPP) and pathological examination revealed incidental small B-cell lymphocytic lymphoma (SLL). Conclusion It is uncommon for lymphoma to initially present as OSA. SLL is an indolent malignancy and is not easy to detect in the early stage. We conclude that SLL may be a contributing factor of OSA in the present case. ==== Body Background Adenotonsillar enlargement is the main cause of obstructive sleep apnea (OSA) in the pediatric population. However, this prevalent syndrome is more complicated in adults [1]. OSA has also been described in cases of benign lymphoid hyperplasia, plasmacytoma, amyloidosis, pharyngeal tumors and diseases that involve the nasopharyngeal structures. A series of careful examinations of the upper airway should be performed in every adult patient to check for anatomic causes related to upper airway obstruction [2]. We report here a patient with severe obstructive sleep apnea treated by uvulopalatopharyngoplasty (UPPP). Case presentation A 41-year-old man presented with complaints of snoring, excessive daytime sleepiness, and pavor nocturnes for more than 10 years. Systemic diseases were denied. Physical examination revealed bilateral symmetric and enlarged palatine tonsils without abnormal surface change. There were no palpable cervical lymph nodes or B symptoms (fever, body weight loss and cold sweats). White and red blood cell counts, biochemistry and chest radiographs were within normal limits. The results of an overnight polysomnography (PSG) showed mean SaO2, 91%, minimal SaO2, 62%, and a desaturation index (≥ 4%) of 61.8/h. The arousal index was 64.8/h and the respiratory disturbance index (RDI) was 66.0/h. Believing that the patient was suffering from severe OSA and hyperplastic palatine tonsils, he received UPPP. The postoperative course was uneventful and sleep apnea improved. PSG performed 4 months after surgery demonstrated that the RDI had reduced to 23.9/h. Pathology indicated small B cell lymphocytic lymphoma (Figure 1,2) with bone marrow involvement. During the whole course, the patient was free from B symptoms and no further abnormal lymphadenopathy was detected even after head and neck computed tomography (CT) and thallium scan (figure 3). Chemotherapy was started after evaluation at the oncology clinic. The patient is doing well and is on regular follow-up in the ENT and oncology clinics. Figure 1 a) surgical specimen of palatine tonsils; b) picture of oropharynx post UPPP 3 months later Figure 2 Photomicrograph a) effacement of normal architecture and infiltration of monotonous small lymphoid cells is visible (Hematoxylin and Eosin 100X); b) Bone marrow showing monotonous small lymphoid cells infiltration (Hematoxylin and Eosin 100X). Figure 3 a):Mild lymphadenopathy over bilateral posterior neck area; b:Gallium scan: gallium-avid lymphoma in bilateral submandibular regions and suspected lesions in the mid-abdomen Discussion Adenotonsillar enlargement is the leading cause of OSA in the pediatric population [1] though it is not so rare disorder in adults as well. The morbidity of OSA includes hypertension, arrhythmia, heart disease, erythrocytosis, and hyperlipidemia. Malignancy should be considered a potential contributing factor that rarely contributes to OSA and has never been shown to be related to it[2]. Small lymphocytic lymphoma (SLL) is an indolent but relentless malignancy, with a median survival of about 10 years. Because It usually presents as neck lymphadenopathy in the later stages, SLL is not easy to diagnose in the early stage. The effectiveness of chemotherapy for treating SLL is controversial. Most studies have found no benefit in treating patients until they develop symptoms [3]. Lymphoma presenting as OSA is extremely rare, but this case report illustrates that malignancy should be considered a potential contributing factor of OSA; a careful oropharyngeal examination in patients with OSA is necessary. Both tonsillectomy and UPPP can improve the patency of upper airway in OSA patients presenting with abnormally enlarged palatine tonsils. However, pathology of unsuspicious tissues can reveal malignancy with specific staining, and structural abnormalities secondary to a hidden malignancy might present initially as OSA. Therefore, a thorough physical examination should be performed and the pathological results should be closely traced. Nolan described a case of adenotonsillar enlargement due to chronic lymphatic leukemia which caused severe OSA [4]. His report highlights the need to consider OSA as a cause of constitutional symptoms in adults with lymphoreticular disease, especially when there is involvement of the Waldeyer's ring. Zorick et al., [5] reported that upper airway sleep apnea was exacerbated by lymphocytic lymphoma but that chemotherapy led to complete remission of well differentiated lymphocytic lymphoma and subsidence of OSA [5]. Abe et al., [6] described a patient with Non-Hodgkin's lymphoma who was successfully treated by tonsillar surgery and chemotherapy. In one published case, complete remission of centrocytic-centroblastic diffuse B cell lymphoma was found after tonsillectomy with UPPP, as in our case [7]. Conclusions Tonsillar surgery should be performed even on patients highly suspected of having lymphoma to improve OSA [8-10]. Neck CT is also suggested as a preoperative examination for patients with OSA and neck lymphadenopathy. Whether the prognosis or the outcome of chemotherapy or radiation therapy will be affected by tonsillar surgery is controversial. We conclude that SLL might be a contributing factor of OSA. Therefore careful neck examination should also be performed on patients complaining of snoring or sleep disturbances. Competing interest None declared. Authors' contributions YT, YC, CL, WC and MT made substantial contributions to the intellectual content of the paper, in the interpretation of results and in drafting the manuscript. All authors read and approved the manuscript Acknowledgement Patient consent was obtained for publication of his case record, scan and specimen photograph. ==== Refs Arens R McDonough JM Costarino AT Mahboubi S Tayag-Kier CE Maislin G Schwab RJ Pack AI Magnetic resonance imaging of the upper airway structure of children with obstructive sleep apnea syndrome Am J Respir Crit Care Med 2001 164 698 703 11520739 Strohl KP Goldman L, Ausiello D Obstructive sleep apnea-hypopnea syndrome Cecil Textbook of Medicine 2000 Philadelphia, W.B. Saunders Company 462 426 Keating MJ Goldman L, Ausiello D Chronic lymphocytic leukemia Cecil Textbook of Medicine 2000 Philadelphia, W.B. Saunders Company 949 953 Nolan P Chronic lymphatic leukemia presenting as severe obstructive sleep apnea Respirology 1996 1 299 301 9441119 Zorick F Roth T Kramer M Flessa H Exacerbation of upper-airway sleep apnea by lymphocytic lymphoma Chest 1980 77 689 690 6892693 Abe K Hori Y Ohtsu SY Koike Y A case of non-Hodgkin's lymphoma with macroglobulinemia Acta Otolaryngol Suppl 1996 523 259 262 9082801 King M Gleeson M Rees J Obstruction sleep apnea and tonsillar lymphoma Br Med J (Chin Res Ed) 1987 294 1605 1606 Ridgway D Wolff LJ Neerhout RC Tilford DL Unsuspected non-Hodgkin's lymphoma of the tonsils and adenoids in children Pediatrics 1987 79 399 402 3822639 Chehal A Haidar JH Jabbour R Yammout B Bazarbachi A Obstructive sleep apnea secondary to chronic lymphocytic leukemia Ann Oncol 2002 13 1833 12419760 10.1093/annonc/mdf277 Darrow DH Siemens C Indications for tonsillectomy and adenoidectomy Laryngoscope 2002 112 6 10 12172229 10.1097/00005537-200208001-00004

15272938

PMC509286

CC BY

2021-01-04 16:37:47

no

Int J Behav Nutr Phys Act. 2004 Jul 23; 1:10

latin-1

Int J Behav Nutr Phys Act

10.1186/1479-5868-1-10

oa_comm

==== Front J Transl MedJournal of Translational Medicine1479-5876BioMed Central London 1479-5876-2-261528386210.1186/1479-5876-2-26CommentaryCancer immunotherapy: avoiding the road to perdition Chiriva-Internati Maurizio 1maurizio.chirivainternati@ttuhsc.eduGrizzi Fabio 23fabio.grizzi@humanitas.itBright Robert K 1Robert.Bright@ttmc.ttuhsc.eduMartin Kast W 4mkast@usc.edu1 Department of Microbiology & Immunology and Southwest Cancer Treatment and Research Center, Texas Tech University Health Science Center, Lubbock, TX, 79430, USA2 Scientific Direction, Istituto Clinico Humanitas, Rozzano, 20089 Milan, Italy3 "M. Rodriguez" Foundation – Institute for Quantitative Methods in Medicine, 20100 Milan, Italy4 Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, 90089 USA2004 29 7 2004 2 26 26 8 6 2004 29 7 2004 Copyright © 2004 Chiriva-Internati et al; licensee BioMed Central Ltd.2004Chiriva-Internati et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The hypothesis that human cancers express antigens that can be specifically targeted by cell mediated immunity has become a scientifically justifiable rationale for the design and clinical testing of novel tumor-associated antigens (TAA). Although a number of TAA have been recognized and it has been suggested that they could be useful in the immunological treatment of cancer, the complexity of human beings leads us to reflect on the need to establish new criteria for validating their real applicability. Herein, we show a system level-based approach that includes morphological and molecular techniques, which is specifically required to improve the capacity to produce desired results and to allow cancer immunotherapy to re-emerge from the mist in which it is currently shrouded. ==== Body Introduction Although considerable advances have been made in terms of our molecular and cellular knowledge, for most human disease states a fundamental understanding of causal disease onset, disease mechanism and progression, and optimal treatment is still significantly limited. In part, this advancement has been hampered by our inability to fully and rapidly delineate complex cellular metabolic processes and molecular pathways. Organisms are complex self-organizing entities made up of such parts: organs, tissues, cells, organelles and ultimately molecules and atoms. One question that arises, concerns the relationship between the whole and its component parts. The issue at stake is sometimes called "the question of reduction" or "the problem of reductionism" [1]. The inefficacy of contemporary science to describe biological systems, consisting of non-identical parts that have different and non-local interactions has tended to limit progress in the human healthcare. Many biological systems remain incomprehensible because their multifarious nature has been combined with a reductionist approach based on the linear conception of cause and effect. The use, however, of a more holistic multidimensional system level-based approach may provide new insights into the understanding of disease processes and mechanisms of action of therapeutical agents [2]. Herein we aim to introduce a system level-based approach that includes morphological and molecular techniques for validating the appropriateness of using novel tumor-associated antigens (TAA) for clinical purposes. This approach might be easily implemented for identifying prognostic, diagnostic and alternative biomarkers. Finally, this type of analysis of appropriately designed cohorts might also provide a key to understanding the differences in patients who do or do not respond to any particular therapy. This information may be helpful for a more effective (and therefore more cost-effective) design of clinical trials [2]. Immunotherapy and the human complexity The recognition and characterization of novel TAA is fundamental to the advance of cancer immunotherapy. The original hypothesis of Boon [3] and Rosenberg [4] that human cancers express antigens that can be specifically targeted by cell mediated immunity has become a scientifically justifiable rationale for the design and clinical testing of novel TAA based immunotherapies and therapeutic vaccines [5-7]. However, although a number of TAA have been discovered and it has been suggested that they could be useful in the immunological treatment of cancer, the complexity of human beings leads us to reflect on the need to establish compelling new criteria for validating their real applicability. Biological complexity can be intuitively appreciated – at least in terms of morphological or behavioral complexity, or the variety of cell types in an organism – but the term itself is notoriously difficult to define [8]. Human beings are complex hierarchical systems consisting of a number of levels of anatomical organization (genes, cells, tissues, organs, apparatuses, and organism) that interrelate differently with each other to form networks of growing complexity. The concept of anatomical entities as hierarchy of graduated forms, and the increasing number of known structural variables, have highlighted new properties of organized biological matter and raised a series of intriguing questions. In order to understand biology at the system level, we need to examine the structure and dynamics of the functions of organisms rather than the characteristics of their constitutive isolated parts [8-13]. The expression of TAA in biological materials has mainly been studied at the level of gene expression and gene level measurement by Reverse Transcriptase-Polymerase Chain Reaction (RT-PCR) analysis and the Quantitative real-time PCR (qrt-PCR) technology [14-17]. However, the information provided by these approaches is limited by the fact that the phenomena observed at each level of anatomical organization have properties that do not exist at a lower or higher level: RT-PCR and qrt-PCR may offer a satisfactory qualitative/quantitative description of small-scale structures, but this is likely to be irrelevant when it comes to large-scale features. The above considerations, in conjunction with the complexity of tumor-host interactions within the tumor microenvironment caused by temporal changes in tumor phenotypes and an array of immune mediators expressed in the tumor microenvironment [18] might clarify the limited reliability and applicability of current immunotherapeutic approaches. Here, we suggest a system level-based approach (Figure 1) for validating the appropriateness of using TAA for clinical purposes, which includes the following never defined before key points: Figure 1 System level-based approach for validating candidate TAA for clinical application. Aside from the well defined experimental procedure, the method presented here is based on the complex hierarchical nature of the human beings. The analysis begins at level of gene expression and then continues to higher levels of anatomical organization, (cell, tissue, organ, apparatuses and organism). This approach includes both morphological and molecular techniques. It also introduces the concept of dynamics of TAA expression at the level of the cell cycle, the physiological status of the organism and the process of aging. • Discriminating the cell types expressing the candidate antigen on the basis of the morphological visualization of all of the parts making up the organ under investigation. • Discriminating the candidate antigen's sub-cellular localization (at the level of cell nucleus, cytoplasm and/or plasma membrane) by ultra-structural morphological visualizations. • Mapping candidate antigen expression in all of the organs making up the apparatuses. • Mapping candidate antigen expression in all of the apparatuses making up the living organism. • Estimating the percentage of normal cells and their neoplastic counterparts expressing the candidate antigen. • Evaluating the dynamics of candidate antigen expression at the level of the cell cycle, the physiological status of the organism (i.e. the woman's menstrual cycle) and the process of aging. In order to advance our knowledge in a currently widely debated field of investigation, a clearer distinction must be made between in vitro laboratory results (the discovery and validation of target antigens) and their in vivo application (in vivo validation), and it is necessary to adopt a more complete experimental approach that forcefully includes both morphological and molecular techniques [19]. Conclusions Translational science which is aimed to test, in humans, novel therapeutic strategies developed through experimentation [20] should begin to consider the role of emergence in other words the appearance of unexpected structures and/or the occurrence of surprising behaviors in large systems composed from microscopic parts, whether physical or biological. By unexpected and surprising we mean structures and behaviors which are not intuitive and are not simply predictable. Since our understanding of complex human disease such as cancer, is still limited and pre-clinical models have shown a discouraging propensity [2,6] to fail when applied to humans, a new way of thinking is strongly needed that unites physicians, biologists, mathematicians and epidemiologists, in order to develop a better theoretical framework of tumor development, progression and tumor-host interactions. Although the model presented here is based on a multidisciplinary system-level approach probably within the reach of only very large and multi-talented laboratories, it is aimed to introduce a different way of investigating human cancer, which takes into account the complexity of the human being as a system. The use of a holistic approach, which enables a more accurate selection of immunotherapeutic target antigens in the first phase of the experimental research, will reduce the notable fragmentation of the biological information in the post-genomic era, and will facilitate a more accurate transfer of the acquired knowledge to the bedside. Further, this new multidisciplinary approach is specifically required to improve the capacity to produce desired results with a minimum expenditure of energy, time, or resources for immunotherapeutic treatments and to allow cancer immunotherapy to re-emerge from the mist in which it is currently shrouded. ==== Refs Ayala FJ Yates FE In Self-Organizing Systems-The Emergence of Order 1987 New York and London: Plenum Press 315 Morel NM Holland JM van der Greef J Marple EW Clish C Loscalzo J Naylor S Primer on medical genomics. Part XIV: Introduction to systems biology – a new approach to understanding disease and treatment Mayo Clin Proc 2004 79 651 658 15132407 van der Bruggen P Traversari C Chomez P Lurquin C De Plaen E Van den Eynde B Knuth A Boon T A gene encoding an antigen recognized by cytolytic T lymphocytes on a human melanoma Science 1991 254 1643 1647 1840703 Kawakami Y Eliyahu S Delgado CH Robbins PF Rivoltini L Topalian SL Miki T Rosenberg SA Cloning of the gene coding for a shared human melanoma antigen recognized by autologous T cells infiltrating into tumor Proc Natl Acad Sci USA 1994 91 3515 3519 8170938 Goldman B Cancer vaccines: finding the best way to train the immune system J Natl Cancer Inst 2002 94 1523 1526 12381703 10.1093/jnci/94.20.1523 Lewis JD Reilly BD Bright RK Tumor-associated antigens: from discovery to immunity Int Rev Immunol 2003 22 81 112 12962271 10.1080/08830180305221 Gilboa E The promise of cancer vaccines Nat Rev Cancer 2004 4 401 411 15122211 10.1038/nrc1359 Szathmary E Jordan F Pal C Molecular biology and evolution. Can genes explain biological complexity? Science 2001 292 1315 1316 11360989 10.1126/science.1060852 Noble D Modeling the heart–from genes to cells to the whole organ Science 2002 295 1678 1682 11872832 10.1126/science.1069881 Nurse P Reductionism. The ends of understanding Nature 1997 387 657 9192884 10.1038/42600 Brenner S Bock G, Goode JA The limits of Reductionism in Biology Novartis Found Symp 1998 213 John Wiley, London 106 116 9653718 Kitano H Computational systems biology Science 2002 295 1662 1664 11872829 10.1126/science.1069492 Goldenfeld N Kadanoff LP Simple lessons from complexity Science 1999 284 87 89 10102823 10.1126/science.284.5411.87 Juretic A Spagnoli GC Schultz-Thater E Sarcevic B Cancer/testis tumour-associated antigens: immunohistochemical detection with monoclonal antibodies Lancet Oncol 2003 4 104 109 12573352 10.1016/S1470-2045(03)00982-3 Lim SH Periman P Klug P Weidanz J Whitton V Chiriva-Internati M Wang Z Wright S Defining tumor antigens: mRNA, protein or cytotoxicity? Trends Immunol 2002 23 236 237 12102740 10.1016/S1471-4906(02)02196-8 Schultze JL Vonderheide RH From cancer genomics to cancer immunotherapy: toward second-generation tumor antigens Trends Immunol 2001 22 516 523 11525943 10.1016/S1471-4906(01)02015-4 Mocellin S Rossi CR Pilati P Nitti D Marincola FM Molecular oncology in the post-genomic era: the challenge of proteomics Trends Mol Med 2003 9 189 195 12763523 10.1016/S1471-4914(03)00047-9 Marincola FM Wang E Herlyn M Seliger B Ferrone S Tumors as elusive targets of T-cell-based active immunotherapy Trends Immunol 2003 24 335 342 12810110 Chiriva-Internati M Grizzi F Franceschini B Kast WM Is sperm protein 17 a useful target for tumor immunotherapy? Blood 2003 102 2308 2309 12959941 10.1182/blood-2003-05-1747 Marincola FM Translational Medicine: A two-way road J Transl Med 2003 1 1 14527344 10.1186/1479-5876-1-1

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PMC509287

CC BY

2021-01-04 16:39:24

no

J Transl Med. 2004 Jul 29; 2:26

utf-8

J Transl Med

10.1186/1479-5876-2-26

oa_comm

==== Front RetrovirologyRetrovirology1742-4690BioMed Central London 1742-4690-1-181528579110.1186/1742-4690-1-18ResearchSpecific TATAA and bZIP requirements suggest that HTLV-I Tax has transcriptional activity subsequent to the assembly of an initiation complex Ching Yick-Pang 12ypching@hkucc.hku.hkChun Abel CS 1cschun@hkusua.hku.hkChin King-Tung 1tonychin@hkusua.hku.hkZhang Zhi-Qing 3zhangzq@public3.bta.net.cnJeang Kuan-Teh kj7e@nih.govJin Dong-Yan 4dyjin@hkucc.hku.hk1 Department of Biochemistry, The University of Hong Kong, Pokfulam, Hong Kong, China2 Department of Pathology, The University of Hong Kong, Pokfulam, Hong Kong, China3 National Key Laboratory for Molecular Virology, Institute of Virology, 100 Yingxin Street, Beijing 100052, China4 Laboratory of Molecular Microbiology, National Institutes of Health, 9000 Rockville Pike, Bethesda, MD 20892-0460, USA2004 30 7 2004 1 18 18 27 5 2004 30 7 2004 Copyright © 2004 Ching et al; licensee BioMed Central Ltd.2004Ching et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background Human T-cell leukemia virus type I (HTLV-I) Tax protein is a transcriptional regulator of viral and cellular genes. In this study we have examined in detail the determinants for Tax-mediated transcriptional activation. Results Whereas previously the LTR enhancer elements were thought to be the sole Tax-targets, herein, we find that the core HTLV-I TATAA motif also provides specific responsiveness not seen with either the SV40 or the E1b TATAA boxes. When enhancer elements which can mediate Tax-responsiveness were compared, the authentic HTLV-I 21-bp repeats were found to be the most effective. Related bZIP factors such as CREB, ATF4, c-Jun and LZIP are often thought to recognize the 21-bp repeats equivalently. However, amongst bZIP factors, we found that CREB, by far, is preferred by Tax for activation. When LTR transcription was reconstituted by substituting either κB or serum response elements in place of the 21-bp repeats, Tax activated these surrogate motifs using surfaces which are different from that utilized for CREB interaction. Finally, we employed artificial recruitment of TATA-binding protein to the HTLV-I promoter in "bypass" experiments to show for the first time that Tax has transcriptional activity subsequent to the assembly of an initiation complex at the promoter. Conclusions Optimal activation of the HTLV-I LTR by Tax specifically requires the core HTLV-I TATAA promoter, CREB and the 21-bp repeats. In addition, we also provide the first evidence for transcriptional activity of Tax after the recruitment of TATA-binding protein to the promoter. ==== Body Background In eukaryotes, transcription by RNA polymerase II requires the orderly recruitment of basal transcription factors and activators to the core promoter and enhancers, respectively [1,2]. The core promoter contains the transcription initiation site, and it provides the docking sites for the basal transcription factors that nucleate the assembly of a functional preinitiation complex (PIC). The TATA box is one of four major core promoter elements, and it is specifically recognized by the TATA-binding protein (TBP), a subunit of the basal transcription factor TFIID which also contains at least 14 TBP-associated factors (TAFs). On the other hand, enhancers are bound by sequence-specific transcriptional activators that are thought to promote PIC assembly through interactions with components of the basal transcription machinery. Human T-cell leukemia virus type I (HTLV-I) Tax protein is a unique transcriptional regulator [3]. Tax can modulate the HTLV-I long terminal repeats (LTR), heterologous viral promoters, and a variety of cellular genes. In most context, Tax acts as a potent transcriptional activator through Tax-responsive DNA elements that are recognized by cellular transcription factors CREB, NFκB and serum response factor (SRF) [4-6]. For activation of the HTLV-I LTR, Tax targets three imperfectly conserved 21-bp direct repeats flanked by GC-rich sequences. In this scenario, Tax forms a ternary complex with CREB and the 21-bp repeat through physical interaction with CREB and direct contact with the flanking GC-rich sequences [7-9]. Tax-induced activation of other promoters is thought to be mediated through protein-protein interactions. Thus, Tax is a pleiotropic transcriptional activator that targets multiple enhancer elements through multiple cellular transcription factors. To date, the molecular mechanisms for Tax trans-activation have been well studied. Due to its pleiotropic activities, there are likely nuances to Tax's activity which remain unrevealed. Currently, we understand Tax to harbor a minimal activation domain [10], to interact with basal transcription factors such as TBP [11], to form a homo-dimer [12-14], and to stimulate the dimerization of cellular regulatory factors such as CREB [15,16] and IKK-γ [17]. Moreover, we also know that Tax can directly engage transcriptional coactivators such as CREB-binding protein, p300 and P/CAF [18-20]. However, it remains unclear what is Tax's optimal preference for an enhancer – TATAA configuration. It has also been unaddressed whether Tax has a transcriptional activity after the formation of an initiation complex at the TATAA-box. In mammalian cells, the artificial recruitment of TBP sufficiently activates transcription from some promoters [21-24]. It is understood that the structure of core promoter is one important determinant for this activation [23]. On the other hand, DNA-tethered TBP can also work synergistically with selective natural activators such as human immunodeficiency virus type 1 (HIV-1) Tat protein [21-23] and cytomegalovirus IE2 protein [25]. In this regard, it is not known whether TBP recruitment suffices for activation of HTLV-I minimal promoter. Nor is it clear whether Tax can cooperate with promoter-tethered TBP. Here, we have constructed a series of chimeric enhancer-TATAA reporters to analyze the functional roles of these transcription elements in Tax-mediated activation. We observed that Tax activates the HTLV-I 21-bp repeats more potently than other enhancer elements. Analysis of ten mutants of Tax revealed that Tax utilizes different domains to target different cellular factors. We also found that multiple bZIP transcription factors including the newly-identified LZIP are involved in Tax activation of HTLV-I LTR. Finally, two other salient findings are that optimal Tax-responsiveness is specified by the HTLV-I-specific TATAA element, and that Tax synergizes with artificially recruited, DNA-tethered, TBP in a phase of transcription after the assembly of an initiation complex at the promoter. Results Specific preference by Tax for only one enhancer element Tax can activate transcription through 21-bp repeats, CRE, κB site or SRE [4-9]. However, a direct head-to-head comparison between the relative preferences of Tax for each of these elements is complicated by the context of additional DNA elements in the various promoters tested to date (i.e. the HTLV-I LTR versus the HIV-1 LTR versus the interleukin-2 promoter). To directly compare enhancer motifs, they should be placed in identical TATAA-context and tested in identical experimental settings. Towards this end, we constructed a series of six reporters to dissect the ordered preference of Tax for various enhancers. Each reporter contains two copies of enhancer motifs (21-bp repeats, CRE, AP1, Sp1, κB or SRE) and a minimal HTLV-I TATAA promoter (Fig. 1A). Because all reporters have the same HTLV-1 minimal promoter and are otherwise devoid of any known enhancer elements, side-by-side comparisons would reflect directly the contribution of the variously added cis-enhancer. We observed that the κB- and CRE- motifs had the highest basal activities in HeLa cells in the absence of Tax (Fig. 1B, lanes 3, 4, 9 and 10; and Fig. 1C, columns 3 and 6 compared to column 1). Of significant interest, in stark contrast to the cellular CRE elements, the reiterated HTLV-I 21-bp repeats (normally considered as viral CRE elements) and the SRE exerted little or no basal activity (Fig. 1B, lanes 1, 2, 11 and 12; and Fig. 1C, lanes 2 and 7 compared to lane 1). The AP1 and Sp1 sites were moderately active (Fig. 1B, lanes 5–8 and Fig. 1C, lanes 4 and 5). Hence for basal expression in the context of the HTLV-I TATAA promoter, κB, CRE > AP1, Sp1 >> 21 bp, SRE. Figure 1 Relative responsiveness of enhancers to Tax in HeLa cells. (A) CAT reporter plasmid. Each plasmid contains two copies of enhancer elements (21-bp repeats, CRE, AP1, Sp1, κB and SRE) and one copy of HTLV-I minimal promoter (HTLV TATAA). The enhancer (Enh.) sequences are shown in green. (B) A representative example of CAT assay. Increasing amounts (5 to 10 μg) of p21-HTLV-CAT (lanes 1 and 2), pCRE-HTLV-CAT (lanes 3 and 4), pAP1-HTLV-CAT (lanes 5 and 6), pSP1-HTLV-CAT (lanes 7 and 8), pKB-HTLV-CAT (lanes 9 and 10) and pSRE-HTLV-CAT (lanes 11 and 12) were transfected into HeLa cells. CAT assays were performed 48 h after transfection. AcCM: acetyl chloramphenicol. CM: chloramphenicol. (C) Basal transcriptional activities of enhancer elements. Five microgram of plasmids containing the HTLV TATAA alone (pHTLV-CAT; column 1) or the indicated enhancer elements (columns 2 to 7) were transfected into HeLa cells and the relative CAT activities were compared. CAT activity from pKB-HTLV-CAT-transfected HeLa cells was taken as 100% (lane 6). (D) Tax-dependent transcriptional activities of enhancer elements. The same plasmids as in C plus 1 μg of Tax-expressing plasmid pIEX were co-transfected into HeLa cells and the CAT assays were performed. Fold activation in the presence of Tax versus in the absence of Tax was calculated and compared. All CAT results are representative of three independent experiments. When the reporters were tested in the presence of Tax, a different pattern emerged. Transcription from the 21-bp repeats was stimulated approximately 70-fold (Fig. 1D, lane 2 compared to lane 1) while that from the Sp1 site, not prototypically known to be responsive to Tax, was not activated significantly over the activity of the HTLV-I minimal promoter (Fig. 1D, lane 5 compared to lane 1). All other responses to Tax were markedly weaker than that seen from the 21-bp repeats. Hence, for all practical purposes, only a duplicated 21-bp repeat in the context of isolated placement upstream of an authentic HTLV-I minimal TATAA box could be regarded as significantly Tax-responsive in HeLa cells. We repeated the experiments in Jurkat T lymphocytes and obtained similar results (Fig. 2). Thus, while the κB and CRE enhancers displayed the highest activities in the absence of Tax (Fig. 2B, lanes 3 and 6 compared to lanes 5, 4, 2, 1, and 7), only the 21-bp repeats were highly responsive to Tax (Fig. 2A, lanes 1 and 2; Fig. 2C, lane 2). Our results from HeLa and Jurkat cells consistently support the preferential activation of the 21-bp repeats by Tax. Figure 2 Relative responsiveness of enhancers to Tax in JPX9 cells. (A) A representative example of CAT assay. Tax-expressing plasmid pIEX (1 μg) and increasing amounts (0.5 to 1 μg) of p21-HTLV-CAT (lanes 1 and 2), pCRE-HTLV-CAT (lanes 3 and 4), pAP1-HTLV-CAT (lanes 5 and 6), pSP1-HTLV-CAT (lanes 7 and 8), pKB-HTLV-CAT (lanes 9 and 10) and pSRE-HTLV-CAT (lanes 11 and 12) were transfected into Jurkat cells. CAT assays were performed 48 h after transfection. AcCM: acetyl chloramphenicol. CM: chloramphenicol. (B) Basal transcriptional activities of enhancer elements. One microgram of plasmids containing the HTLV TATAA alone (pHTLV-CAT; column 1) or the indicated enhancer elements (columns 2 to 7) were transfected into Jurkat cells and the relative CAT activities were compared. CAT activity from pKB-HTLV-CAT-transfected Jurkat cells was taken as 100% (lane 6). (D) Tax-dependent transcriptional activities of enhancer elements. The same plasmids as in C plus 1 μg of Tax-expressing plasmid pIEX were co-transfected into Jurkat cells and the CAT assays were performed. Fold activation in the presence of Tax versus in the absence of Tax was calculated and compared. All CAT results are representative of three independent experiments. Multiple activation surfaces are configured in Tax In Fig. 1D, the 21-bp repeats were activated by Tax >75 fold, while κB and SRE motifs were activated five and three fold, respectively. The low activation of the latter motifs, although comparatively less significant than that from the 21 bp elements, was real and reproducible. To further understand how Tax works, we wondered whether the different magnitudes of activation were due to quantitative or qualitative differences in protein-protein interaction. To address this question, we examined the separate responses of the three motifs to a battery of Tax mutants. Previously we had characterized 47 mutations in Tax that affect transcriptional activity [26]. Here we selected 10 of these Tax mutants to shed light on the discrete surfaces used by Tax to mediate effects on 21-bp repeats, κB and SRE. All mutants were expressed to comparable levels in HeLa cells (data not shown). Their relative activities on 21-bp repeats, κB and SRE were assessed (Fig. 3). Figure 3 Differential activities of Tax mutants on 21-bp repeats (A), κB (B), and SRE (C) motifs. One microgram of plasmid expressing the indicated Tax mutants plus 5 μg of p21-HTLV-CAT, pKB-HTLV-CAT or pSRE-HTLV-CAT was individually transfected into HeLa cells. CAT activity from wild type Tax-transfected cells (lane 1) was taken as 100%. Based on percentage of activation relative to wild type Tax, we saw three patterns of mutant activity for 21 bp, κB and SRE (Fig. 3). Hence, the activation domain mutant Tax L320G [10] and the zinc finger mutant Tax H52Q [26] were defective in activating either 21-bp repeats or SRE, but were fully competent for κB (Fig. 3, lanes 4 and 10). By contrast, the N-terminal mutant Tax Δ3–6 and the point mutant Tax S258A activated 21-bp repeats and SRE well, but did not activate κB (Fig. 3, lanes 2 and 7). Additionally, mutants Tax Δ94–114, Tax S150A and Tax Δ337–353 were active on all three motifs (Fig. 3, lanes 5, 6 and 11), while neither Tax Δ2–58, Tax Δ 284–353 nor Tax L296G (Fig. 3, lanes 3, 8 and 9) activated any of the motifs. These non-identical patterns suggest that Tax may use different contact surfaces to target factors docked at the 21-bp repeats, κB or SRE. We note some similarity in the Tax mutant activity profiles for the 21-bp repeats and SRE suggesting that overlapping surfaces may be utilized. Amongst bZIP factors, CREB is specifically preferred by Tax Tax activates the HTLV-I LTR through the viral 21-bp repeats [7-9]. When compared to κB and SRE, the activation of 21-bp repeats by Tax is particularly effective (Fig. 1 and Fig. 2) and, based on mutant profiles (Fig. 3A), relies upon unique structural surfaces. Previously, it has been proposed that bZIP cellular transcription factors including CREB [9,27,28], ATF4 [29,30] and c-Jun [31] play roles in Tax activation of 21-bp repeats. However, the relative contribution of these bZIP factors has not been compared directly in the same experimental setting. Furthermore, it remains undetermined whether additional newly identified bZIP proteins may also participate in Tax activation of 21-bp repeats. We next used dominant-negative proteins to assess the contributory roles of different bZIP transcription factors on Tax-dependent activation. We employed several well-documented dominant-negative inhibitors of CREB and Jun proteins including KCREB [32], A-CREB [33], A-Fos [34] and TAM67 [35]. In addition, we constructed dominant-negative versions of ATF4 and LZIP [36] using the strategies suggested by Vinson et al. [37]. The dominant-inhibitory activities of the latter two proteins A-ATF4 and A-LZIP were verified using electrophoretic mobility shift assay and CAT reporter assay (data not shown). We interrogated these dominant negative bZIP proteins for inhibition of Tax activation of HTLV-I LTR (Fig. 4A). All, KCREB, A-CREB, A-ATF4 and TAM67, suppressed Tax activation in a dose-dependent manner (Fig. 4A, lanes 3–10 compared to lane 2). However, different dominant negative inhibitors constructed to the same protein using different strategies might have different potencies. For example, KCREB contains a mutation of a single amino acid in the CREB DNA-binding domain [32], whereas A-CREB was constructed by fusing a designed acidic amphipathic extension onto the N terminus of the CREB leucine zipper region [33]. Differential inhibitory effects of KCREB and A-CREB were observed (Fig. 4A, lanes 3–6). In light of this, we quantitated and compared the inhibitory activities of dominant negative proteins all constructed using the same strategy (Fig. 4B). Since NFκB is not involved in Tax activation of HTLV-I LTR, we included a dominant negative form of IKKβ, IKKβ DN, as a neutral control (Fig. 4B, group 7). When we compared four dominant negative bZIP proteins, A-CREB, A-LZIP, A-Fos and A-ATF4, constructed using the identical molecular strategy, we observed the most dramatic suppression of Tax activation of HTLV-I LTR with A-CREB (Fig. 4B, group 3, red column). The second most significant reduction in activity was seen with A-LZIP [36] (Fig. 4B, group 6, red column). Thus, although several bZIP proteins can redundantly serve to mediate Tax-activation of the LTR, a clear preference for CREB is revealed by our assay. Figure 4 Specific preference for CREB by Tax. (A) An example of CAT assay. HeLa cells were transfected with pU3RCAT alone (lane 1), pU3RCAT plus Tax expression plasmid pIEX (lane 2) or pU3RCAT plus pIEX plus increasing amounts (5 to 10 μg) of plasmids expressing the indicated dominant-negative proteins (lanes 3–10). D-Threo-[dichloroacetyl-1-14C]-chloramphenicol was as used as substrate in the CAT assay. (B) Influence of dominant-negative proteins on Tax activation. The cells received pU3RCAT (red) or pKB-SV40-CAT (blue) only (group 1), pU3RCAT/pKB-SV40-CAT plus Tax-expressing plasmid pIEX (group 2) or pU3RCAT/pKB-SV40-CAT plus pIEX plus plasmids expressing the indicated dominant-negative proteins. The empty vector was used to normalize the amount of plasmids given to each group of cells. DN: dominant-negative. To verify the specificity of dominant negative effects, we also tested the activities of dominant negative proteins on an NFκB-dependent reporter (Fig. 4B, blue columns). Noticeably, none of the dominant negative bZIP proteins had an effect on Tax activation of NFκB (Fig. 4B, groups 3–6 compared to group 2, blue columns). In contrast, the expression of IKKβ DN led to more than 50% suppression of NFκB activity (Fig. 4B, group 7, blue column). These results ruled out the possibility that A-CREB, A-ATF4, A-Fos and A-LZIP might non-specifically inhibit transcription. Functional significance of the HTLV-I TATAA element to transcriptional activation by Tax In the course of our analyses, we noted that Tax can activate the HTLV-I minimal TATAA-promoter without any known enhancer element by approximately 4-fold (Fig. 1D, lane 1). This responsiveness of the HTLV-I minimal promoter is compatible with the concept that the core promoter can also be an important determinant of transcriptional specificity [2]. We next asked whether all TATAA-elements are recognized by Tax in the same way for purposes of activated transcription. Hence, we constructed reporter plasmids that contain two 21-bp repeats and a minimal TATAA promoter from HTLV-I, HIV-1 or SV40 (Fig. 5A). Since the TATAA promoters were all placed within the same context, we consider this a valid comparison of their relative responsiveness to Tax activation. Figure 5 Tax preferentially activates the HTLV-I minimal TATAA promoter. (A) CAT reporter plasmid. Each plasmid contains two 21-bp repeats and one copy of minimal promoter (TATAA) from HTLV-I, HIV-1 and SV40. The minimal promoter sequences are shown in blue. (B) A representative example of CAT assay. The cells received 0, 0.5 and 1 μg of Tax-expressing plasmid pIEX and 5 μg of the indicated CAT reporter constructs (p21-HTLV-CAT, p21-HIV-CAT and p21-SV40-CAT). (C, D) Basal and Tax-induced transcriptional activities. HeLa cells were co-transfected with 5 μg of the indicated CAT reporter plasmids (p21-HTLV-CAT, p21-HIV-CAT and p21-SV40-CAT) plus 0.5 μg of pCMV empty vector (w/o Tax) or pIEX (w/ Tax). Basal CAT activity from p21-SV40-CAT-transfected cells was taken as 100% (C, column 3). While the basal activities of HIV-1 and SV40 minimal promoters were measurably greater than that from HTLV-I (Fig. 5C), replacement of the HTLV-I TATAA with the counterpart element from either HIV-1 or SV40 led to a significant reduction in Tax responsiveness (Fig. 5B, lanes 4–9; and Fig. 5D). To further verify the importance of the TATAA-promoter, we asked the same question using a different approach. Above, Tax was recruited presumably to the downstream TATAA-box via factors bound to the HTLV-1 21bp repeats (see Fig. 5A). We next investigated whether the same conclusion could be established if a Gal4 DNA-binding domain-Tax fusion protein (Gal4-Tax) was delivered to downstream TATAA element by tethering to upstream Gal4-binding sites (see Fig. 6A for reporter schematic). For this assay, we tested the HTLV-I, the HIV-1, and the E1b TATAA-elements. Consistent with the results from the 21 bp-TATAA experiments (Fig. 5), Gal4-Tax activated most strongly the HTLV-I TATAA element (Fig. 6B, lane 9 and Fig. 6D, group 3) and was minimally potent for the adenoviral E1b promoter (Fig. 6B, lane 7 and Fig. 6D, group 1). As a control for Gal4-Tax, we checked in parallel the activity of the artificial Gal4-VP16 activator. In contrast with Gal4-Tax, Gal4-VP16 showed no preference for the various TATAA elements (Fig. 6B, lanes 4–6 and Fig. 6D). Thus, two lines of evidence here support that the HTLV-I TATAA promoter is an additional Tax-specific responsive element. Figure 6 DNA-tethered Tax is specifically active on the HTLV-I minimal promoter. (A) CAT reporter plasmid. Each plasmid contains five tandem copies of Gal4-binding sites and one copy of minimal promoter (TATAA) from adenovirus E1b, HIV-1 and HTLV-I. The minimal promoter sequences are shown in blue. (B) A representative example of CAT assay. The cells were co-transfected with 2 μg of a Gal4DB plasmid (pM vector alone for lanes 1–3, pGal4-VP16 for lanes 4–6, and pGal4-Tax for lanes 7–9) and 5 μg of a CAT reporter construct (pG5-E1B-CAT for lanes 1, 4 and 7; pG5-HIV-CAT for lanes 2, 5 and 8; and pG5-HTLV-CAT for lanes 3, 6 and 9). (C, D) Basal and activated transcriptional activities. HeLa cells were co-transfected with 5 μg of the indicated CAT reporter plasmids (pG5-E1B-CAT, pG5-HIV-CAT and pG5-HTLV-CAT) plus 2 μg of pM empty vector (C), pGal4-VP16 (D, blue) or pGal4-Tax (D, yellow). Basal CAT activity from pG5-HIV-CAT-transfected cells was taken as 100% (C, column 2). Evidence for Tax activity after assembly of an initiation complex Artificial recruitment of TBP to some higher eukaryotic promoters bypasses transcriptional activation by a DNA-tethered activator [21-24]. When observed at such promoters, this finding is evident that those activators act mechanistically to enhance TBP recruitment to the TATAA box. For general transcriptional activation, additional events subsequent to TBP recruitment are also known to be functionally critical [21-23,25]. To date, it remains unclear whether Tax works transcriptionally through a mechanism solely to recruit TBP or whether there are additional mechanistic implications after TBP is recruited to the TATAA-element. To investigate the mechanism(s) of Tax function with respect to TBP recruitment, we constructed a series of reporter plasmids (Fig. 7A) with two copies of 21-bp repeat, five copies of Gal4-binding sites and a minimal TATAA sequence from one of four viral promoters (HTLV-I, HIV-1, SV40 and E1b). We artificially delivered TBP to each promoter by provision of Gal4-TBP, and we asked whether Tax has an additional transcriptional effect which is independent of TBP-recruitment to the TATAA-element. If Tax were to serve only for TBP-recruitment, then when TBP is tethered to the TATAA via Gal4-TBP one should expect to see no transcriptional enhancement from Tax. Provocatively, for both the HTLV-I and HIV-1 TATAA elements, Tax stimulated reporter expression greatly over that already achieved with Gal4-TBP (Fig. 7, groups 1 and 2). Consistent with above findings, the SV40 and E1b TATAA elements appear to be transcriptionally rate-limited by TBP recruitment, and Tax has minimal activity on these promoters. However, the findings from the HTLV-I and the HIV-1 reporters provide evidence that more than simply accelerating TBP recruitment Tax can serve transcriptional function(s) subsequent to TBP (TFIID) assembly at the core promoter. This is the first time that Tax has been shown to have a role subsequent to transcriptional initiation complex formation at the promoter. Figure 7 Tax further activates a promoter with DNA-tethered TBP. (A) CAT reporter plasmid. Each plasmid contains two copies of 21-bp repeat, five copies of Gal4-binding sites and one copy of minimal promoter (TATAA) from adenovirus HTLV-I, HIV-1, SV40 and adenovirus E1b. (B) CAT assay. HeLa cells were co-transfected with 5 μg of the indicated CAT reporter plasmids (p21-G5-HTLV-CAT, p21-G5-HIV-CAT, p21-G5-SV40-CAT and p21-G5-E1B-CAT) and 2 μg of pGal4-TBP (yellow) or 2 μg of pIEX (Tax; pink) or 2 μg of pGal4-TBP plus 2 μg of pIEX (Gal4-TBP + Tax; blue). Basal CAT activity from cells transfected with pGal4-TBP plus p21-G5-E1B-CAT was taken as 100% (group 4, yellow). Discussion Here, we have delineated functional requirements for both the TATAA promoter and the 21-bp enhancer elements in HTLV-I Tax mediated activation of the viral LTR. To date Tax has been considered solely to initiate transcription. Our study shows for the first time that Tax has a transcriptional role after assembly of an initiation complex at the promoter. Preferential requirements for 21-bp repeats, CREB, and the HTLV-I TATAA box HTLV-I is etiologically associated with adult T-cell leukemia [38,39]. Expression of Tax leads to immortalization of T lymphocytes [40-42] and transformation of rat fibroblasts [43,44]. Tax is a transcriptional activator that can interact pleiotropically with several different enhancers. In addition to the HTLV-I 21-bp repeats, κB and SRE elements can also mediate Tax activation [4-6]. Amongst these three enhancers, it is clear that the viral 21-bp repeats are the most highly responsive to Tax-activation (Fig. 1D). However, data elsewhere have raised questions as to the identity of the 21-bp binding bZIP factor which is best used to mediate Tax activation [30]. In direct comparisons, we have used matched A-CREB, A-Jun, A-ATF4 and A-LZIP dominant negative mutants to ask which bZIP factor is most contributory to Tax activation. In our cell system, a novel bZIP factor called LZIP [36] can apparently participate in LTR transcription; however, for Tax activation CREB is preferred over ATF4 or c-Jun (Fig. 4). Beyond the requirement for the 21-bp enhancer, our experiments revealed that the HTLV-I TATAA is also specifically preferred by Tax (Fig. 5 and Fig. 6). This finding is consistent with the general notion that core promoters can contribute specificity to transcriptional regulation [2]. Indeed, core promoter preference by other cellular and viral activators such as Sp1, VP16 and Tat have been documented previously [45-47]. However, the reasons underlying core promoter preferences are poorly understood. TAFs have been suggested to be responsible for the core promoter selectivity of some activators [48-50]. In this vein, the interaction of Tax with TBP [11] and TBP-associated factors such as TAFII28 [51] might provide mechanistic explanations. Roles of Tax subsequent to TBP recruitment A provocative notion which emerges from our study is that Tax can further activate a promoter at which TBP has already been artificially tethered (Fig. 7). Experiments in yeast and mammalian cells indicate that many genes can be activated through artificial recruitment of TBP and other components of the basal transcription machinery to their promoters [52,53]. In yeast, artificial recruitment of TBP bypasses the effect of DNA-tethered activators whereas the activators fail to activate transcription when physically fused to components of the basal transcription machinery [54]. This and other lines of evidence support the notion that activator-dependent recruitment of TBP and basal transcription machinery is a major mechanism for transcriptional activation in yeast cells [54,55]. In contrast, artificial recruitment of TBP to mammalian promoters has not yet been extensively studied. Among the few promoters examined, some such as the ones from E1b and thymidine kinase genes can be fully activated by artificially recruited TBP, while others such as HIV-1 and c-fos promoters are stimulated weakly [21-25]. On the other hand, some activators such as VP16, E1A, Tat, E2F1 and IE2 work synergistically with artificially recruited TBP, while others such as Sp1 cannot further enhance the activity of DNA-tethered TBP [21,22]. Thus, artificial recruitment of TBP might insufficiently activate transcription in mammalian cells and different activators might function at different steps with respect to TBP recruitment. Our results indicate that DNA-bound TBP can activate HTLV-I LTR only weakly, but its activity is further enhanced by Tax (Fig. 6). While such experimental results do not exclude that under physiological circumstances the primary function of Tax may be to enhance initiation complex formation (i.e. TBP-recruitment), they do indicate that Tax has an additional transcriptional activity that extends to phases after transcriptional initiation. Currently, we do not know whether this is at the step of promoter clearance, transcriptional elongation, or some other processes. However, we do believe that Tax should be added to the list of mammalian activators that can function at steps subsequent to TBP recruitment [21-25]. All the transcriptional assays in the present study were based on transiently transfected reporters. We noted that transiently transfected and stably integrated promoters might behave differently [24,56]. Obviously, chromatin structure and copy numbers can account for significant differences [56,57]. Future experiments are required to verify whether the observations established here also hold for stably integrated HTLV-I LTRs. Methods Plasmids Chloramphenicol acetyltransferase (CAT) reporter plasmid pG5CAT was from Clontech. CAT plasmid pU3RCAT containing the HTLV-I LTR has been previously described [13]. Other CAT plasmids were derived from pCAT-basic (Promega). For each construct, one copy of a minimal promoter and two copies of an enhancer were chemically synthesized and cloned into pCAT-basic. For example, pCRE-HTLV-CAT contains two copies of canonical CRE motif plus one copy of HTLV-I minimal promoter (Fig. 1A). Five copies of Gal4-binding sites as in pG5CAT were also inserted in some reporters. All constructs have the same spacing between the TATAA box and the CAT open reading frame (44 bp) or between the enhancer and the TATAA box (23 bp). Sequences of canonical CRE, Sp1, AP1 and κB motifs in the reporter plasmids have been described [36,58,59]. HTLV-I 21-bp repeats and serum response element (SRE) in the plasmids were derived from the following synthetic oligonucleotides: 21-bp repeats, 5'-AGCTTAGGCC CTGACGTGTCCCCCTGGATCCTAGGCCCTGACGTGTCCCCCTA-3' and 5'-AGCTTAG GGGGACACGTCAGGGCCTAGGATCCAGGGGGACACGTCAGGGCCTA-3'; SRE, 5'-AGCTACCATATTAGGATCCATATTAGGT-3' and 5'-AGCTACCTAATATGGATCCTAATATGGT-3'. Sequences of the minimal promoter elements from HTLV-I, HIV-1, SV40 and adenoviral E1b have been described [60]. The SV40 early promoter naturally used for expression of the viral T/t antigens was used. Expression plasmids for wild type and mutant Tax have been described elsewhere [26,61]. pIEX is a Tax expression vector driven by cytomegalovirus IE promoter. Tax mutants are indicated by the amino acid to be changed, the position of the residue, and the replacement amino acid (e.g. Tax S150A). Amino acids that were removed in mutants are indicated as in Tax Δ3–6. Expression vector pM for Gal4 DNA binding domain (Gal4DB; amino acids 1–147) was from Clontech. Tax, human TBP and the activation domain of VP16 fused to Gal4DB were designated Gal4-Tax, Gal4-TBP and Gal4-VP16, respectively. Expression plasmids for Gal4-Tax and Gal4-TBP have been described [10,21]. Expression plasmid for Gal4-VP16 was from Clontech. Expression plasmid pRSV-KCREB for the dominant-negative CREB protein KCREB [32] was kindly provided by Dr. Richard Goodman. Expression plasmids pCMV-ACREB and pCMV-AFOS for dominant-negative CREB and AP1 proteins A-CREB [33] and A-Fos [34] were gifts from Dr. Charles Vinson. Expression plasmid pCMV-TAM67 for dominant-negative c-Jun protein TAM67 [35] was from Dr. Michael Birrer. Expression plasmids pCMV-AATF4 and pCMV-ALZIP for dominant-negative ATF4 and LZIP proteins A-ATF4 and A-LZIP were derived from pCMV500 provided by Dr. Charles Vinson [33,37]. A-ATF4 contains 304–352 amino acids of human ATF4 and A-LZIP contains 175–223 amino acids of human LZIP. A-ATF4 and A-LZIP can specifically and dominantly inhibit the CRE-binding and CRE-activating activities of ATF4 and LZIP, respectively, in electrophoretic mobility shift assay and CAT reporter assay (data not shown). Expression plasmid for dominant-negative IKKβ (IKKβ DN) was a gift from Dr. Michael Karin [62]. Reporter assay HeLa cells were grown in Dulbecco's modified Eagle's medium supplemented with fetal calf serum and antibiotics, seeded at 5 × 105 cells/well into six-well culture plates and transfected using calcium phosphate method as described [13]. Jurkat cells were cultured in RPMI 1640 medium and transfected by FUGENE 6 reagents (Roche). CAT activity was assayed as previously described [63]. Briefly, transfected cells were harvested and lysed by freezing and thawing. Protein concentration of clarified lysates was determined by Bradford reagent (Bio-Rad). Equal amounts of lysates were mixed with 14C-labeled chloramphenicol (Amersham) and acetyl coenzyme A (Calbiochem) for CAT reaction. CAT activities were detected using thin-layer chromatography and quantified by phosphorimager (Molecular Dynamics). For transfection of cells, each well received the same dose of plasmids. The empty vector or pUC19 was added to compensate for the different amounts of plasmids when necessary. Competing interests None declared. Acknowledgements We thank E.W.M. Cheng for technical assistance, R.H. Goodman, C. Vinson, M.J. Birrer and M. Karin for plasmids, and C.M. Wong and M.L. Yeung for critical reading of manuscript. D.-Y. J. is a Leukemia and Lymphoma Society Scholar. 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10026 3808945 Chun ACS Zhou Y Wong CM Kung H Jeang KT Jin DY Coiled-coil motif as a structural basis for the interaction of HTLV type 1 Tax with cellular cofactors AIDS Res Hum Retrov 2000 16 1689 1694 10.1089/08892220050193155 Zandi E Rothwarf DM Delhase M Hayakawa M Karin M The IκB kinase complex (IKK) contains two kinase subunits, IKKα and IKKβ, necessaryfor IκB phosphorylation and NF-κB activation Cell 1997 91 243 252 9346241 10.1016/S0092-8674(00)80406-7 Chun ACS Jin DY Transcriptional regulation of mitotic checkpoint gene MAD1 by p53 J Biol Chem 2003 278 37439 37450 12876282 10.1074/jbc.M307185200

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020196Research ArticleCell BiologyDevelopmentImmunologyDrosophilaCellular Immune Response to Parasitization in Drosophila Requires the EBF Orthologue Collier Drosophila Immune Response to ParasitizationCrozatier Michèle 1 Ubeda Jean-Michel 2 Vincent Alain vincent@pop.cict.fr 1 Meister Marie M.Meister@ibmc.u-strasbg.fr 2 1Centre de Biologie du Développement, Centre National de la Recherche Scientifique and Université Paul SabatierToulouse, France2Institut de Biologie Moléculaire et CellulaireCentre National de la Recherche Scientifique, StrasbourgFrance8 2004 17 8 2004 17 8 2004 2 8 e1965 2 2004 22 4 2004 Copyright: © 2004 Crozatier et al.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. A Protein Required for Fruitflies to Dispatch Wasp Parasites Drosophila immune response involves three types of hemocytes (‘blood cells’). One cell type, the lamellocyte, is induced to differentiate only under particular conditions, such as parasitization by wasps. Here, we have investigated the mechanisms underlying the specification of lamellocytes. We first show that collier (col), the Drosophila orthologue of the vertebrate gene encoding early B-cell factor (EBF), is expressed very early during ontogeny of the lymph gland, the larval hematopoietic organ. In this organ, Col expression prefigures a specific posterior region recently proposed to act as a signalling centre, the posterior signalling centre (PSC). The complete lack of lamellocytes in parasitized col mutant larvae revealed the critical requirement for Col activity in specification of this cell type. In wild-type larvae, Col expression remains restricted to the PSC following parasitization, despite the massive production of lamellocytes. We therefore propose that Col endows PSC cells with the capacity to relay an instructive signal that orients hematopoietic precursors towards the lamellocyte fate in response to parasitization. Considered together with the role of EBF in lymphopoiesis, these findings suggest new parallels in cellular immunity between Drosophila and vertebrates. Further investigations on Col/EBF expression and function in other phyla should provide fresh insight into the evolutionary origin of lymphoid cells. The lamellocyte is induced to differentiate under conditions such as parasitization by wasps and is shown in this study to require collier, the orthologue of the vertebrate early B-cell factor ==== Body Introduction Hematopoiesis in Drosophila shares several features with the analogous process in vertebrates. A first population of embryonic hemocyte precursors (prohemocytes) is specified from the head mesoderm very early during embryogenesis. At the end of larval stages and the onset of metamorphosis, a second population of hemocytes is released from a specialised hematopoietic organ, the larval lymph gland (Rizki and Rizki 1984; Tepass et al. 1994; Campos-Ortega and Hartenstein 1997; Evans et al. 2003; Holz et al. 2003). Both populations give rise to plasmatocytes, which are dedicated phagocytes, and crystal cells, which are responsible for melanisation of pathogens. Lymph glands contain precursors of a third type of hemocyte that is not generated in embryos, the lamellocyte. Lamellocytes are large, adhesive cells devoted to the encapsulation of foreign bodies too large to be phagocytosed; these cells differentiate only in response to specific conditions, such as parasitization of larvae by Hymenoptera (Lanot et al. 2001; Sorrentino et al. 2002). Striking similarities with vertebrate hematopoiesis were revealed when it was shown that Serpent (Srp), a GATA factor, and Lozenge (Lz), a transcription factor related to Runx1/AML1, are required for the development of hemocytes and of crystal cells, respectively (Rehorn et al. 1996; Lebestky et al. 2000; Orkin 2000). However, except for the observation that gain-of-function mutations in the Janus kinase Hopscotch and in the Toll receptor lead to constitutive production of lamellocytes (Harrison et al. 1995; Luo et al. 1995; Qiu et al. 1998), the mechanisms and factors underlying the specification of this cell type remain unknown (Evans et al. 2003; Meister 2004). During our search for genes involved in specification of lamellocytes, we observed that collier (col) is expressed in the lymph glands at the end of embryogenesis (Kambris et al. 2002). The gene col encodes the Drosophila orthologue of mammalian early B-cell factor (EBF) (Hagman et al. 1993; Crozatier et al. 1996), a key factor controlling B-cell lymphopoiesis in mice (Lin and Grosschedl 1995; Maier and Hagman 2002). We show here that Col activity is required for specification of the lamellocyte lineage in Drosophila. On the basis of Col expression and col mutant phenotypes, we propose that this factor confers an instructive function on a discrete subpopulation of cells in the Drosophila definitive hematopoietic organ. Results/Discussion Col Expression Identifies Lymph Gland Precursors in Early Embryos We first observed that Col is expressed in Drosophila lymph glands at the end of embryogenesis (Figure 1). In the absence of a specific molecular marker, the embryonic anlage of lymph glands has been mapped to the thoracic lateral mesoderm by lineage analysis of transplanted cells (Holz et al. 2003). By histochemical staining, we observed that Col is expressed in two discrete clusters of cells in the dorsal mesoderm of thoracic segments T2 and T3, starting at the germ-band extension, when lymph gland hemocyte precursors become specified (stage 11; Figure 1A) (Holz et al. 2003). These clusters of Col-expressing cells grow closer during germ-band retraction before coalescing to form the paired lobes of the lymph glands (early stage 13; Figure 1B and 1C). Double staining for Col and Odd-skipped, a lymph gland marker expressed from that stage onward (Ward and Skeath 2000), confirmed that Col-expressing cells are lymph gland precursors (Figure 1E). Thereafter, only three to five cells located at the posterior tip of each lobe maintain high levels of Col expression, although low levels are still detected in the other cells of the lymph glands and in some pericardial cells (Figure 1D, 1F, and 1G). Col expression thus identifies a few cells of the thoracic dorsal mesoderm as the lymph gland primordium and distinguishes a specific posterior region of this hematopoietic organ (Figure 1H). The embryonic hematopoietic primordium has been defined as the cephalic domain of Srp expression at the blastoderm stage (Rehorn et al. 1996; Lebestky et al. 2000). Srp is not detected, however, in lymph gland precursors prior to stage 12 (Berkeley Drosophila Genome Project gene expression report [http://www.fruitfly.org/cgi-bin/ex/insitu.pl]; Lebestky et al. 2003). Consistent with this result, larval hematopoietic progenitors expressing Col are observed in srp6G (an amorphic allele; Rehorn et al. 1996) mutant embryos (Figure 1I), indicating that the specification of the embryonic and larval lymph gland progenitors may involve different processes. Figure 1 Col Expression during Lymph Gland Ontogeny (A) Col expression in lymph gland precursors is first observed in two separate clusters of cells (black arrows) in the dorsal-most mesoderm of thoracic segments T2 and T3 at stage 11 (stages according to Campos-Ortega and Hartenstein [1997]). Col expression in the head region is ectodermal (parasegment 0) and related to its function in head segmentation (Crozatier et al. 1999). (B and C) The clusters of Col-expressing cells get closer between stage 12 and early stage 13 (B) before coalescing (C). (D and E) Col expression becomes progressively restricted to the posterior-most cells of the forming lymph glands (arrowhead) during stage 14, as shown by the partial overlap between Odd-skipped (Odd) and Col expression. (F and G) Enlarged view of lymph glands after completion of embryogenesis, stage 16. Col expression marks the prospective PSC (Lebestky et al. 2003) in a dorsal-posterior position (arrowheads). (H) Schematic representation of Col expression in the lymph glands and pericardial cells in stage 16 embryos. (I) A srp6G mutant embryo arrested at stage 13. Col is expressed in the presumptive lymph gland primordium (black arrow), although it is not possible to distinguish between high and low levels of expression. All embryos are oriented anterior to the left. (A–C), (G), and (I) are lateral views; (D–F) are dorsal views. (B), (C), and (E–G) are higher magnifications of the dorsal thoracic region. White arrows in (A) and (I) indicate Col expression in a developing dorsal muscle (Crozatier and Vincent 1999). Lamellocyte Differentiation in Response to Parasitization Requires Col Activity Expression of Col in the embryonic lymph gland prompted us to investigate its possible function during larval hematopoiesis. Loss-of-function mutations of col (e.g., col1) are lethal at the late embryonic stage (Crozatier et al. 1999), but lymph glands form normally, indicating that Col activity is not required for formation of the organ per se. Rescue of the embryonic lethality by expressing the col cDNA under the control of a truncated col promoter that is active in the head ectoderm but not in the lymph glands (Crozatier and Vincent 1999) thus allowed us to analyse hematopoiesis in col1 larvae. The presence of plasmatocytes and crystal cells in the circulation of these mutants indicated that col is not required for specification of either of these lineages (Table 1). We then tested the competence of col1 larvae to respond to wasp (Leptopilina boulardi) parasitization by producing lamellocytes. This dedicated cellular response is maximal in wild-type (wt) larvae 48 h after wasp egg-laying (Figure 2A and 2B) (Lanot et al. 2001). No circulating lamellocytes were detected in the hemolymph of parasitized col1 larvae; as a consequence, the wasp eggs were not encapsulated and they developed into parasitic larvae (Figure 2C). That this phenotype completely lacked lamellocytes was confirmed by using a lamellocyte marker, misshapen-lacZ, provided by the enhancer trap line l(3)06949 (Braun et al. 1997). Whereas in wt larvae, numerous lacZ-positive cells could be seen adhering to and surrounding wasp eggs, no such cells were detected in col1 larvae (Figure 2D and 2E). To ascertain that the absence of lamellocytes was the consequence solely of the col mutation, we tested col1 in transheterozygous combinations with two other col loss-of-function alleles and over the deficiency Df(2R)AN293 (Crozatier and Vincent 1999). In no case did we observe lamellocyte differentiation (we tested 10–20 larvae for each genotype) in response to parasitization by L. boulardi, thereby confirming the critical requirement for Col activity in rendering hematopoietic precursors competent to differentiate into lamellocytes. Although gain-of-function mutations that lead to constitutive activation of either the Janus kinase or the Toll signalling pathways result in hematopoietic defects, including differentiation of lamellocytes in the absence of infestation (Harrison et al. 1995; Luo et al. 1995; Qiu et al. 1998), col1 is, to our knowledge, the first identified loss-of-function mutation that abolishes lamellocyte production upon parasitization. Figure 2 col Requirement for Lamellocyte Differentiation (A–C) 4′,6-diamidino-2-phenylindole (DAPI) staining of hemocytes from wt (A and B) and from col1 (C) third instar larvae. (A) Uninfected larva; (B) and (C) infected larvae. Plasmatocytes (inset in [A]) are always present, whereas lamellocytes (inset in [B]) are detected in the hemolymph of wt (B) but not col1 (C) larvae 48 h after infestation by L. boulardi. In col1 mutants, the wasp eggs are not encapsulated (white arrows) and develop into larvae (bottom right organism in [C]). (D–F) Lamellocytes expressing the P-lacZ marker l(3)06949 (Braun et al. 1997) surround the wasp eggs in wt larvae (D), are completely absent in infected col1 mutant larvae (E), and differentiate in the absence of wasp infection following enforced Col expression in hematopoietic cells (srpD-Gal4/UAS-col larvae) (F). (G) srpD-Gal4/UAS-col pupa showing the presence of melanotic tumors. Bars: 50 μm. Table 1 Circulating Hemocytes in Third Instar Larvae Values are expressed as mean (SD). Hemocyte types were counted as described in Duvic et al. (2002) aCrystal cells were counted in the three posterior-most segments bThe strong adhesive properties of lamellocytes preclude an accurate counting of individual cells cObserved in a fraction of the larvae Bal, balancer chromosome; ND, not determined Enforced Col Expression Triggers Lamellocyte Differentiation in the Absence of Immune Challenge We then asked whether forced expression of Col in hematopoietic cells could induce lamellocyte differentiation in the absence of infestation. Because the e33C-Gal4 line, which drives expression in lymph glands (Harrison et al. 1995) but also epidermis and some other tissues, was lethal in combination with UAS-col, we designed a new Gal4 driver. The driver srpD-Gal4 contains distal elements of the srp gene promoter and drives expression of a UAS reporter gene in prohemocytes and hemocytes (see below) (Waltzer et al. 2003), with a low level of expression in pericardial cells and the fat body (data not shown). Although embryonic-lethal at 25 °C, the srpD-Gal4/UAS-col combination was viable when embryos were allowed to develop to the second larval instar at 18 °C before shifting to 25 °C. Examination of hemolymph samples from late third instar larvae expressing Col under the control of the srpD-Gal4 driver revealed the presence, in a fraction of the larvae, of numerous lamellocytes identified on the basis of both cell morphology and expression of misshapen-lacZ (Figure 2F; Table 1). Around 5% of all larvae developed melanotic tumors (Figure 2G), which have been previously observed in other genetic contexts that lead to overproduction of lamellocytes (Hou and Perrimon 1997). This phenomenon is considered to be a consequence of an autoimmune reaction in which hemocytes encapsulate self-tissue (Sparrow 1978). Thus, we conclude that enforced col expression in hematopoietic cells can induce differentiation of lamellocytes in the absence of immune challenge. We also observed a concomitant drop in the number of circulating crystal cells (Table 1), consistent with the hypothesis that lamellocytes and larval crystal cells could differentiate from a common precursor (Evans et al. 2003). No production of lamellocytes was observed, however, when col expression was targeted to already specified crystal cells or plasmatocytes by using the lz-Gal4 (Lebestky et al. 2000) and hml-Gal4 drivers (Goto et al. 2003), respectively. This indicates that lamellocytes differentiate only when col expression is forced in yet-uncommitted progenitors. Col-Expressing Cells Play an Instructive Role At the end of larval stages, the lymph gland is composed of four to six paired lobes. The two anterior (primary) lobes that formed in the embryo (Figure 1) contain prohemocytes, plasmatocytes, and crystal cells, whereas the posterior (secondary) lobes, which form during the third larval instar, contain predominantly prohemocytes, suggesting that they correspond to a more immature stage of development (Shrestha and Gateff 1982; Lanot et al. 2001). Col expression in the anterior primary lobes was found to be restricted to a posterior cluster of about 30–40 posterior cells (Figure 3A–3C). Consistent with, on average, three to four cell divisions between embryo hatching and the third larval instar—as observed both in circulating hemocytes and imaginal tissues (Schubiger and Palka 1987; Qiu et al. 1998)—these cells are likely to represent the entire progeny of the three to five cells that strongly express Col in the late embryo (see Figure 1E and 1F). They remain clustered at the posterior end of the primary lobes throughout larval development. Col is expressed in a variable number of cells in secondary lobes (Figure 3A and 3C) but is never observed in circulating hemocytes. Despite the dramatic burst of lamellocyte production that occurs in lymph glands when larvae are parasitized (see Figure 2) (Lanot et al. 2001; Sorrentino et al. 2002), the number and posterior clustering of Col-expressing cells were unchanged (Figure 3D and 3E). This indicates that the small group of Col-expressing cells are not likely to be the direct precursors of lamellocytes, but rather that they play an instructive role in orienting hematopoietic precursors present in the lymph glands towards the lamellocyte lineage. Figure 3 Col Expression in Lymph Glands of Third Instar Larvae (A and B) Col is expressed in the primary lobes, in a posterior cluster of cells (arrow), and in a variable number of secondary lobes. Low expression is also detected in some pericardial cells (asterisks), the significance of which remains unknown. PI, propidium iodide. (C) Schematic representation of the lymph glands and Col expression in late third instar larvae. (D and E) Col expression 24 h (D) and 48 h (E) after wasp infection; despite strong cell proliferation, including in secondary lobes, Col expression remains unchanged (black arrow). (F–H) Overlap between Ser-lacZ (Bachmann and Knust 1998) and Col expression in PSC cells; note a few scattered Ser-expressing cells that do not stain for Col. Bars: 50 μm (A, B, D, and E) ; 10 μm (F–H). Col expression in a posterior cluster of cells of the primary lobes is reminiscent of that of Serrate (Ser), a Notch ligand (Lebestky et al. 2003). The Ser/Notch pathway has recently been shown to be essential for crystal cell development (Duvic et al. 2002; Lebestky et al. 2003). Analysis of clones of Ser mutant cells in the larval lymph glands further indicated that Ser-expressing cells are responsible for activation of Lz expression in surrounding cells and their commitment to a crystal cell fate (Lebestky et al. 2003). Together with the Ser expression pattern, this observation led the authors to propose that the posterior cluster of Ser-expressing cells could act as a signalling centre, which they termed the posterior signalling centre (PSC). Through double-labelling experiments, we confirmed the overlap between Col and Ser expression (as visualised by Ser-LacZ [Bachmann and Knust 1998]) in the posterior cells of the primary lobe (Figure 3F–3H). However, Ser, but not Col, is expressed in scattered cells throughout the primary lymph gland lobes in addition to the PSC (Figure 4) (Lebestky et al. 2003). Figure 4 PSC-Specific Gene Expression Is Dependent upon Col Activity PSC-specific expression of col, Ser-lacZ, and Ser (arrowhead in [A], [C], and [E]) is lost in col1 mutant larvae (B, D, and F); only Ser expression in scattered cells is maintained (arrow in [E] and [F]). Bar: 50 μm. PSC-Specific Gene Expression Is Dependent upon Col Activity Because Col expression and function suggested that the PSC was playing an instructive role in orienting other lymph gland cells towards the lamellocyte fate, we asked whether Col was necessary for the PSC to form properly. We looked at col and Ser expression in col1 mutant lymph glands, using in situ hybridisation for col because Col antibodies do not recognise the Col1 protein (Crozatier and Vincent 1999). In wt larvae, consistent with the results of immunostaining, col transcripts were restricted to the PSC (Figure 4A). In contrast, we could not detect col expression in col1 mutant lymph glands (Figure 4B). Furthermore, expression both of Ser-lacZ and Ser in the PSC (Figure 4C and 4E) was also abolished (Figure 4D and 4F), indicating that proper specification of PSC identity is dependent upon Col activity. Although Ser expression was lost from the PSC region, it was still observed in scattered cells in the primary lobe (Figure 4E and 4F, arrows), suggesting that Ser-lacZ expression reflected the presence of a PSC-specific transcriptional enhancer without reproducing the entire Ser expression pattern. Evidence for a Bipotential Crystal Cell/Lamellocyte Precursor Ser signalling through the Notch signalling pathway is critical for the specification of crystal cell precursors (Duvic et al. 2002; Lebestky et al. 2003). However, numerous crystal cells differentiate in col mutant lymph glands, including in secondary lobes, despite the loss of Ser expression in the PSC (see Figures 4E, 4F, 5A, and 5B). These data, together with the clonal analysis of Lebestky et al. (2003), lead us to conclude that crystal cell development is triggered by signalling from the scattered Ser-expressing lymph gland cells, rather than from the PSC itself. In contrast, no differentiating lamellocytes could be detected in col mutant lymph glands, even under conditions of wasp infestation that induced massive lamellocyte differentiation in wt glands (Figure 5C–5F), confirming the key role of the PSC in this process. Figure 5 Col-Expressing Cells Play an Instructive Role in Lamellocyte Production Expression of the crystal cell marker doxA3 (Waltzer et al. 2003) (A, B, and G); of the lamellocyte markers α-ps4 (M. Meister, unpublished data) (C–F and H) and L1 (Asha et al. 2003) (J); and of Col (I and J); in wt (A, C, and E), col loss-of-function mutant (B, D, and F), and srp-Gal4/UAS-col (G–J) larvae. In (E) and (F), larvae were taken 48 h after infestation. An increased number of doxA3-positive cells (B) parallels the absence of lamellocyte differentiation (F) in col1 mutant lymph glands. Conversely, lamellocyte differentiation and a reduced number of doxA3-positive cells are observed upon enforced Col expression (G and H). Double staining for Col and L1 shows that Col-expressing cells and differentiating lamellocytes do not overlap in the lymph gland. (I) shows ectopic Col expression compared to expression in the PSC (arrowhead; not visible in [J]). Antibody and in situ probes are indicated on each panel. In all panels, larvae are oriented with the head to the left: a single primary lobe is shown, with sometimes a few secondary lobes. Bar: 50 μm. We then looked at the production of crystal cells and lamellocytes in lymph glands with enforced Col expression (srpD-Gal4/UAS-col; Figure 5G–5J). Very few crystal cells and numerous lamellocytes were observed, consistent with the circulating hemocyte picture (Figure 5G and 5H). The srpD-Gal4-driven Col expression in the lymph gland is not uniform. Some cells express high levels when compared to the PSC, whereas many others show no detectable expression. A similar pattern was also observed in combination with UAS-lacZ (Figure 5I; data not shown). Double-labelling experiments showed that the lymph gland cells induced to differentiate into lamellocytes surround but do not overlap with the Col-expressing cells (Figure 5J), confirming the instructive role of Col-expressing cells. In all genotypes that we tested, we found equally large numbers of plasmatocytes in the lymph glands (data not shown), which indicates that this cell type is not affected by col loss-of-function and gain-of-function mutations. Altogether, the absence of lamellocytes after parasitization that is associated with the increase in the number of crystal cells in col mutant lymph glands, and the opposite situation in srpD-Gal4/UAS-col lymph glands (Figure 5; Table 1), support the existence of bipotential crystal cell/lamellocyte precursors. A Model for Induction of Lamellocytes in Response to Parasitization In summary, our data show that (i) Col expression defines a specific group of cells within the lymph glands; (ii) lamellocyte differentiation, which is an exclusive feature of lymph gland hematopoiesis, depends upon Col activity; and (iii) the massive production of lamellocytes that follows parasitization does not involve changes in Col expression. We thus propose a two-step signalling model for induction of lamellocytes in response to wasp egg-laying (Figure 5A). According to this scheme, Col endows PSC cells with the competence to respond to a primary signal emitted by plasmatocytes as these permanent immune supervisors form a first layer around the parasite egg (Russo et al. 1996). Subsequently, PSC cells send a secondary signal that orients prohemocytes towards the lamellocyte fate. The production of lamellocytes upon enforced col expression suggests that the need for the primary signal to activate the secondary signal can be bypassed in overexpression experiments. Although several aspects of this model remain to be translated into molecular terms, it certainly sheds a new light on the genetic control of hemocyte lineages in Drosophila. Concluding Remarks B- and T-lymphocytes mediate adaptive immunity, a phylogenetically recent component of the immune system as it is found only in gnathostomes (Kimbrell and Beutler 2001; Mayer et al. 2002). How adaptive immunity emerged during evolution, and was built on top of the innate immune system by which it is controlled and assisted, remains a fascinating question. The requirement for Col function in the Drosophila cellular immune response, and EBF function in B-cell development in vertebrates, suggests that Col/EBF function was co-opted early during the evolution of cellular immunity. A puzzling question remains, however, of how the cell-autonomous function of EBF in B-cell development, and the non–cell-autonomous function of Col in lamellocyte development, could relate to an ancestral Col/EBF function. We would like to propose that the ancestral expression of Col/EBF in a subset of hematopoietic cells conferred on these cells the ability to respond to signals from circulating immune supervisors (generically designated as macrophages in Figure 6) and provide a secondary line of defence against specific intruders. This cell-specific property in turn laid the ground for the emergence of the vertebrate lymphoid cells on one side and the Drosophila PSC on the other. Although admittedly highly speculative, this proposal takes into account the following considerations. B-cell development represents the default fate of lymphoid progenitors (Schebesta et al. 2002; Warren and Rothenberg 2003). Although specification of B-cells critically depends on EBF (and the basic helix-loop-helix protein E2A), commitment depends on another gene, Pax5. The Pax5−/− pro–B-cells retain the ability to generate a whole range of both ‘innate’ myeloid and lymphoid cells (Nutt et al. 1999; Rolink et al. 1999; Mikkola et al. 2002). Thus, the ontogeny of the B-cell lineage from preexisting myeloid cell types has occurred through several steps, one key event being the co-opting of Pax5, acting downstream of EBF, for which there is no known counterpart in Drosophila hematopoiesis. Second, the co-opting of Col activity for lamellocyte differentiation in larval hematopoiesis most likely came on top of a preexisting hematopoietic system, such as that operating in Drosophila embryos (Evans et al. 2003; Meister 2004). Further investigation of Col/EBF functions in intermediate phyla should provide more insight into the diversity of myeloid lineages and ontogeny of the lymphoid lineages during evolution. Figure 6 A Model for Lamellocyte Specification (A) A model for the induction of lamellocyte differentiation in the Drosophila lymph glands in response to wasp parasitization. Col enables PSC cells to respond to a primary signal (S1) that is likely emitted by plasmatocytes upon their encounter with a parasite (Russo et al. 1996; Meister 2004). As a result, the PSC cells send a secondary signal (S2) that causes prohemocytes to develop into lamellocytes. Notch (N) signalling instructs a fraction of prohemocytes to become crystal cells (Duvic et al. 2002; Lebestky et al. 2003). The circular arrow indicates that increased proliferation leading to increased numbers of crystal cells and lamellocytes follows parasitization (Sorrentino et al. 2002). (B) Schematic view of hematopoiesis in Drosophila and mouse. Left: Lymph gland cells contain two types of hematopoietic cells, PSC cells and uncommitted precursors. These precursors can give rise to either plasmatocytes or crystal cells. Crystal cell precursors can also give rise to lamellocytes upon receiving a signal from the PSC cells expressing Col (dotted arrows); this signalling is itself dependent upon a communication between circulating plasmatocytes and the PSC (A). Right: In mice, hematopoietic stem cells (HSC) give rise to common myeloid precursors (CMP) and common lymphoid precursors (CLP) (adapted from Orkin [2000] and Schebesta et al. [2002]). Signalling between CMP- and CLP-derived cells is an essential component of adaptive immunity. Col and EBF functions, in Drosophila and vertebrate hematopoiesis, respectively, suggest an ancestral role in their conferring on a subset of hematopoietic cells the ability to respond to signals from circulating immune supervisors (generically designated here as macrophages) and to provide a secondary line of defence against specific intruders. Materials and Methods Fly stocks and hemocyte counting Unless otherwise stated, all fly stocks were maintained at 25 °C on standard medium, and genotypes were verified with marked balancer chromosomes. For wasp infection, second instar larvae were submitted to egg-laying by L. boulardi for 2–4 h, then allowed to develop at the appropriate temperature and analysed 24 or 48 h later. Hemocyte observation and counting, and lacZ staining of lamellocytes, were as previously described (Braun et al. 1997; Duvic et al. 2002). Transgenic constructs and flies The srpD-Gal4 transgene: A distal promoter fragment, between 8.8 and 6 kb upstream of the srp transcription start site and a 340-bp fragment overlapping this site were amplified by PCR using 5′-GCTAGCGACGCGTGATGCAACTTAATCAA-3′ and 5′-CTGCAGTTTATGAATGGAAGACGCGGACG-3′ primers, and 5′-CTGCAGACGGCCAAGTCCAACAACAACAA-3′ and 5′-GGATCCCTGTTGCTGCTGTAACTGTTGAT-3′ primers, respectively, then fused before subcloning upstream of the Gal4 coding sequence in a pCaSpeR vector. Transgenic lines were obtained by standard procedures. Because they are embryonic-lethal at 25 °C, the srpD-Gal4/UAS-col animals were kept at 18 °C before shifting to 25 °C at the second larval instar. Immunostaining and in situ hybridisation. Immunostaining and in situ hybridisation of larval lymph glands and embryos were performed as in Crozatier and Vincent (1999) using rabbit anti-Col (1:250), rat anti-Ser (gift from K. Irvine; 1:500), mouse anti-β-galactosidase (Promega, Madison, Wisconsin, United States; 1:1000), mouse lamellocyte-specific L1 (gift from I. Ando; 1:10), and guinea-pig anti-Odd-skipped (gift from J. B. Skeath; 1:100). Peroxidase and Alexa Fluor 546 or 488 labelled secondary antibodies (Molecular Probes, Eugene, Oregon, United States) were used at a 1:500 dilution. In some cases, lymph glands were incubated for 30 min at 37 °C in a propidium iodide solution in the presence of RNase. Mounting in Vectashield medium (Vector Laboratories, Burlingame, California, United States) preceded observation by confocal microscopy (Zeiss LSM 510 [Zeiss, Oberkochen, Germany] and Leica SP2 [Leica, Wetzlar, Germany]). Single-stranded digoxigenin-labelled RNA probes were synthesised from corresponding cDNAs cloned in pGEM (Promega). We thank M. Lagueux for help with the srpD-Gal4 transgene; E. Knust, U. Banerjee, R. Reuter, and the Bloomington Stock Center for fly stocks; J. B. Skeath, I. Ando, and K. Irvine for antibodies; and J. A. Hoffmann, J. Smith, L. Waltzer, and many colleagues for critical reading of the manuscript and discussion. We are grateful to J. Mutterer and B. Ronsin for assistance with confocal microscopy. This work was supported by Centre National de la Recherche Scientifique, EntoMed, Exelixis Inc., l'Association de la Recherche contre le Cancer, and Ministère de la Recherche (ACI Biologie du Développement). Conflicts of interest. The authors have declared that no conflicts of interest exist. Author contributions. MC, AV, and MM conceived and designed the experiments. MC, J-MU, and MM performed the experiments. MC, AV, and MM analysed the data. AV and MM wrote the paper. Academic Editor: Michael Levine, University of California, Berkeley Citation: Crozatier M, Ubeda JM, Vincent A, Meister M (2004) Cellular immune response to parasitization in Drosophila requires the EBF orthologue collier. PLoS Biol 2(8): e196. Abbreviations ColCollier EBFearly B-cell factor LzLozenge PSCposterior signalling centre SerSerrate SrpSerpent wtwild-type ==== Refs References Asha H Nagy I Kovacs G Stetson D Ando I Analysis of ras-induced overproliferation in Drosophila hemocytes Genetics 2003 163 203 215 12586708 Bachmann A Knust E Dissection of cis -regulatory elements of the Drosophila gene Serrate Dev Genes Evol 1998 208 346 351 9716725 Braun A Lemaitre B Lanot R Zachary D Meister M Drosophila immunity: Analysis of larval hemocytes by P-element-mediated enhancer trap Genetics 1997 147 623 634 9335599 Campos-Ortega JA Hartenstein V The embryonic development of Drosophila melanogaster 1997 Berlin Springer 405 Crozatier M Vincent A Requirement for the Drosophila COE transcription factor Collier in formation of an embryonic muscle: Transcriptional response to Notch signalling Development 1999 126 1495 1504 10068642 Crozatier M Valle D Dubois L Ibnsouda S Vincent A Collier, a novel regulator of Drosophila head development, is expressed in a single mitotic domain Curr Biol 1996 6 707 718 8793297 Crozatier M Valle D Dubois L Ibnsouda S Vincent A Head versus trunk patterning in the Drosophila embryo; collier requirement for formation of the intercalary segment Development 1999 126 4385 4394 10477305 Duvic B Hoffmann JA Meister M Royet J Notch signaling controls lineage specification during Drosophila larval hematopoiesis Curr Biol 2002 12 1923 1927 12445385 Evans CJ Hartenstein V Banerjee U Thicker than blood: Conserved mechanisms in Drosophila and vertebrate hematopoiesis Dev Cell 2003 5 673 690 14602069 Goto A Kadowaki T Kitagawa Y Drosophila hemolectin gene is expressed in embryonic and larval hemocytes and its knock down causes bleeding defects Dev Biol 2003 264 582 591 14651939 Hagman J Belanger C Travis A Turck CW Grosschedl R Cloning and functional characterization of early B-cell factor, a regulator of lymphocyte-specific gene expression Genes Dev 1993 7 760 773 8491377 Harrison DA Binari R Stines Nahreini T Gilman M Perrimon N Activation of a Drosophila Janus kinase (JAK) causes hematopoietic neoplasia and developmental defects EMBO J 1995 14 2857 2865 7796812 Holz A Bossinger B Strasser T Janning W Klapper R The two origins of hemocytes in Drosophila Development 2003 130 4955 4962 12930778 Hou XS Perrimon N The JAK-STAT pathway in Drosophila Trends Genet 1997 13 105 110 9066269 Kambris Z Hoffmann JA Imler JL Capovilla M Tissue and stage-specific expression of the Tolls in Drosophila embryos Gene Expr Patterns 2002 2 311 317 12617819 Kimbrell DA Beutler B The evolution and genetics of innate immunity Nat Rev Genet 2001 2 256 267 11283698 Lanot R Zachary D Holder F Meister M Postembryonic hematopoiesis in Drosophila Dev Biol 2001 230 243 257 11161576 Lebestky T Chang T Hartenstein V Banerjee U Specification of Drosophila hematopoietic lineage by conserved transcription factors Science 2000 288 146 149 10753120 Lebestky T Jung SH Banerjee U A Serrate-expressing signaling center controls Drosophila hematopoiesis Genes Dev 2003 17 348 353 12569125 Lin H Grosschedl R Failure of B-cell differentiation in mice lacking the transcription factor EBF Nature 1995 376 263 267 7542362 Luo H Hanratty WP Dearolf CR An amino acid substitution in the Drosophila hopTum-l Jak kinase causes leukemia-like hematopoietic defects EMBO J 1995 14 1412 1420 7729418 Maier H Hagman J Roles of EBF and Pax-5 in B lineage commitment and development Semin Immunol 2002 14 415 422 12457614 Mayer WE Uinuk-Ool T Tichy H Gartland LA Klein J Isolation and characterization of lymphocyte-like cells from a lamprey Proc Natl Acad Sci U S A 2002 99 14350 14355 12388781 Meister M Blood cells of Drosophila Cell lineages and role in host defence Curr Opin Immunol 2004 16 10 15 14734104 Mikkola I Heavey B Horcher M Busslinger M Reversion of B cell commitment upon loss of Pax5 expression Science 2002 297 110 113 12098702 Nutt SL Heavey B Rolink AG Busslinger M Commitment to the B-lymphoid lineage depends on the transcription factor Pax5 Nature 1999 401 556 562 10524622 Orkin SH Diversification of haematopoietic stem cells to specific lineages Nat Rev Genet 2000 1 57 64 11262875 Qiu P Pan PC Govind S A role for the Drosophila Toll/Cactus pathway in larval hematopoiesis Development 1998 125 1909 1920 9550723 Rehorn KP Thelen H Michelson AM Reuter R A molecular aspect of hematopoiesis and endoderm development common to vertebrates and Drosophila Development 1996 122 4023 4031 9012522 Rizki TM Rizki RM The cellular defense system of Drosophila melanogaster . 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Insect ultrastructure 1984 New York Plenum Publishing 579 604 Rolink AG Nutt SL Melchers F Busslinger M Long-term in vivo reconstitution of T-cell development by Pax5-deficient B-cell progenitors Nature 1999 401 603 606 10524629 Russo J Dupas S Frey F Carton Y Brehelin M Insect immunity: Early events in the encapsulation process of parasitoid (Leptopilina boulardi) eggs in resistant and susceptible strains of Drosophila Parasitology 1996 112 135 142 8587797 Schebesta M Heavey B Busslinger M Transcriptional control of B-cell development Curr Opin Immunol 2002 14 216 223 11869895 Schubiger M Palka J Changing spatial patterns of DNA replication in the developing wing of Drosophila Dev Biol 1987 123 145 153 3622926 Shrestha R Gateff E Ultrastructure and cytochemistry of the cell types in the larval hematopoietic organs and hemolymph of Drosophila melanogaster Dev Growth Differ 1982 24 65 82 Sorrentino RP Carton Y Govind S Cellular immune response to parasite infection in the Drosophila lymph gland is developmentally regulated Dev Biol 2002 243 65 80 11846478 Sparrow JC Melanotic tumours. In: Ashburner M, Wright TRF, editors. The genetics and biology of Drosophila 1978 London Academic Press 277 315 Tepass U Fessler LI Aziz A Hartenstein V Embryonic origin of hemocytes and their relationship to cell death in Drosophila Development 1994 120 1829 1837 7924990 Waltzer L Ferjoux G Bataille L Haenlin M Cooperation between the GATA and RUNX factors Serpent and Lozenge during Drosophila hematopoiesis EMBO J 2003 22 6516 6525 14657024 Ward EJ Skeath JB Characterization of a novel subset of cardiac cells and their progenitors in the Drosophila embryo Development 2000 127 4959 4969 11044409 Warren LA Rothenberg EV Regulatory coding of lymphoid lineage choice by hematopoietic transcription factors Curr Opin Immunol 2003 15 166 175 12633666

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020199Research ArticleEvolutionGenetics/Genomics/Gene TherapyHomo (Human)Evidence for Widespread Convergent Evolution around Human Microsatellites Convergent Evolution around MicrosatellitesVowles Edward J 1 Amos William 1 1Department of Zoology, University of CambridgeCambridgeUnited Kingdom8 2004 17 8 2004 17 8 2004 2 8 e1998 8 2003 27 4 2004 Copyright: © 2004 Vowles and Amos.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. Evolution's "Molecular Clock": Not So Dependable After All? Microsatellites are a major component of the human genome, and their evolution has been much studied. However, the evolution of microsatellite flanking sequences has received less attention, with reports of both high and low mutation rates and of a tendency for microsatellites to cluster. From the human genome we generated a database of many thousands of (AC)n flanking sequences within which we searched for common characteristics. Sequences flanking microsatellites of similar length show remarkable levels of convergent evolution, indicating shared mutational biases. These biases extend 25–50 bases either side of the microsatellite and may therefore affect more than 30% of the entire genome. To explore the extent and absolute strength of these effects, we quantified the observed convergence. We also compared homologous human and chimpanzee loci to look for evidence of changes in mutation rate around microsatellites. Most models of DNA sequence evolution assume that mutations are independent and occur randomly. Allowances may be made for sites mutating at different rates and for general mutation biases such as the faster rate of transitions over transversions. Our analysis suggests that these models may be inadequate, in that proximity to even very short microsatellites may alter the rate and distribution of mutations that occur. The elevated local mutation rate combined with sequence convergence, both of which we find evidence for, also provide a possible resolution for the apparently contradictory inferences of mutation rates in microsatellite flanking sequences. An analysis of sequences flanking microsatellites in the human and chimpanzee genomes suggests that mutations do not occur independently and randomly, as is commonly assumed in models of DNA sequence evolution ==== Body Introduction DNA base substitutions do not occur randomly (Graur and Li 2000). Instead, they may be clustered in hotspots, for example around methylated CG dinucleotides, or subject to more general biases such as the excess of transitions relative to transversions. In addition, local structural context may be important, with neighbouring bases interacting to favour some changes over others (Blake et al. 1992; Morton et al. 1997; Goodman and Fygenson 1998; Zavolan and Kepler 2001). However, many nonrandom patterns of sequence evolution remain unexplained. Here we explore how an abundant class of repetitive sequences, microsatellites, may influence the pattern of mutations in sequences that surround them. Microsatellites are sequences of repeated 1–6-bp motifs that mutate primarily through the gain and loss of repeat units, in a process thought to depend on DNA replication slippage (Levinson and Gutman 1987; Tautz and Schlötterer 1994). Previous studies indicate that their flanking sequences evolve unusually and often contain mutated versions of microsatellites (Matula and Kypr 1999). Estimates of flanking sequence mutation rates vary greatly. Very slow evolution is suggested by sequence comparisons between distantly related species, where divergence rates may be as low as 0.016% to 0.1% per million years (Schlötterer et al. 1991; Rico et al. 1996; Zardoya et al. 1996). Elsewhere, pedigree studies suggest much higher rates and even hypermutability (Stallings 1995). There is also disagreement about trends in mutation rate, some studies indicating an increase towards the microsatellite (Blanquer-Maumont and Crouau-Roy 1995; Zardoya et al. 1996; Grimaldi and Crouau-Roy 1997; Brohede and Ellegren 1999) while others claim a more even distribution (Karhu et al. 2000). To our knowledge, no one has yet conducted a systematic study of mutational biases operating around microsatellites. The direct study of naturally occurring mutations in flanking sequences is virtually prohibited by their slow rate of accumulation, and inferences based on comparisons between homologous microsatellite loci rely on small numbers of sequences. However, an indirect approach is possible, based on comparisons among very large numbers of microsatellite flanking sequences from the finished human genome. If microsatellites have little or variable influence on their flanking regions, among-locus similarities will be minimal or absent. Conversely, if microsatellites generate similar local mutation biases, nonhomologous loci should betray evidence of convergent evolution. With the publication of large blocks of sequence from the chimpanzee genome, one can extend this approach to ask questions about rate of divergence between homologous flanking sequences. Here we use a combination of these indirect approaches to show that microsatellites appear to create regions around them in which both the rate and spectrum of mutations are modified. Results We studied the most abundant class of human dinucleotide repeats, (AC)n, and for simplicity considered only ‘isolated’ repeats, defined as those at least 100 bp from the nearest AC repeat as small as two units in length. 47% of AC repeats on human Chromosome 1 match these criteria. From the human genomic sequence, maximum sample size was set at 5,000 randomly selected loci for length classes (AC)2 to (AC)5. For longer microsatellites, of which fewer than 5,000 could be found, all sequences encountered were included. Figure 1 displays the length frequency distribution and sample sizes. Additionally, a control set of 5,000 randomly selected, non-microsatellite-associated sequences, each 50 bases long and containing no (AC)2+ repeats, was generated from Chromosome 1. Figure 1 Frequency Distribution of Isolated, Pure (AC)n Microsatellite Lengths (in Repeat Units) in the Human Genome Black shading indicates numbers of microsatellites used for analyses in this study. Distribution of Cassette Type To distinguish between (AC)n and (CA)n repeats, (AC)n microsatellites were divided into subclasses, termed ‘cassettes’, according to their immediate 5′ and 3′ flanking bases such that 5′-X(AC)nY-3′ is referred to as cassette X/Y. Hence, a (CA)3 repeat would be classed as cassette C/A around (AC)2. Such a distinction may appear pedantic, but since both DNA replication fidelity and repair efficiency are known to be influenced by base order and local sequence context (Goodman and Fygenson 1998; Marra and Schar 1999), it seems by no means certain that (AC)n and (CA)n are equivalent. This nomenclature also helps to resolve the problem of defining microsatellite length because (CA)3 equals (AC)2. Figure 2 shows the frequency distribution of cassette types relative to expectations, calculated assuming that each cassette base forms a dinucleotide with the end base of the microsatellite it flanks. Thus, cassette X(AC)nY is viewed as comprising two dinucleotides, XA and CY. The probability of observing XA and CY jointly is then calculated from the individual frequencies of XA and CY estimated using 1 Mb of randomly sampled sequence from Chromosome 1 containing no (AC)2+ repeats. Figure 2 Frequency Distribution of the 16 Possible Microsatellite-Flanking 5′–3′ Base Combinations Relative to Random Expectation (A) Cassette frequencies around (AC)2 microsatellites: black bars, observed; white bars, expected. Error bars show 95% confidence intervals and asterisks indicate significant difference (χ2 tests, 1 d.f. p < 0.05 with sequential Bonferroni corrections). (B) Deviation of cassette frequencies from random expectations around (AC)2, (AC)5, and (AC)10 microsatellites: black, white, and hatched bars, respectively. (C) Sampled number (solid line) and proportion (dotted line) of microsatellites with cassette T/A as a function of microsatellite length. Around (AC)2 microsatellites, the cassette frequencies are broadly similar to those expected from the frequencies of the component dinucleotides in unique sequence DNA, though eight cassettes show significant differences (Figure 2A). However, as AC repeat number increases, the relative frequencies of several cassettes begin to deviate more and more from expectations, either decreasing or increasing in frequency, summarised in Figure 2B. Specifically, cassettes of the kind X/A, and particularly T/A are overrepresented, while cassettes X/C and X/T tend to be underrepresented. The total proportion of (AC) repeats with cassette T/A are shown as a function of repeat length in Figure 2C. The observed pattern could arise either if cassette type influences the rate at which microsatellites change length, or if mutation biases generated by the microsatellite cause interconversion between cassette types. Flanking Sequence Base Composition We consider flanking sequences to extend 50 bases either side of a microsatellite. To compare flanking sequences, we first divided microsatellites according to (AC) repeat number and cassette type, and then calculated the frequency of each of the four nucleotides at each of the 100 possible positions. Any mutation biases present should be revealed by locally changed base composition, and this appears to be the case. For many microsatellite length–cassette combinations, the flanking sequences exhibit strong deviations from random. The observed patterns can be placed in six broad classes according to the strength of a two-base periodicity and the degree of 5′ to 3′ asymmetry. These patterns are illustrated in Figure 3 and summarised in Table 1. Three further classes of less regular patterning can also be defined (Figure S1). For illustration, we chose length (AC)5, since this exhibits the strong patterns while at the same time retaining sufficient sample sizes for analyses to be conducted on the rarer cassette types. Several features are apparent. First, levels of patterning can be remarkably strong, with the probability of observing a given base at a given site varying from less than half of that in unique sequence to more than double, often at adjacent sites. Second, many of the patterns show strong dinucleotide periodicities, presumably reflecting the dinucleotide structure of the microsatellite. Third, there are several examples of clear 5′ to 3′ asymmetry, indicating that mutational patterns on one side of a microsatellite may not be the same as those on the other. Figure 3 Flanking Sequence Frequency Distributions for Six Representative Nucleotide–Cassette Combinations for (AC)5 Microsatellites In each panel, the microsatellite is centrally placed, represented as a gap at position zero, and the cassette type, base, and number of sequences considered (n) are given. Frequency distributions are plotted with separate 95% confidence intervals for odd- and even-numbered positions (shading). Horizontal lines indicate mean frequencies for the 3′ and 5′ flanking regions, calculated separately. (A–F) illustrate the six main classes of patterning where either dinucleotide periodicity or 5′–3′ asymmetry are present, summarised for all cassette–base combinations in Table 1. Table 1 Summary of Patterns in Flanking Sequence Base Frequencies by Cassette As well as showing variation between cassettes, flanking sequence patterning also changes with microsatellite length. For those cassettes where sample size is sufficient to show a trend, that is, T/A and to some extent C/A and A/A, both amplitude of deviation from random and the breadth of patterning tend to increase with increasing AC repeat number. We do not see dramatic changes such as a reversal in 5′ to 3′ asymmetry or the emergence of new patterns. For cassette T/A, pattern strength increases up to (AC)9 but then declines in longer microsatellites. Table 1 reveals a dominant role for nucleotides A and T, with excesses of base A tending to be complemented by deficits at the same positions of base T. In some cases, the excesses of A are interleaved with only weak deviations from base frequency expectation. In other cases, excesses of A are interleaved with excesses of base T. Dinucleotide Patterns In view of the strong two-base periodicities seen for some base–cassette combinations, we next examined the distribution of frequencies of all 16 possible dinucleotide motifs. As expected from the single nucleotide patterning, dinucleotides also tend to show periodic patterning (Figures 4 and S2), and this is particularly pronounced for motif AT. As with the mononucleotide patterns, there is often marked 5′ to 3′ asymmetry (for example, cassette T/T, dinucleotide AT; Figure 4B). Frequency plots for the 16 cassette types reveal patterns that fall into classes similar to those observed for the mononucleotides, summarised in Table 2. Both the presence of patterning and the degree of 5′ to 3′ asymmetry show a strong dependence on cassette type. Figure 4 Flanking Sequence Frequency Distributions for Three Representative Dinucleotide Motif–Cassette Combinations for (AC)5 Microsatellites (See Figure S4 for the four other patterns). In each panel, the microsatellite is centrally placed, represented as a gap at position zero, and the cassette type, dinucleotide motif, and number of sequences considered (n) are given. Frequency distributions are plotted with separate 95% confidence intervals for odd- and even-numbered positions (shading). Horizontal lines indicate mean frequencies for the 3′ and 5′ flanking regions, calculated separately. A summary of how all seven patterns are distributed among all dinucleotide motif–cassette combinations is given in Table 2. Table 2 Summary of Patterns in Flanking Sequence Dinucleotide Frequencies by Cassette From Table 2 it seems that patterning occurs most commonly where the 5′ cassette base is T or the 3′ cassette base is A and least commonly where the 5′ cassette base is either G or A. In almost all cases where patterning is recorded, the dinucleotide involves one or both bases present in the cassette. However, it is unclear whether the flanking pattern is simply an extension of the cassette bases. For example, although 5′ AT or TA periodicity only occurs where the 5′ cassette base is T, CC deviations occur where the 5′ cassette base is A (cassette A/C). As with the mononucleotide patterning, the periodicity in dinucleotide frequencies changes in amplitude and width (5′ to 3′) as repeat number increases. For most cassettes, the paucity of long microsatellites precludes study of how the patterning changes with repeat number. However, cassette T/A is sufficiently abundant for the progression to be described, and cassettes A/A and C/A, although less common, nonetheless yield meaningful results. Figure 5A–5F shows, for cassette T/A, how the patterning of motif AT first becomes detectable by eye around (AC)3, then increases towards a peak in strength at (AC)9 before diminishing as AC repeat number increases further. Cassettes A/A and C/A show similar trends and together suggest that, where patterning occurs, it is apparent by (AC)6. When data were plotted without first categorizing them by cassette type, although a number of the dinucleotide patterns in Table 1 were seen, deviations from expectation were weaker (for example, about half as strong for dinucleotide AT). Figure 5 Dependence of Dinucleotide Flanking Sequence Patterning on AC Repeat Number Plots are as described in Figure 4. The progression for dinucleotide AT is illustrated for the commonest cassette type, (T/A). (A–F) depict AT dinucleotide frequencies, where patterning is most extreme, and show how periodicity and amplitude increase towards a maximum at around (AC)10 and decline thereafter. Other Repetitive Elements in the Genome An artefactual appearance of convergent evolution could arise if microsatellites within major classes of interspersed repetitive elements such as LINE and Alu repeats are treated as independent observations. Such loci will often share a common origin, and hence appear more similar to each other than expected. To address this problem, we used the program RepeatMasker (Smit and Green 1996) to divide Chromosome 1 into sequences related or not related to known interspersed repeats. Just under half (45%) of all isolated microsatellites were found within interspersed repeats, but only a minority contained microsatellites as long or longer than (AC)5. Classifying loci by cassette type, length, and whether they occurred in LINE/L1, SINE/Alu, or unique sequence DNA yielded in most classes sample sizes too low to be of use. However, where sample sizes were adequate, that is, cassette T/A, dinucleotide AT, patterning in unique sequence loci was indistinguishable from that in LINE and SINE microsatellites (Figure S3). If the among-locus similarities were due to shared evolutionary history, we would expect flanking sequences in the three classes to differ. That they do not, suggests an evolutionary process that depends little if at all on original context. Microsatellites in the Flanking Sequence The strongest two-base periodicities we find tend to involve motif AT. Such periodicity might arise in two main ways: either because AT motifs in phase with the microsatellite tend to expand through slippage to form (AT)n microsatellites, or because mutation biases favour the formation of AT motifs in phase with the AC tract. Consequently, we examined the extent to which patterning could be reduced by filtering the flanking sequences for the presence of AT motifs, focusing on cassette T/A and (AC)5 to provide strong patterning and large sample sizes. The results of deleting all flanking sequences containing AT microsatellites with n or more repeats, where n = 2, 3, 4, and 5, are given in Figure 6. This filtering effectively abolishes patterning in all but the region immediately adjacent to the AC repeat tract. Here, patterning extends as far as the maximum value of n allowed, suggesting that the dominant AT patterning results from (AT)n microsatellites developing immediately adjacent to the AC tract. Figure 6 Dependence of Dinucleotide Pattern Strength on the Presence of Repeat Clusters Beginning with the dataset from the scenario showing strong patterning and large sample size (cassette T/A, dinucleotide AT, (AC)5; see Figure 5C), flanking sequences containing (AT)x were excluded, where x equalled 2 or more (A), 3 or more (B), 4 or more (C), and 5 or more (D). Plotting conventions are the same as for Figure 4. We next examined whether the phase of AT dinucleotides was determined solely by their tendency to form clusters next to (AC)n repeats. This is an important test given that our strict definition of a microsatellite restricts our analysis to pure AC repeats and allows the possibility that compound repeats, for example, (AT)n(AC)n(AT)n are included. To do this, we plotted the distribution of single AT motifs around (AC)3+ microsatellites in the subset of flanking sequences with no (AT)n microsatellites, where n > 1. Summed over all AC microsatellite lengths, single AT dinucleotides are overrepresented in 5′ sequences at odd numbered positions and at even numbered positions in 3′ sequences (Figure 7). Excesses (or deficits) in AT occur up to six bases away from the microsatellites, suggesting that the periodic patterns we see do indeed occur in the flanking sequence over and above the generation of AT microsatellites adjacent to the microsatellite itself. In other words, the patterning we see is generated beyond any tendency for our strict definition of a pure AC repeat to include compound repeats. Figure 7 Location of Single AT Dinucleotide Motifs Relative to the Central AC Microsatellite in Flanking Sequences Lacking (AT)2+ Microsatellites Figure shows frequency of AT dinucleotides around all length classes of AC repeat microsatellites longer than (AC)2 (5′ number of sequences, n = 2,924; 3′ number of sequences, n = 3,309), with significantly greater numbers at odd positions 5′ and even positions 3′. Data are for cassette T/A only. Error bars show upper 95% confidence limit. Convergence of Flanking Sequence Pattern To assess the level of any convergent evolution, we used a simple assignment test to determine how often individual sequences resemble others flanking unrelated microsatellites of similar length (see Materials and Methods). Figure 8 summarises these results. If all sequences were evolving divergently, any given sequence would be assigned to each of the microsatellite length classes with equal probability of around 5%. Sequences not associated with (AC)2 or longer were assigned back to their own class 57% of the time, showing that these sequences consistently differ from those near to AC repeat tracts. Remarkably, this figure falls to almost half (32%) for sequences flanking (AC)2, indicating that, even with just two repeats, similarities to other microsatellite flanking sequences already exist. The same pattern extends to other length microsatellites, with flanking sequences tending to be preferentially assigned back to their own or to an adjacent length class. When a flanking sequence is not assigned back to its own class, it is usually assigned to one of three other classes: the ‘1’ class of random sequences, the ‘9’ class where patterning is strongest, or to the longest class, class 21 (unpublished data). Figure 8 Cross-Locus Similarity among Sequences Flanking Microsatellites of Similar Length Length classes are as follows: class 1, randomly selected sequences not containing (AC)2+; classes 2–20, (AC)2–(AC)20; and class 21, (AC)21–25. Figure shows proportion of flanking sequences assigned on the basis of sequence similarity to their own AC repeat number class (dark grey), to the class above (grey), or to the class below (white). Expectation for assignment to self is shown by the horizontal line. Data are for cassette T/A only. Asterisks denote significant overassignment back to the same class or to an adjacent class, tested using χ2 tests (p < 0.05 using sequential Bonferroni corrections). These analyses reveal a tendency for microsatellite flanking sequences to be similar to each other, but fail to quantify the level of sequence change involved. To do this, we sought to estimate similarity among three classes of sequence: (1) blocks of 50 bp lying immediately adjacent to a microsatellite; (2) blocks of 50 bp chosen randomly to lie between 500 and 600 bases downstream from a microsatellite (the random selection aims to remove possible complications of exact position and phase with the microsatellite); and (3) blocks of 50 bp randomly selected from around the genome. Comparisons within class 3 define the average level chance similarity in the genome, here estimated at 12.77 ± 3.28 (sd) bases out of 50. Comparisons within class 1 estimate how much convergent evolution is apparent at any given repeat number, and reveal a profile that rises to a maximum of 14.31 at a length of seven repeats, followed by a gentle decline with increasing length thereafter (Figure 9A). Similarity is significantly above random for all but the very shortest microsatellites. As controls, we also made comparisons between class 1 and class 2 within a locus (Figure 9B), between class 1 and class 2 among loci (Figure 9C), and between class 1 and class 3 (Figure 9D). Each of these comparisons reveals above random similarity in a profile that approximates that of the class 1–class 1 comparisons but peaking at lower levels. Figure 9 Dependence of Sequence Similarity among Flanking Sequences on AC Repeat Number The average number of matches shown (± standard error) quantifies similarity among three classes of sequence: (1) blocks of 50 bp lying immediately adjacent to a microsatellite; (2) blocks of 50 bp chosen randomly to lie between 500 and 600 bases downstream from a microsatellite; and (3) randomly selected blocks of 50 bp from around the genome. Average level of chance similarity in the genome is shown by a black line in each plot (comparison among class 3). 5′ and 3′ sequences are shown separately. Comparisons among sequence classes are shown for class 1 to class 1 (A), class 1 to class 2 for sequences at the same locus (B), class 1 to class 2 for sequences at different loci (C), and class 1 to class 3 (D). Thus, in all cases, sequences immediately flanking a microsatellite show greater similarity to each other, to sequences nearby, and to sequences elsewhere in the genome than randomly selected sequences do to each other, a trend that is maximal for microsatellites around 7–10 repeats in length. We believe these similarities are generated primarily by the enhanced simplicity of microsatellite flanking regions and their tendency to gain AT motifs. Such characteristics allow unusually high matches when compared with random blocks of 50 bases that have high simplicity or contain polyA tracts. Over and above this background level of elevated similarity, proximity to any microsatellite appears to increase similarity, implying that microsatellites tend to lie more generally in regions of similar base composition. This might reflect either a tendency for microsatellites to arise preferentially in certain broad sequence contexts, or modification of the local base composition by the microsatellite itself. Moreover, similarity is further enhanced when a flanking sequence is compared with a neighbouring block. This suggests a local context effect such as might arise through the isochore structure of the genome, with neighbouring blocks being located in the same isochore and hence ‘coloured’ by the same nucleotide biases. How Big Is the Sphere of Influence of a Microsatellite? To define more precisely the regions where convergent evolution is occurring, we repeated the assignment test but instead of using the full 50 bases either side we now used a symmetric pair of moving 25-base windows placed either side of the AC microsatellite (Figure 10). Close to the microsatellite, the assignment probability is similar to but a little greater than that observed for the full 50-base analysis. As expected, this value declines as the window is moved away from the microsatellite. However, overassignment of (AC)2 flanking sequences to their own class is significant up to ten bases away from the microsatellite (χ2 = 9.7, d.f. = 1, p < 0.05 with sequential Bonferroni correction), and only when the window reaches 24 bases from the microsatellite does the assignment level fall to the value of 4.8% expected of random sequences. Figure 10 Relationship between the Probability of Assigning (AC)2 Microsatellite Flanking Sequences to Self and Proximity to the AC Microsatellite Solid line shows the probability of assignment back to self. Analysis is restricted to (AC)2 flanking sequences and is based on an assignment window 25 nucleotides wide on each side of the microsatellite. Dotted line indicates assignment probability expected of random DNA sequences. Do Microsatellites Increase the Local Rate of Evolution? So far we have considered only the nature of the mutations that affect flanking sequences, and not their rate. To examine whether mutation rates are affected by the presence of a microsatellite, we used Megablast (National Center for Biotechnology Information (NCBI); ftp://ftp.ncbi.nih.gov/blast/executables) to compare microsatellites identified in completed sections of the chimpanzee genome against homologous loci identified in humans. If homologous loci are identified through comparisons among their immediate flanking sequences, an element of circularity will be introduced, since loci with lower rates of evolution will be identified preferentially. To circumvent this problem, we used a region 300 bases in length and 220 bases downstream of the microsatellite to conduct each Megablast search. A total of 8218 chimpanzee loci were identified, and they yielded 5537 unique human homologues. Since microsatellite flanking sequences may contain insertions or deletions, we adopted the following approach so as to minimise problems of alignment. The chimpanzee flanking sequence was divided into 20 contiguous blocks of 20 bases, ten on each side of the microsatellite. Each block was then compared against 1,000 bases of human sequence, downstream from the region identified by Megablast, to find the best possible match. To filter sequences with major rearrangement we required both that all 20 blocks match with at least 15/20 bases, and that matched blocks all lie in the same order as their homologues. Differences between pairs of homologous flanking sequences were then quantified, at each of the 20-block positions, as the proportion of perfectly matching blocks and the average number of matches within each block (Figure S4). After the above filtering, our data base contained 5017 sequences (91% of the original number), and among these, approximately 77% of the blocks were identical. Around (AC)2–3 there is little apparent variation in either measure of similarity with block position apart from a small tendency for 5′ blocks to show an increasing average percentage match closer to the microsatellite. However, although the trends are by no means strong, around longer microsatellites similarity of blocks near to the microsatellite is reduced, particularly when measured using average percentage matches (Figure S4C and S4D). Our analysis of dinucleotide frequencies around microsatellites shows patterns of similarity on a smaller scale than might be revealed with 20-base blocks of sequence. To investigate the number of changes in the immediate flanking bases, we also calculated the proportion of mismatches occurring at a given base for each 5′ and 3′ sequence in the immediate flanking blocks (blocks −1 and +1; Figure S5). The average proportion of mismatches is relatively constant along the flanking sequence around short microsatellites, with a possible rise immediately 3′ of the microsatellites. However, the clear overabundance of mutations in the immediate flanking region of long microsatellites, with a higher than average proportion of mismatches −9 bases 5′ and +4 bases 3′, indicates that the regions closest to the microsatellites are indeed experiencing elevated mutation rates. The dearth of mismatches further away from the microsatellites, and a similar overall mean proportion of mismatches to that around short microsatellites (0.012 versus 0.011, respectively), suggests that a higher mutation rate close to microsatellites is occurring at the expense of the number of mutations further from microsatellites. Discussion We have studied very large numbers of (AC)n microsatellite flanking regions culled from the human genome and asked questions about the extent that these evolve in any consistent and unusual manner. Patterning is present in the form of over- and underrepresentation of bases and dinucleotide motifs at odd and even positions either side of the microsatellite. Pattern strength is maximal around (AC)9, but appears present even around sequences as short as (AC)2 and may extend as many as 50 bases either side. Some patterning is more or less symmetrical, but we also found several examples showing strong 5′ to 3′ asymmetry, implying that the two ends of a microsatellite are by no means equivalent. The net result is that sequences flanking microsatellites of a given length tend to be more similar to each other than to random sequences or to sequences flanking microsatellites of different lengths. Thus, there appears to be convergent evolution. Finally, we compared large numbers of homologous flanking sequences between humans and chimpanzees, and found evidence that mutation rates near microsatellites tend to be somewhat elevated. Sequences surrounding (AC)n tracts exhibit remarkable levels of patterning, with any given dinucleotide motif tending to be much more likely to occur at even numbered positions rather than odd, or vice versa. For several reasons, we believe that the patterning arises due to the structural properties of the microsatellite (see below), becoming more pronounced as repeat number increases. These reasons include the following: the consistently central placement of microsatellites within the patterning, the dependence of the strength of patterning on AC repeat number, the similarity between microsatellites in LINE and SINE elements and those elsewhere, the weakness of the patterning around (AC)2, and the strong influence of cassette type on the form of patterning. Unfortunately, it is surprisingly difficult to eliminate the alternative hypothesis, namely that the patterning arises due to some other force and that AC repeats then either form or expand more rapidly when placed centrally within the pattern. This ambiguity is particularly relevant to the question of cassette distribution, where it seems reasonable both that (AC)n tracts might cause biased interconversion between cassettes and that certain cassettes may allow slippage more than others. For example, while the structural properties of AC repeats are known to generate mutational biases in adjacent bases (Timsit 1999) capable of changing cassette type, minisatellite mutation rate can depend critically on the presence of a particular base in the flanking sequence (Monckton et al. 1994). The relationship between an AC microsatellite and its flanking sequences begins surprisingly early, with (AC)2 already showing a small but significant bias in the distribution of cassette types and greater similarity to other sequences flanking AC microsatellites than to random sequences. In addition, the moving window assignment test indicates that significant convergence exists even when the ten bases closest to the microsatellite are excluded. Such a wide influence around such a common, short motif is remarkable and suggests that a high proportion of the genome may be affected by these and similar forces. To illustrate, (AC)2 is expected to occur every 250 bases, as is (GT)2. Taking the sphere of influence on each side as ten bases plus half the 25-bp window yields a value of 45. This predicts that over 30% (approximately 45 bases of every 125) of the genome will be affected by (AC)2 on one strand or the other, a figure that will only increase with inclusion of longer arrays and other microsatellite motifs. As AC repeat number increases, so does the strength of patterning, becoming pronounced by (AC)5 and peaking in strength at (AC)9. Although patterning is seen in several different dinucleotide motifs, even in the human genome there are insufficient data to study any but the commonest cassette–motif combinations over a wide range of microsatellite lengths. Focusing on the motif AT, we found evidence that the strongest patterning was due to the development of AT microsatellites abutting AC tracts. However, this is not the only effect. After removal of all (AT)2 or longer microsatellites, there remains a significant tendency for single AT motifs to appear in phase with AC tracts, suggesting that mutation bias as well as slippage is involved. Given the increase in strength of patterning between (AC)2 and (AC)9, it might seem logical that the pattern would become stronger and stronger as repeat number increases further. Instead, (AC)9 appears to be the peak strength, with longer microsatellites showing lower amplitude but a broader spread of patterning. It is interesting that this peak coincides with the length at which microsatellites begin to become polymorphic: a common rule of thumb for marker development in mammals is that primers are designed for loci carrying ten or more repeats (Weber 1990). This may be mere coincidence or may reflect, for example, a change in mutation process associated with individuals who are heterozygous for alleles carrying different repeat numbers (Rubinsztein et al. 1995; Amos et al. 1996; Amos and Harwood 1998). Again, there are parallels with minisatellites, where many mutations occur by the transfer of material from one homologous chromosome to the other (Jeffreys et al. 1995). The rich patterning we find presumably arises through local mutation biases. Previous work on mutation biases has tended to reveal either generic effects such as isochors (Bernardi 2000), where some bases are favoured over others in large regions of the genome, or specific but highly localised biases where one or two bases may influence what happens to their immediate neighbours (Blake et al. 1992; Morton et al. 1997; Goodman and Fygenson 1998; Zavolan and Kepler 2001). The patterns we find suggest a somewhat intermediate process in which mutational dependency appears to extend over distances of 30 bases or more. At the same time, the patterning is position dependent, in that it involves not just, for example, a favouring of A over other bases, but, instead, a favouring of A over other bases at even numbered sites. The actual mechanism that causes patterning remains unclear, but our data suggest a model based on the structural properties of AC repeat tracts. Local variation in DNA structure is known to be associated with mutational biases (Morton et al. 1997) and variation in mutation rate (Petruska and Goodman 1985; Goodman and Fygenson 1998), as well as possibly influencing the mismatch repair process (Werntges et al. 1986; Marra and Schar 1999). Tracts of repeating AC motifs tend to exhibit unusual structural properties with high propeller twist and shifted base pairing (Timsit 1999), and hence may be considered prime candidates for sequences capable of influencing the evolution of their immediate surroundings. Indeed, crystallographic studies indicate that sequences like (AC)n and (A)n induce local mutation biases (Timsit 1999). The unusual structure of microsatellite DNA may generate mutational biases in at least two ways. First, in AC repeat tracts, each base interacts unusually strongly with the neighbour of its complement base in a way that may lead to misincorporation of incoming nucleotides toward the ends of the microsatellite or in the immediate flanking region. Second, AC tract structure may influence the efficiency of the mismatch repair machinery in correcting either noncomplementary bases or loops resulting from slipped strand misalignment of repetitive DNA. Given that the mismatch repair system is strongly implicated in moderating the otherwise high rates of slippage mutation at microsatellite loci (Levinson and Gutman 1987; Schlötterer 2000), it seems possible that even a small bias in the repair of loop structures might be responsible for the patterning we observe. However, although variation in mismatch repair efficiency may depend to some extent on DNA structure, the effect of sequence context on repair is not well understood (Marra and Schar 1999). Unfortunately, with current understanding, none of these mechanisms would generate mutation biases that extend tens of bases away from the microsatellite, and hence this aspect must await further research. An alternative explanation for some of the patterning, for example, the tendency for single AT motifs to lie in phase with the microsatellite, could be that these elements represent the remnants of a longer and now eroded (AC)n repeat tract. Under this scenario, point mutations at specific positions along the microsatellite would presumably interrupt the repeats. Given a strong bias toward transition mutations, we can explain both the existence of strong AT pattern, with C to T transition mutations dominating over C to R (purine) or A to Y (pyrimidine) transversion mutations, and also the increase in pattern strength around longer microsatellites, with interruptions in longer arrays more likely to be internal to the repeat tract and hence be excluded from the analysis. However, we suggest that this model is unlikely for two reasons. First, such a model fails to accommodate the strong asymmetry in patterning that is observed for some dinucleotides and specific cassette bases around the (AC)n repeat tract. Polarity has been noted for minisatellite mutations, with mutational processes differing between the two ends of the repeat tract (Armour et al. 1993; Jeffreys et al. 1994), but a microsatellite is much simpler in structure than a minisatellite and any polarity would have to affect some dinucleotides but not others. Second, the commonest and strongest patterning is observed for dinucleotide AT, and this would require high rates of C to T transitions but effectively no A to G transitions. More generally, the microsatellite erosion model predicts that flanking sequence patterning should be dominated by purine/pyrimidine, and this is not the case (see Table 2). The patterning we describe appears to represent an important component of the forces that shape genome evolution, both in terms of its ubiquity and the absolute strength of its effect. It follows that there are many possible practical and theoretical implications. For example, even very short microsatellites appear able to cause some level of convergent sequence evolution, and hence to confound phylogenetic analyses. Similarly, microsatellites near genes may increase local mutation rates and influence the spectrum of new mutations that arise. To explore the size of these effects we designed experiments both to measure absolute convergence and to ask about evidence for changes in mutation rate. To measure convergence, we made various comparisons between blocks of 50 bases chosen randomly, lying next to a microsatellite and lying near a microsatellite. We found an ordered progression of similarity from 12.77/50 bases for random–random through to a maximum of 14.31/50 bases between blocks adjacent to microsatellites 7–10 repeats long, an increase of 12% similarity. Although modest, trends are highly significant, with all comparisons showing a dependency on microsatellite length that peaks at around 7–10 repeats. The most parsimonious explanation for these similarities is that sequences flanking AC microsatellites tend to be AT-rich and to exhibit increased simplicity. Both these characteristics would increase the chance of flanking sequences being unusually similar both to each other and to random sequences that may contain polyA tails or other sources of simplicity. At the same time, the high scores gained by (AC)7–10 both for assignment to their own class and for similarity to each other relative to random blocks provide a clear indication that convergent sequence evolution is occurring. Interestingly, any given flanking sequence tends to be more similar to a block 500 bases away than to a similarly placed block near a different microsatellite, suggesting longer range patterning such as might arise through placement within the same isochore (Bernardi 2000). Furthermore, our attempts to measure variation in mutation rate indicate reduced similarity between homologous human and chimpanzee sequences, implying a higher rate of evolution, at least for a region in the order of ten bases around the microsatellite. On a scale of blocks of 20 bases the trends are less convincing. Having said this, it seems likely that any genuine variation in mutation rate would be to some extent masked by the convergent evolution, and hence that this aspect would benefit from further investigation. In conclusion, previous studies of microsatellite flanking sequences have identified several features, including a tendency to harbour other microsatellites, a locally increased mutation rate, and, conversely, conservation over unexpectedly large tracts of evolutionary time. Our analyses support all these trends and provide a possible resolution for the apparent contradiction between faster evolution but at the same time greater sequence conservation. Although there is evidence that mutation rates near microsatellites are elevated, we also find evidence of convergent evolution. Consequently, the increased rate of change may be to some extent neutralised and perhaps even reversed by the tendency for similar changes to occur in related lineages. Furthermore, the greatest changes appear to occur in flanking sequences around microsatellites that are below the length used as markers, at least in humans. Overall, therefore, we have been able to formalise previous anecdotal evidence and hence to document a remarkably widespread source of directional change and nonrandom evolution that undoubtedly plays an important role in shaping the make-up of our genomes. Materials and Methods Dataset. Our dataset of (AC)n dinucleotide repeats was extracted from the human genome (build 33, NCBI Reference Sequences; NCBI, Bethesda, Maryland, United States) using a custom macro written in Visual Basic. Only microsatellites separated by at least 100 bp from the nearest (AC)2 or longer were included in the dataset. Thus (AC)2AT(AC)10 would not be included in the dataset, whereas ACAT(AC)10 would be included as (AC)10. Flanking sequences are here defined as the 50 bases lying either side of a microsatellite. No attempt was made to translate TG repeats with complementary AC repeats on the opposite strand. Consequently, all our microsatellites are 5′-(AC)n-3′. Flanking sequence base composition. For each frequency estimate, 95% confidence intervals were derived based on the binomial distribution (n < 200 observations) or a normal approximation (n ≥ 200 observations). Bases used to define cassette type were excluded from all calculations, and expected frequencies were taken as the average frequency across all positions. Convergence of flanking sequence pattern: assignment test. Microsatellites were divided into 21 classes according to repeat number. Class 1 was the control set, comprising 5,000 randomly selected, non-microsatellite-associated sequences from Chromosome 1. All other classes contained flanking sequences from single-length microsatellites, except class 21, which contained combined data from microsatellites 21–25 repeats long. Analysis was restricted to the most abundant cassette class, T/A, yielding sample sizes that peaked at 1,087 for (AC)5 and declined to 175 for (AC)20 (see Figure 2). As an index of similarity, we calculated the log likelihood of observing a given sequence based on its position-specific dinucleotide motif composition: where fijk is the frequency of dinucleotide i at position j (j ≠ −1 or 0, with position 0 including the microsatellite and its cassette bases) in flanking sequences of class k. To avoid bias, when a sequence was compared with its own class, its contribution to the dinucleotide frequencies was first removed. For each sequence in turn, A was calculated for every class and the sequence was then assigned to the class that yielded the highest index value. Under convergent evolution, we expect sequences to tend to be assigned to their own or similar length classes. Convergence of flanking sequence pattern: quantifying sequence change. Sequences were again divided into length classes 2 to 21, and each sequence contributed four 50-bp blocks of sequence, one from each side immediately adjacent to the microsatellite but excluding the cassette bases (class 1), and one from each side displaced by a randomly selected number 500–600 bases distal (class 2). In addition, we also generated a database of 5,000 non-microsatellite-associated sequences. When making comparisons within a class, nonindependence was avoided by randomising the sequence order and then comparing sequence 1 with sequence 2, 2 with 3, …, (n − 1) with n. Our index of similarity was simply a count of the number of matching bases. A few pairs of sequences (less than 0.1%) gave high similarity scores of over 30/50 matching bases, presumably because these loci have been duplicated or lie in repetitive elements. Such sequences were discarded. As with all other analyses, sequences containing base ambiguities (marked base N) were also discarded. Rate of evolution around microsatellites. (AC)n repeat microsatellites were extracted from the available chimpanzee finished-quality high-throughput genomic sequence (NCBI) as outlined above for humans. A 300-base region 220 bases upstream from each chimpanzee microsatellite was used by Megablast (Win32 version 2.2.6, NCBI) to identify homologous human loci in the finished genome sequence. Sequences with multiple high-scoring hits were discarded, as they presumably occur because a locus is found in repetitive elements or has been duplicated. Those nonoverlapping hits with at least 280/300 matching bases and an expectation (e-value) greater than five times that of any other hit to the same sequence were thus retained, giving a dataset of 5,537 sequences. Supporting Information Figure S1 Flanking Sequence Nucleotide Frequency Distributions Illustrating Three Classes of Patterning with Neither Strong Periodicity Nor Asymmetry From little structure of any kind (A) to complicated aperiodic clustering (C). Plots are as described in Figure 3. (1.7 MB TIF). Click here for additional data file. Figure S2 Flanking Sequence Frequency Distributions for Four Dinucleotide Motif–Cassette Combinations Further to Those Shown in Figure 4 Plots are as described in Figure 4. (3.0 MB TIF). Click here for additional data file. Figure S3 Dinucleotide Flanking Sequence Patterning in Interspersed Repeats and Unique Sequence DNA Figure depicts equivalent patterns of asymmetry in AT dinucleotide frequencies for the commonest cassette type, (T/A), around microsatellites in unique sequence DNA (A), LINE/L1 elements (B), and SINE/Alu elements (C). Plotting conventions are the same as for Figure 4. (1.4 MB TIF). Click here for additional data file. Figure S4 Dependence of Differences among Homologous Loci on Location of Microsatellite Block position is relative to the central microsatellite (not shown). (A and B) Proportion of exact matches (with 95% binomial confidence intervals) and average number of matches, excluding exact matches (± standard error), with block position around (AC)2–3 microsatellites (n = 4,593). (C and D) As (A and B) but for (AC)4+ microsatellites (n = 356). Average proportion of exact matches and number of matches, calculated separately for 5′ and 3′ blocks around (AC)2–3 microsatellites, are shown by a black line in (A) and (C), and (B) and (D), respectively. Average percentage match rather than average match is plotted in (B) and (D) because overlapping blocks were truncated to exclude overlapping regions from the analysis, with the result that not all blocks contained 20 bases. (2.9 MB TIF). Click here for additional data file. Figure S5 Mean Proportion of Mismatches along Homologous Flanking Sequences The proportion of mismatches occurring at a given base in a flanking sequence are averaged over (AC)2–3 microsatellite loci (A) and over (AC)4+ microsatellite loci (B). Shown ± standard error. The microsatellite at base position 0 is not shown. Expectation, calculated separately for 5′ and 3′ sequences around (AC)2–3 microsatellites, is shown by a black line in both plots. (3.4 MB TIF). Click here for additional data file. Work was funded under a Natural Environment Research Council studentship. We are grateful for help with computing facilities from David Judge (Department of Genetics, Cambridge University). Conflicts of interest. The authors have declared that no conflicts of interest exist. Author contributions. EJV and WA conceived and designed the experiments. EJV performed the experiments and analyzed the data. EJV and WA wrote the paper. Academic Editor: David Penny, Massey University Citation: Vowles EJ, Amos W (2004) Evidence for widespread convergent evolution around human microsatellites. PLoS Biol 2(8): e199. Abbreviations NCBINational Center for Biotechnology Information ==== Refs References Amos W Harwood J Factors affecting levels of genetic diversity in natural populations Philos Trans R Soc Lond B Biol Sci 1998 353 177 186 9533122 Amos W Sawcer SJ Feakes RW Rubinsztein DC Microsatellites show mutational bias and heterozygote instability Nat Genet 1996 13 390 391 8696328 Armour JAL Harris PC Jeffreys AJ Allelic diversity at minisatellite Ms205 (D16s309): Evidence for polarized variability Hum Mol Genet 1993 2 1137 1145 8401495 Bernardi G Isochores and the evolutionary genomics of vertebrates Gene 2000 241 3 17 10607893 Blake RD Hess ST Nicholsontuell J The influence of nearest neighbors on the rate and pattern of spontaneous point mutations J Mol Evol 1992 34 189 200 1588594 Blanquer-Maumont A Crouau-Roy B Polymorphism, monomorphism, and sequences in conserved microsatellites in primate species J Mol Evol 1995 41 492 497 7563137 Brohede J Ellegren H Microsatellite evolution: Polarity of substitutions within repeats and neutrality of flanking sequences Proc R Soc Lond B Biol Sci 1999 266 825 833 Goodman MF Fygenson DK DNA polymerase fidelity: From genetics toward a biochemical understanding Genetics 1998 148 1475 1482 9560367 Graur D Li WH Fundamentals of molecular evolution, 2nd ed 2000 Sunderland (Massachusetts) Sinauer Associates 481 Grimaldi MC Crouau-Roy B Microsatellite allelic homoplasy due to variable flanking sequences J Mol Evol 1997 44 336 340 9060400 Jeffreys AJ Tamaki K Macleod A Monckton DG Neil DL Complex gene conversion events in germline mutation at human minisatellites Nat Genet 1994 6 136 145 8162067 Jeffreys AJ Allen MJ Armour JAL Collick A Dubrova Y Mutation processes at human minisatellites Electrophoresis 1995 16 1577 1585 8582338 Karhu A Dieterich JH Savolainen O Rapid expansion of microsatellite sequences in pines Mol Biol Evol 2000 17 259 265 10677848 Levinson G Gutman GA Slipped-strand mispairing: A major mechanism for DNA sequence evolution Mol Biol Evol 1987 4 203 331 3328815 Marra G Schar P Recognition of DNA alterations by the mismatch repair system Biochem J 1999 338 1 13 9931291 Matula M Kypr J Nucleotide sequences flanking dinucleotide microsatellites in the human, mouse and drosophila genomes J Biomol Struct Dyn 1999 17 275 280 10563577 Monckton DG Neumann R Guram T Fretwell N Tamaki K Minisatellite mutation-rate variation associated with a flanking DNA-sequence polymorphism Nat Genet 1994 8 162 170 7842015 Morton BR Oberholzer VM Clegg MT The influence of specific neighboring bases on substitution bias in noncoding regions of the plant chloroplast genome J Mol Evol 1997 45 227 231 9302315 Petruska J Goodman MF Influence of neighbouring bases on DNA polymerase insertion and proofreading fidelity J Biol Chem 1985 260 7533 7539 3158658 Rico C Rico I Hewitt G 470 million years of conservation of microsatellite loci among fish species Proc R Soc Lond B Biol Sci 1996 263 549 557 Rubinsztein DC Amos W Leggo J Goodburn S Jain S Microsatellite evolution: Evidence for directionality and variation in rate between species Nat Genet 1995 10 337 343 7670473 Schlötterer C Evolutionary dynamics of microsatellite DNA Chromosoma 2000 109 365 371 11072791 Schlötterer C Amos B Tautz D Conservation of polymorphic simple sequence loci in cetacean species Nature 1991 354 63 65 1944571 Smit AFA Green P RepeatMasker. Available: http://ftp.genome.washington.edu/RM/RepeatMasker.html via the Internet 1996 Accessed 25 June 2004 Stallings RL Conservation and evolution of (Ct)(N)/(Ga)(N) microsatellite sequences at orthologous positions in diverse mammalian genomes Genomics 1995 25 107 113 7774907 Tautz D Schlötterer C Simple sequences Curr Opin Genet Dev 1994 4 834 837 Timsit Y DNA structure and polymerase fidelity J Mol Biol 1999 293 835 853 10543971 Weber JL Informativeness of human (dC-dA)n.(dG-dT)n polymorphisms Genomics 1990 7 524 530 1974878 Werntges H Steger G Riesner D Fritz H Mismatches in DNA double strands: Thermodynamic parameters and their correlation to repair efficiencies Nucleic Acids Res 1986 9 3773 3789 Zardoya R Vollmer DM Craddock C Streelman JT Karl S Evolutionary conservation of microsatellite flanking regions and their use in resolving the phylogeny of cichlid fishes (Pisces: Perciformes) Proc R Soc Lond B Biol Sci 1996 263 1589 1598 Zavolan M Kepler TB Statistical inference of sequence-dependent mutation rates Curr Opin Genet Dev 2001 11 612 615 11682302

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PLoS Biol. 2004 Aug 17; 2(8):e199

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PLoS Biol

10.1371/journal.pbio.0020199

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020200Community PageScience PolicyHomo (Human)A New Model for Open Sharing: Massachusetts Institute of Technology's OpenCourseWare Initiative Makes a Difference Community PageMargulies Anne H 8 2004 17 8 2004 17 8 2004 2 8 e200Copyright: © 2004 Anne H. Margulies.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.M.I.T. offers an education to the world through its OpenCourseWare program ==== Body Imagine a fledgling biology instructor at a university in the developing world. Heading into her first semester of teaching, she is armed with nothing but her college degree, some old notebooks, and—if she is lucky—a late-edition textbook. Forging a curriculum that is both current and engaging for her students could be a daunting challenge. But what if that same young instructor was given free and open access to a syllabus, complete lecture notes, and problem sets and solutions from two members of the faculty of the Massachusetts Institute of Technology (MIT)? And not just any faculty members, but David Page—the recipient of a MacArthur Foundation Prize Fellowship in 1986, a Searle Scholar's Award in 1989, and the Amory Prize for advances in reproductive biology from the American Academy of Arts and Sciences in 1997—and Chris Kaiser, who won a 1999 fellowship from MIT that recognizes his teaching excellence? This is the premise of MIT's OpenCourseWare project. Utilizing the Internet, MIT OpenCourseWare (MIT OCW) has opened MIT's curriculum and educational materials to a global audience of teachers and learners—an instructor at a new engineering university in Ghana, a precocious highschool biology student in suburban Chicago, a political scientist in Poland, a literature professor in upstate New York—who are all now able to use the same materials that MIT's professors rely on to teach their full-time students. The Makings of a Movement Ten years from now, we expect that MIT OCW will have become firmly planted in MIT's educational landscape. But MIT OCW was just a leap of faith when the concept was originally proposed by a group of faculty four years ago. In the fall of 1999, Provost Robert A. Brown asked the faculty committee to provide strategic guidance on how the institute should position itself in the e-learning environment. At first, many members of the group assumed that their work would lead to an “MIT.com” venture. But after a year of analysis, market research, and development of business scenarios, the committee concluded that a revenue-generating distance-education model was not desirable for MIT. The committee went back to the drawing board and, convinced that open software and open systems were the wave of the future, came to a very simple conclusion: that MIT should use the Internet to give its teaching materials away. Brown and MIT President Charles Vest instantly recognized the simplicity and brilliance of the idea. “It seemed to me that it would be a way to advance education, by constantly widening access to our information and inspiring other institutions to do the same with theirs,” Vest said. While the 701 courses currently available represent just a third of the ultimate goal of 2,000 courses by the year 2008, MIT OCW has already had an impact on MIT's campus. We have published teaching materials from almost half of MIT's 950 faculty members, and a significant portion of the faculty have told us that they are already using materials available on MIT OCW—the lecture notes, syllabi, problem sets, and exams of their colleagues—to prepare for their classes, do research, and help their students. But the real payoff of what we hope will become the “opencourseware movement” will be its effect on educators and learners around the world. Our goal is to create a model that other universities can follow and improve upon. Ultimately, the trend toward open knowledge will help bring people of all backgrounds together and promote improved educational systems across the globe. Measuring Success Since April 2001, we have received more than 20,000 e-mail messages from around the world endorsing the vision and potential benefits of sharing knowledge freely. A typical message came from Andrew Wilson in the United Kingdom in October 2003: There can be no greater hope for humankind than the belief that wisdom generated through increased learning will ultimately lead to a better world. With OCW, MIT has taken an ethical stand against the belief that knowledge should only be accessible to those who can pay for it or are in proximity to it.” Just after its “official launch” in fall 2003, MIT began a rigorous data collection process to find out who is accessing MIT OCW, why and how they use it, and what difference the initiative makes. The results of this first baseline evaluation confirm what we have heard anecdotally through those e-mails: that educators, students, and self-learners around the world are using our course materials, and that, overwhelmingly, they find the materials useful in meeting their own learning and teaching goals. Who Is Accessing MIT OCW? On average, MIT OCW clocks over 11,000 visits per day, with nearly a quarter-million unique visitors per month. About 45% of these visitors are from the United States and Canada. Outside North America, the top countries of origin are China, the United Kingdom, Germany, India, and Brazil. About 52% of visitors identify themselves as “self-learners,” 31% as “students” enrolled in a formal course of study, and 13% as “educators.” We view educators as a particularly important target audience because it is through them that MIT course materials can touch the greatest number of people and have the most profound impact on education around the world. Why and how are they using it? MIT OCW asked visitors their primary purpose in using MIT course materials. Of educators who responded, about 57% answered that they use it for course or curriculum development, 33% to enhance their subject matter understanding or support research, and 7% for student advising. Elements of MIT materials have been adapted for classroom use by 47% of educators who answered our survey, while 41% report they are considering it. Critical Mass Among the 33 academic disciplines available are 15 courses from the MIT Department of Biology (see Figure 1), 63 from the Department of Brain and Cognitive Sciences, and 13 from the Harvard–MIT Division of Health Sciences and Technology. Figure 1 Sample MIT OCW Course Homepage for Graduate Biochemistry Course (Image of DNA courtesy of Lawrence Livermore National Laboratory.) Educators, students, and self-learners from a wide variety of fields will find materials they can use in their teaching and learning activities. And as the opencourseware concept spreads to other colleges and universities, we expect that access to the work of faculty from diverse disciplines and institutions will increase, by an order of magnitude, the benefits to educators and learners who (whether for reasons of geography, cost, or culture) would not otherwise have access to such materials. History has proved that education and discovery are best advanced when knowledge is shared openly. Our agenda must evolve to shape the future, and to respond to new challenges and opportunities. At MIT, we believe the idea of opencourseware is one such opportunity, which we must seize during the next decade. For more information about MIT OCW, please contact Jon Paul Potts, MIT OCW Communications Manager, at E-mail: jpotts@mit.edu or 617-452-3621. Anne H. Margulies is Executive Director of the Massachusetts Institute of Technology's OpenCourseWare initiative. E-mail: amarguli@mit.edu Abbreviations MITMassachusetts Institute of Technology MIT OCWMIT OpenCourseWare

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PLoS Biol. 2004 Aug 17; 2(8):e200

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PLoS Biol

10.1371/journal.pbio.0020200

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020217Research ArticleBiotechnologyEcologyGenetics/Genomics/Gene TherapyPlant SciencePlantsInsectsNicotine's Defensive Function in Nature Nicotine's Defensive FunctionSteppuhn Anke 1 Gase Klaus 1 Krock Bernd 1 Halitschke Rayko 1 Baldwin Ian T baldwin@ice.mpg.de 1 1Department of Molecular Ecology, Max Planck Institute for Chemical EcologyJenaGermany8 2004 17 8 2004 17 8 2004 2 8 e2176 2 2004 4 5 2004 Copyright: © 2004 Steppuhn et al.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. Nicotine Keeps Leaf-loving Herbivores at Bay Plants produce metabolites that directly decrease herbivore performance, and as a consequence, herbivores are selected for resistance to these metabolites. To determine whether these metabolites actually function as defenses requires measuring the performance of plants that are altered only in the production of a certain metabolite. To date, the defensive value of most plant resistance traits has not been demonstrated in nature. We transformed native tobacco(Nicotiana attenuata) with a consensus fragment of its two putrescine N-methyl transferase (pmt) genes in either antisense or inverted-repeat (IRpmt) orientations. Only the latter reduced (by greater than 95%) constitutive and inducible nicotine. With D4-nicotinic acid (NA), we demonstrate that silencing pmt inhibits nicotine production, while the excess NA dimerizes to form anatabine. Larvae of the nicotine-adapted herbivore Manduca sexta (tobacco hornworm) grew faster and, like the beetle Diabrotica undecimpunctata, preferred IRpmt plants in choice tests. When planted in their native habitat, IRpmt plants were attacked more frequently and, compared to wild-type plants, lost 3-fold more leaf area from a variety of native herbivores, of which the beet armyworm, Spodoptera exigua, and Trimerotropis spp. grasshoppers caused the most damage. These results provide strong evidence that nicotine functions as an efficient defense in nature and highlights the value of transgenic techniques for ecological research. Transgenic plants confirm the role that nicotine has in protecting tobacco plants from predators in nature and demonstrates the power of transgenic tools in studying ecological interactions in the field ==== Body Introduction Plants produce many secondary metabolites, of which some are thought to function as direct defenses against pathogens and herbivores by reducing their performance, survival, and reproduction. Numerous plant allelochemicals with antiherbivore properties are classified according to their mode of action (e.g., toxins, antifeedants, antidigestive proteins, etc.) (Bennett and Wallsgrove 1994) and have been used in agriculture to control insect pests (Hedin 1991). The fact that a secondary metabolite reduces herbivore performance does not by itself demonstrate that the endogenously expressed metabolite functions defensively in the plant's natural environment (Bell 1987), because the evolutionary interaction between herbivores and their host plants may have reduced the defensive efficacy of the metabolite. Phytophagous insects have evolved various strategies to cope with allelochemicals (Karban and Agrawal 2002) and tend to tolerate, or even co-opt, plant defenses for their own defenses (Wink and Theile 2002). Pharmacological studies demonstrating a resistance effect of metabolites applied to plants or artificial diets (Yamamoto et al. 1968; Bowers and Puttick 1988), and studies using heterologously expressed genes in agricultural systems (Carozzi and Koziel 1997; Hilder and Boulter 1999), represent a first step in evaluating the defensive function of a secondary metabolite. The interpretation of these studies is confounded by both the altered ecological context in which the resistance is measured and the altered chemical milieu, which is also known to influence the defensive function of a metabolite. Stronger evidence for resistance effects of allelochemicals arises from studies establishing correlations between plant resistance against herbivores and the genetically variable accumulation of secondary metabolites (Berenbaum et al. 1986; Shonle and Bergelson 2000) or from studies demonstrating the defensive role played by a suite of elicited metabolites (Orozco-Cardenas et al. 1993; Baldwin 1998; Halitschke and Baldwin 2003). Ideally, the benefits of a putative defense trait should be determined in plants differing only in a single gene that controls the expression of a resistance trait and are otherwise identical (Bergelson and Purrington 1996). To date, studies measuring resistance of “near isogenic” lines with altered metabolite accumulations (Jackson et al. 2002) provide the strongest evidence for their resistance, but these lines, which are created by repetitive backcrossing, are likely to differ in many loci linked to the target locus, which may also affect resistance. Such problems of genetic linkage have been overcome through the use of genetic transformation to explore the fitness effects of herbicide resistance (Bergelson et al. 1996; Purrington and Bergelson 1997) and pathogen resistance (Tian et al. 2003) in field populations of Arabidopsis. In this study, we use transgenic silencing to alter a single putative resistance trait—the production of nicotine—and thereby establish its contribution to plant resistance in the field. The pyridine alkaloid nicotine is one of the best-studied putative plant resistance traits. Because it can interact with the acetylcholine receptors in the nervous systems of animals, nicotine is extremely toxic to most herbivores and, consequently, was one of the first insecticides used to control pests in agriculture (Schmeltz 1971). Evidence for the resistance value of nicotine arises from the agricultural practice of using nicotine sprays and genotypes of cultivated tobacco differing in nicotine levels (Jackson et al. 2002). Although nicotine is widely toxic, insects adapted to nicotine-producing plants have evolved resistance to this alkaloid (Glendinning 2002). The tobacco specialist Manduca sexta (tobacco hornworm) tolerates doses of nicotine that are fatal to unadapted herbivores but grows more slowly on high-nicotine diets (Appel and Martin 1992; Wink and Theile 2002). Other studies suggest that M. sexta might even be better defended by dietary nicotine against its parasitoid, Cotesia congregata, which suffers higher mortality when parasitizing larvae fed on high- rather than low-nicotine diets (Barbosa et al. 1986; Thorpe and Barbosa 1986). Thus, the coevolutionary arms race between nicotine-producing plants and their adapted herbivores may have reduced the defensive value of nicotine. In the native tobacco species Nicotiana attenuata and N. sylvestris, nicotine is the most abundant alkaloid. Elicitation of N. attenuata with jasmonic acid methyl ester (MeJA) in its native habitat increases nicotine content, which is correlated with enhanced plant fitness when plants are attacked (Baldwin 1998). However, herbivore attack and MeJA elicitation (as well as the plant's endogenous jasmonic acid cascade [Halitschke and Baldwin 2003]) regulate many resistance traits, including trypsin protease inhibitors (TPIs), diterpene glycosides, and volatile emissions involved in indirect defense. Hence, nicotine is only one of a suite of putative defense traits elicited by herbivore attack, and its specific role remains to be determined. In laboratory trials, resistance benefits of nicotine production against M. sexta larvae were established using transgenic N. sylvestris plants silenced in their nicotine biosynthesis by antisense expression of putrescine N-methyl transferase (PMT). Plant consumption and the performance of M. sexta larvae were negatively correlated with constitutive nicotine levels in laboratory feeding trials (Voelckel et al. 2001); whether this result applies to plants in their natural habitat is unclear. To examine the resistance effect of nicotine, we transformed N. attenuata with inverted-repeat pmt (IRpmt) and antisense pmt constructs and found that only IRpmt plants had strongly reduced nicotine content. We characterized the defense and growth phenotypes of two independently transformed homozygous IRpmt lines and found that measured direct and indirect defenses did not differ from those of the wild-type (WT) plants, except for a dramatic reduction (greater than 95%) of MeJA-elicited and constitutive nicotine production and an increase in anatabine content. In pulse-chase experiments with D4-nicotinic acid (NA) ethyl ester, we demonstrated that the increased anatabine likely results from a dimerization of the NA that would normally have been used in nicotine biosynthesis. In feeding trials, M. sexta larvae preferred and grew faster on IRpmt than WT leaves. We transplanted WT and IRpmt plants into N. attenuata's native habitat in southwestern Utah and elicited a subset with MeJA. Several naturally occurring herbivore species attacked and damaged unelicited IRpmt plants more than unelicited or elicited WT and elicited IRpmt plants. These results demonstrate that nicotine functions as an effective resistance trait under natural conditions. Results/Discussion IRpmt Constructs Silence Nicotine Production Nicotine accumulation was not reduced in most of the independent lines transformed with antisense pmt constructs (25 lines of pNATPMT1 and six lines of pCAMPMT1) compared to WT (Figure 1A). None of the five lines with lower nicotine accumulation in the T1 screen had nicotine levels lower than those of WT in the homozygous T2 generation. In contrast, 29 of 34 independently transformed lines with the IRpmt construct pRESC5PMT had dramatically reduced constitutive and MeJA-induced nicotine accumulations (Figure 1B). The suppression of nicotine accumulation was stable during plant development and when plants were grown in the glasshouse or in the field in Utah. Clearly, inverted-repeat constructs are more efficient at silencing the expression of endogenous genes, as has been previously described (Wesley et al. 2001). Figure 1 Comparison of Antisense and Inverted-Repeat Silencing of pmt Nicotine content (mean of 5–6 plants/line) normalized to mean of WT of unelicited (control) N. attenuata plants and plants 5 d after elicitation with 150 μg of MeJA per plant from independent lines transformed with (A) antisense pmt constructs and (B) an IRpmt construct. In contrast to the 31 lines transformed with the antisense pmt construct, 29 of the 34 IRpmt lines had dramatically reduced constitutive and MeJA-induced nicotine levels. T, terminator; P, promoter; I, spliceable intron; arrow, 950-bp consensus fragment of pmt1 and pmt2. For details of transformation constructs see Protocol S1. Genomic and Transcriptional Characterization Two homozygous T2 IRpmt lines (108 and 145) with reduced nicotine levels were further characterized. Southern blot analysis using a probe hybridizing to the selective marker in the IRpmt construct demonstrated that both lines contained a single insertion (Figure S1). Transformation with a pRESC transformation vector allowed the transferred DNA (T-DNA) and flanking DNA at the insertion site to be recovered from the plant genomic DNA. These experiments demonstrated that the T-DNA integrated into the N. attenuata genome at a single site in each line, since all sequenced clones from a line (108, n = 4; 145, n = 5) contained the same flanking sequence (see Figure S1 and Protocol S1). Transcripts of the pmt genes in the two lines were significantly reduced to approximately 10% of the constitutive and MeJA-induced WT mRNA levels (Figure 2A), demonstrating that the targeted genes were successfully silenced. Figure 2 PMT Transcript and Alkaloid Levels of IRpmt Lines Mean (± SE) relative PMT mRNA transcript levels in the roots (A), and leaf levels of (B) nicotine and (C) anatabine, in two independent lines of IRpmt-transformed (108 and 145) and WT N. attenuata plants. Elicited (150 μg of MeJA) and unelicited (control) plants were harvested at 10 h for transcript (A) and at 4 d for alkaloid (B and C) quantification. Both IRpmt lines had significantly reduced PMT transcript and nicotine but featured anatabine not present in WT plants. Lowercase letters signify differences at p ≤ 0.01, Bonferroni corrected ([A] n = 3, ANOVA: F2,12 = 12.55; [B] n = 8–10, ANOVA: F2,50 = 135.4; [C] n = 8–10, ANOVA: F2,50 = 39.611]. n.d., not detected. Metabolic Consequences of pmt Silencing in N. attenuata Consistent with the observed silencing of pmt transcripts, the constitutive and induced nicotine levels in transformed plants of both lines were dramatically reduced to 3%–4% of the levels found in WT plants (Figure 2B). All 29 IRpmt lines with reduced nicotine levels accumulated the alkaloid anatabine, which was not detected in WT plants. Constitutive and MeJA-induced total (nicotine, anabasine, and anatabine) alkaloid contents of the two IRpmt lines were about one-half and one-third of the WT levels, respectively, of which anatabine comprised 30% and 23% (Figure 2C). Levels of anabasine representing 20% of the constitutive and 8% of the MeJA-elicited total alkaloid contents in WT plants were unchanged in IRpmt plants (Figure S2). Elevated anatabine levels were also found in recently published studies with antisense pmt transformation of N. tabacum; elevated anatabine levels did not affect transcript levels of other genes encoding enzymes involved in alkaloid metabolism (Chintapakorn and Hamill 2003). Anatabine consists of a pyridine and a piperideine ring. Both are likely derived from NA, which is also the precursor of the pyridine ring of nicotine (Leete and Slattery 1976). Disrupting nicotine biosynthesis at the formation of the pyrrolidine ring by silencing PMT activity might cause an oversupply of the NA used in the biosynthesis of anatabine. Feeding the roots of hydroponically grown MeJA-elicited WT plants with NA ethyl ester resulted in formation of anatabine at levels of about a third of the total alkaloids (nicotine and anatabine) (Figure 3); in the IRpmt lines, anatabine constitutes 98% of the total alkaloids. Feeding plants with D4-NA ethyl ester results in the formation not only of D4-nicotine and D4-anatabine but also of D8-anatabine, demonstrating that the last integrates two D4-NA units. When these experiments are conducted with WT plants, about half of the anatabine is labeled, suggesting that the unlabeled half was formed from endogenous unlabeled NA. In addition, about one-fourth of the WT nicotine was D4-nicotine. In IRpmt plants, in contrast, only traces of D4-nicotine were found, but one-third of the anatabine was either D4- or D8-labeled. In summary, exogenously supplied NA is taken up by the roots of N. attenuata plants and used in alkaloid biosynthesis, and an oversupply of NA results in the formation of anatabine. These results support the hypothesis that the silencing of pmt disrupts nicotine biosynthesis, causing an oversupply of NA and the subsequent formation of anatabine. Figure 3 Alkaloid Biosynthesis and the Consequences of a NA Oversupply Biosynthesis scheme and proportion of unlabeled (M+) and labeled (M++4, M++8) nicotine and anatabine in the leaves of two independently transformed N. attenuata IRpmt lines (108 and 145) and WT plants 5 d after elicitation with 150 μg of MeJA per plant. Plants were grown in hydroponic solutions and supplied with either unlabeled or D4-ring-labeled NA ethyl ester (1 mM) 24 h after elicitation (n = 3 or 4). The oversupply of NA resulted in the formation of anatabine even in WT plants from both labeled exogenous and unlabeled endogenous NA pools. IRpmt plants did not differ from WT plants in any other measured secondary metabolite or growth parameter. Constitutive or MeJA-induced levels of caffeoylputrescine, chlorogenic aid, rutin (Figure S2), TPI activity, or the release of cis-α-bergamotene (Figure S3) in IRpmt-transformed plants did not differ from those of WT plants. Rosette-stage and elongation-stage growth in individual pots in both the glasshouse and the field (Figure S4) did not differ between WT and IRpmt lines, and transformed lines were not visually or morphologically distinguishable from WT plants. Hence, the IRpmt plants represent an ideal construct with which to examine the ecological consequences of nicotine production. Effects of Nicotine Silencing on N. attenuata Herbivores M. sexta larvae reared on IRpmt plants in the glasshouse gained significantly more mass and changed instars faster than larvae reared on WT plants (n = 17–20; ANOVA: p < 0.01, p WT-PMT108 < 0.02, p WT-PMT145 < 0.01). The differences were comparable to those observed for M. sexta larvae reared on nicotine-enriched artificial diets (Parr and Thurston 1972; Appel and Martin 1992) or on nicotine-enhanced WT (Baldwin 1988) or antisense-pmt–transformed N. sylvestris plants (Voelckel et al. 2001). Two-thirds of freshly eclosed M. sexta larvae, given the choice between leaf material from WT or IRpmt (108) plants, preferred to initiate feeding on the latter (n = 43; Chi2 = 6.7, p < 0.01). Such behavior suggests that nicotine plays an important role in determining feeding sites of M. sexta larvae, as has been suggested in a study with cultivated tobacco (Kester et al. 2002). While the relative toxic effects of anatabine and nicotine remain unstudied, these results are likely to underestimate the influence of nicotine on M. sexta choice and performance, because IRpmt plants had enhanced levels of anatabine. Since secondary metabolism is known to be sensitive to environmental parameters that differ between glasshouse and field conditions (e.g., UV-B influence; Caldwell et al. 1983), nicotine, anatabine, and TPI levels of WT and IRpmt plants grown in the field plantation were analyzed: they were found not to differ from plants grown under laboratory conditions (Figure 4A). A M. sexta feeding choice test evaluating the larvae's choice between field-grown WT and IRpmt plants (n = 57; Chi2 = 7.74, p < 0.01) verified the results described above for the same experiment conducted with glasshouse-grown plants. Thus, the phenotype of glasshouse-grown IRpmt plants was not altered by growth under field conditions. In addition, choice tests with field-collected D. undecimpunctata, which was observed colonizing only IRpmt plants in the field plantation, revealed that 77% of these beetles preferred the nicotine-deficient IRpmt leaf material over WT (n = 35; Chi2 = 10.31, p < 0.001). Another beetle species observed occasionally on WT plants, Trichobarus mucorea, does not distinguish between WT and IRpmt leaf material in choice tests (n = 19; Chi2 = 0.05, p = 0.8). Figure 4 Herbivore Damage to IRpmt and WT N. attenuata Plants in Nature (A) Leaf alkaloids (nicotine and anatabine) and TPIs 7 wk after transplantation (n = 6). Mean (± SE) percentage total leaf area damaged by (B) all herbivores and (C) only by Spodoptera exigua on WT N. attenuata plants and plants transformed with an IRpmt construct (108) that were either untreated (solid lines) or elicited (dotted lines; asterisk) with MeJA 7 d after plants were transplanted into a field plot in a native habitat. Differences between 108 and WT, 108*, and WT* are significant at p ≤ 0.05 (n PMT = 36, n WT = 50, n PMT* = 28, n WT* = 27; [B] ANOVA: F3,822 = 5.73, p = 0.001; [C] ANOVA: F3,822 = 4.6, p = 0.004). Plants of the nicotine-deficient transformed line 108 suffered significantly higher leaf area damage than did WT plants, but when line 108 was elicited, leaf damage by all herbivores was reduced to WT levels. In the field plantation, IRpmt plants lost significantly more leaf area to herbivores than did WT plants (Figure 4B), demonstrating that nicotine indeed functions as a direct resistance trait of N. attenuata in its native habitat. Over a period of 16 d, IRpmt plants exposed to naturally occurring herbivores lost 16% of their total leaf area to herbivores, an amount that is more than double the amount of damage incurred by WT plants. In order to meet compliance requirements described in the Code of Federal Regulations (7CFR340.3c) for the introduction of organisms altered through genetic engineering, flowers were removed as they matured, and therefore we could not directly measure the fitness consequences of this greater herbivore load. However, in other experiments with N. attenuata plants grown in natural populations, leaf area damage is negatively correlated with capsule number (Baldwin 1998; Kessler and Baldwin 2004), suggesting that the strongly enhanced herbivore damage of the nicotine-deficient IRpmt plants translates into a fitness loss. IRpmt plants were attacked by a variety of insect herbivores. About half of the total herbivore damage resulted from S. exigua feeding (Figure 4C). One-third of the total herbivore damage was damage from grasshoppers of the genus Trimerotropis, which followed the same general pattern of distribution as S. exigua damage, but the differences between unelicited IRpmt and WT plants were not significant. The damage caused by Epetrix hirtipennis was variable but significantly higher for unelicited IRpmt compared to WT plants (ANOVA: F = 2.81, df = 3, p = 0.04, p PMT-WT < 0.05). MeJA elicitation significantly reduced the damage of IRpmt plants to levels found on WT plants, suggesting that MeJA treatment elicits defense traits that are as efficient as the constitutive levels of nicotine in protecting plants. MeJA elicitation of N. attenuata plants is known to induce a diverse suite of transcriptional responses and secondary metabolites including TPIs, phenolics, flavonoids, phenolic putrescine conjugates, diterpene sugar esters, and volatile organic compounds (Halitschke and Baldwin 2003; Roda and Baldwin 2003), some of which apparently function as resistance traits. Which component of this complex suite of elicited metabolites is as effective as nicotine remains to be determined. It should be noted that the overall amounts of leaf area lost to herbivores was relatively low during the field experiments. Only 5% of the canopy area was lost from control and MeJA-elicited WT plants. In previous experiments (Baldwin 1998), fitness differences were observed between control and MeJA-elicited WT plants in populations that had lost approximately 40% of their canopy area to herbivores. Altogether, these results provide direct evidence for the defensive value of nicotine. In a field trial, we established that a native tobacco, which produces large amounts of nicotine, is better defended against its natural herbivores than are nicotine-deficient transformants of the same genetic background. This is likely mediated by the reduction of herbivore performance and by the fact that these phytophagous insects prefer low-nicotine diets. In contrast to studies demonstrating genetic correlations between the production of secondary metabolites and herbivore resistance (Berenbaum et al. 1986; Shonle and Bergelson 2000), the resistance effects established in this study can be directly attributed to the altered traits. The fact that the silencing of one enzyme in the nicotine biosynthetic pathway redirects metabolite flux, resulting in the accumulation of an apparently less toxic alkaloid, anatabine, underscores the importance of characterizing single-gene transformants for secondary effects. Conclusion Plant secondary metabolites are widely accepted as essential components of a plant's direct defenses against its natural enemies, but unambiguous proof has been lacking, mainly because of the difficulty of altering the expression of single traits in plants and testing the consequences of these manipulations under natural conditions. Transformation technology has provided biologists with the ability to manipulate and study the ecological consequences of single-gene manipulations. To date, the technology has largely been used for the heterologous expression of resistance genes (e.g., Bacillus thuringiensis d-endotoxin) in agricultural systems (see Tian et al. [2003] for an elegant exception), and therefore has provided little evidence for the defensive value of endogenously expressed traits against a plant's native herbivore community. The scientific value of transgenically silencing endogenous genes in native plants to understand the ecological function of particular genes has been undermined by the polarized attitudes towards the use of genetically modified organisms in agriculture. Transgenic down-regulation of nicotine demonstrates that N. attenuata is under relentless herbivore pressure. Disabling this resistance trait, even in a year of low herbivore abundance, results in a large increase in opportunistic herbivory and supports the conclusion that secondary metabolites play an important role in explaining why the earth is largely green (Hairston et al. 1960). Materials and Methods Plant material and transformation N. attenuata Torr. ex Watson (synonymous with N. torreyana Nelson and Macbr.; Solanaceae) grown from field-collected seeds (Baldwin 1998) and inbred 11 or 14 generations were used for transformation and all experiments. Seed germination and the Agrobacterium tumifaciens (strain LBA 4404)–mediated transformation procedure are described in Krügel et al. (2002). In order to silence the expression of the two N. attenuata pmt genes, plants were transformed with pCAMPMT1 and pNATPMT1 vectors, which contain a gene fragment of pmt1 (which has 95% identity to pmt2) in an antisense orientation, and pRESC5PMT, which contains the pmt gene fragment twice in an inverted orientation separated by intron 3 of the Flaveria trinervia gene pyruvate orthophosphate dikinase (pdk) (for vector construction and plasmids see Figure S5 and Protocol S1). T1 plants were screened for hygromycin resistance (hygromycin phosphotransferase II gene of the vector pCAMBIA-1301) and constitutive and induced nicotine accumulation; homozygosity was determined by resistance screening of the T2 plants. Two independently transformed homozygous IRpmt lines (108 and 145) were further characterized by Southern blot analysis and by the rescuing of the transformation vector from genomic DNA into Escherichia coli to identify copy number and insertion site of the T-DNA (see Figure S1 and Protocol S1). PMT mRNA accumulation and secondary metabolites. Transformed lines (108 and 145) and WT plants were grown in 1-l hydroponic vessels in a climate chamber as described in Hermsmeier et al. (2001), and 4-wk-old rosette-stage plants were treated (elicited) on the first two fully expanded (source) leaves with 150 μg of MeJA per plant applied in 20 μl of lanolin paste, or left untreated. Approximately 200 mg of young roots was harvested and frozen in liquid nitrogen 10 h after elicitation, and RNA was extracted with Tri Reagent (Sigma, Taufkirchen, Germany) according to the manufacturer's instructions (n = 3/line/treatment). PMT transcript accumulation was analyzed by real-time PCR (ABI PRISM 7000; Applied Biosystems, Darmstadt, Germany). cDNA was generated from 20 ng of RNA with MultiScribe reverse transcriptase (Applied Biosystems), and amplified using the qPCR core reagent kit (Eurogentec, Searing, Belgium) and a probe and primers that were gene-specific (for sequences see Figure S6). For analysis of secondary metabolites, leaves growing one node above the sink-source transition leaf and young root tissue were harvested 4 d after elicitation (n = 8–10/line/treatment). Samples were analyzed by HPLC for alkaloids, caffeoylputrescine, chlorogenic acid, and rutin (Keinänen et al. 2001; Halitschke and Baldwin 2003). A peak occurring in IRpmt alkaloid extracts but not in extracts of WT N. attenuata was collected and identified by nuclear magnetic resonance imaging as anatabine (for spectra and method, see Protocol S1). To determine whether a NA oversupply was responsible for the formation of anatabine in the transformed lines, we supplied 4-wk-old plants with either unlabeled or D4-NA ethyl ester (1 mM) in their hydroponic solution 24 h after MeJA elicitation (n = 4/line/treatment). After 4 d, the treated leaf was harvested and extracted as above, but analyzed by LC/MS/MS to detect incorporation of the deuterium into nicotine and anatabine (for instrument conditions, see Protocol S1). To examine the release of cis-α-bergamotene in the transformed lines compared to WT, volatiles from hydroponically grown plants (n = 3–5/line/treatment) enclosed in open-top volatile collection chambers were collected for an 8 h period starting 24 h after MeJA elicitation of the first two source leaves, and analyzed by GC/MS (Halitschke et al. 2000). TPI activity in the MeJA-treated leaf 3 d after elicitation was analyzed in plants (n = 5/line/treatment) by radial diffusion activity assay (van Dam et al. 2001). M. sexta performance and feeding choice In the glasshouse, 2-wk-old seedlings were planted individually into 2-l pots with potting soil (C 410; Stender, Schermbeck, Germany) at 26–28 °C under 16-h supplemental light from Philips Sun-T Agro 400- or 600-W Na lights. For analysis of performance, newly eclosed M. sexta larvae (North Carolina State University, Raleigh, North Carolina, United States) were placed on the first-stem leaf of 8-wk-old WT and IRpmt (108 and 145) plants and allowed to feed for 14 d. Larval mass was recorded at 8, 10, 12, and 14 d. The first feeding choice of M. sexta was determined by placing newly eclosed larvae in the center of a 3-cm–diameter cup containing, on opposite sides, 1.5-cm2 WT and IRpmt (108) leaf pieces and recording the leaf on which larvae started feeding (n = 44). Resistance of WT and IRpmt plants to herbivores in the natural habitat. In a field plantation (15 m × 18 m; GPS: lat 37°08′45′′N, long 114°01′12′′) in N. attenuata's natural habitat in southwest Utah, transformed IRpmt (108) and WT plants were exposed to naturally occurring herbivores dispersing from adjacent populations. To allow for spatial heterogeneity, plants were transplanted in a paired design (with 0.3 m and 1.5 m between plants of a pair and between pairs, respectively) in which plants were matched for equal rosette diameters. Plants were grown in soil (Potting Mix; Miracle-Gro, Marysville, Ohio, United States) for 5 wk after germination (Krügel et al. 2002), and were transplanted into the field plot (10 columns by 15 lines) in their 3.8-l pots. Seven days after transplantation, 30 WT and IRpmt plants were elicited with 150 μg of MeJA per plant applied in 20 μl of lanolin paste to the two youngest rosette leaves. Starting 4 d after transplantation, each plant was examined for damage and insects (including predators and eggs) every other day for 14 d. Damage amount was estimated as a percentage of the total leaf area, and the characteristic damage caused by caterpillars, beetles, grasshoppers, myrids, and leafhoppers was noted separately. The most abundant herbivores observed in the field plantation during the release were S. exigua, Trimerotropis spp., E. hirtipennis, and D. undecimpunctata. M. sexta and M. quinquemaculata occurred in the season only rarely, and no eggs were laid in the plantation during the 14 d. As plants began to elongate and produce flowers, they were examined daily, and all flowers were removed before opening and anthesis to meet the performance standards in the Code of Federal Regulations (7CFR340.3c). Consequently, direct fitness measures were unobtainable in this experiment. For analysis of alkaloids and TPIs under field conditions, leaf samples of WT and IRpmt plants in the plot (n = 6) were taken 7 wk after transplantation and frozen (dry ice). To determine if the herbivore phenotype of IRpmt plants observed in glasshouse-grown plants was retained in plants grown under natural light conditions, the M. sexta choice experiment was repeated. The first feeding choices of freshly eclosed M. sexta larvae (North Carolina State University) and of adults of field-collected D. undecimpunctata and Trichobarus mucorea (Chrysomelidae and Curculionidae) found on N. attenuata were determined as described above. Supporting Information Figure S1 Copy Number of T-DNA in the Two Studied IRpmt Lines (A) Southern blot analysis of two independently transformed N. attenuata IRpmt lines (108 and 145) and WT plants. Genomic DNA (15 μg) from individual plants of the three genotypes and the plasmid used for transformation pRESC5PMT (4 ng) were digested with EcoRV and blotted onto nylon membranes (Winz and Baldwin 2001). The blot was hybridized with a PCR fragment of the hygromycin phosphotransferase II gene from pCAMBIA-1301, which is specific for the selective marker on the T-DNA and signifies one insertion in each of the two lines. (B) Ethidium bromide staining of the DNA revealed an overload of the DNA of the IRpmt lines and therefore loading of the WT was controlled by stripping and rehybridization with a PMT probe, which clearly revealed the endogenous pmt1 and pmt 2 genes described (Winz and Baldwin 2001) (unpublished data). (6.3 MB TIF). Click here for additional data file. Figure S2 Secondary Metabolite Levels in the Studied IRpmt Lines Inverted-repeat silencing of pmt did not change the levels of (A) anabasine, (B) caffeoylputrescine, (C) chlorogenic acid, and (D) rutin (mean ± standard error [SE]) in two independently transformed N. attenuata lines (108 and 145) compared to WT plants. Plants were harvested 4 d after receiving one of four treatments: untreated control (Con), wounding (W), wounding and regurgitate application (W+R), and application of 150 μg of MeJA per plant applied in a lanolin paste. Plants were treated at the first two fully expanded (source) leaves and wounding was performed by generating three rows of puncture wounds on each leaf side using a pattern wheel. Subsequently, 10 μl per leaf of either water or M. sexta regurgitate diluted 1:1 (v:v) was dispersed over the puncture wounds (n = 8–10). (179 KB PPT). Click here for additional data file. Figure S3 Proteinase Inhibitor and Volatile Emission of the Studied IRpmt Lines Levels of (A) TPI and (B) cis-α-bergamotene emission (mean ± SE) in two independently transformed N. attenuata IRpmt lines (108 and 145) did not differ from WT plants 4 d (for TPI) and 10 h (for cis-α-bergamotene) after receiving one of four treatments (as described for S2): untreated control (Con), wounding (W), wounding with additional regurgitate application (W+R), and MeJA elicitation. IS, internal standard. (73 KB PPT). Click here for additional data file. Figure S4 Growth Parameters Under Glasshouse and Field Conditions of the Studied IRpmt Lines N. attenuata plants transformed with an IRpmt construct (108 or 145) did not differ in (A) stalk length [n PMT = 43, n WT = 57, n PMT* and n WT* = 28] and (B) rosette diameter [n = 8] from WT grown under either field (A) or glasshouse (B) conditions. Plants in (A) were untreated or elicited (*) with MeJA 7 d after plants were transplanted into a field plot in a native habitat. (98 KB PPT). Click here for additional data file. Figure S5 Transformation Vectors This figure shows plasmids used for the generation of N. attenuata lines with reduced levels of two PMTs due to posttranscriptional gene silencing. Both (A) pCAMPMT1 (10.7 kb) and (B) pNATPMT1 (9.7 kb) allow the synthesis of pmt antisense RNA. (C) pRESC5PMT (12.4 kb) was used for the synthesis of pmt RNA capable of forming an inverted repeat. Functional elements: bla, beta-lactamase gene from plasmid pUC19; hptII, gene for hygromycin resistance from pCAMBIA-1301; LB and RB, left and right border of T-DNA; nptIII, aminoglycoside phosphotransferase of type III from Streptococcus faecalis; ori ColE1, origin of replication from pUC19; ori pVS1, origin of replication from plasmid pVS1; PCaMV and TCaMV, 35S promoter and terminator of cauliflower mosaic virus; pdk i3, intron 3 of pdk; pmt1, gene fragment of pmt1 (95% identical with N. attenuata pmt2); PNOS and TNOS, promoter and terminator of the nopaline synthase gene; repA pVS1, replication protein gene from pVS1; sat-1, nourseothricin resistance gene; staA pVS1, partitioning protein gene from pVS1. Displayed restriction sites mark the borders of functional elements, which are displayed in gray if on the T-DNA and in black if outside the T-DNA. (56 KB PPT). Click here for additional data file. Figure S6 PMT Sequences and TaqMan Probe Nucleotide sequences of N. attenuata pmt1 and pmt2 mRNA (Winz and Baldwin 2001) aligned with ClustalW. Primers and probe (underlined) used for real-time PCR of pmt mRNA are highlighted and bold. (396 KB TIF). Click here for additional data file. Protocol S1 Molecular and Analytical Methods (58 KB DOC). Click here for additional data file. Accession Numbers GenBank accession numbers for the genes discussed in this paper are bla from puc19 (L09137), hygromycin phosphotransferase II from pCAMBIA-1301 (AF234297), pdk (X79095), pmt1 (AF280402), and pmt2 (AF280403). We thank M. Lim and A. Wissgott for outstanding plant transformation services; B. Schneider for NMR analysis; A. Kessler and D. Kessler for species determination; E. Wheeler for editing; the Brigham Young University for use of their awesome field station, the Lytle Preserve; L. Rausing for helping us promote the discussion of the scientific value of transformed plants and J. White and the Animal Plant Health Inspection Service personnel for facilitating their safe use in nature; and the Max-Planck-Gesellschaft for financial support. Conflicts of interest. The authors have declared that no conflicts of interest exist. Author contributions. AS and ITB conceived and designed the experiments. AS, RH, and ITB performed the experiments. AS, BK, RH, and ITB analyzed the data. KG contributed reagents/materials/analysis tools. AS and ITB wrote the paper. Academic Editor: Michael Levine, University of California at Berkeley Citation: Steppuhn A, Gase K, Krock B, Halitschke R, Baldwin IT (2004) Nicotine's defensive function in nature. PLoS Biol 2(8): e217 Abbreviations IRpmtinverted-repeat putrescine N-methyl transferase; MeJA NAnicotinic acid pdk pyruvate orthophosphate dikinase; PMT SEstandard error T-DNAtransferred DNA TPItrypsin protease inhibitor WTwild-type ==== Refs References Appel HM Martin MM Significance of metabolic load in the evolution of host specificity in Manduca sexta Ecology 1992 73 216 228 Baldwin IT Short-term damage-induced increases in tobacco alkaloids protect plants Oecologia 1988 75 367 370 Baldwin IT Jasmonate-induced responses are costly but benefit plants under attack in native populations Proc Natl Acad Sci U S A 1998 95 8113 8118 9653149 Barbosa P Saunders JA Kemper J Trumbule R Olechno J Plant allelochemicals and insect parasitoids effects of nicotine on Cotesia congregata (Say) (Hymenoptera, Braconidae) and Hyposoter annulipes (Cresson) (Hymenoptera, Ichneumonidae) J Chem Ecol 1986 12 1319 1328 24307111 Bell EA Labeyrie V Fabres G Lachaise D Secondary compounds and insect herbivores Insects-plants: Proceedings of the 6th international symposium on insect-plant relationships (PAU 1986) 1987 The Hague Dr. W. Junk Publishers 19 23 Bennett RN Wallsgrove RM Secondary metabolites in plant defense mechanisms New Phytol 1994 127 617 633 Berenbaum MR Zangerl AR Nitao JK Constraints on chemical coevolution: Wild parsnips and the parsnip webworm Evolution 1986 40 1215 1228 Bergelson J Purrington CB Surveying patterns in the cost of resistance in plants Am Nat 1996 148 536 558 Bergelson J Purrington CB Palm CJ López-Gutiérrez J-C Cost of resistance: A test using transgenic Arabidopsis thaliana Proc R Soc Lond B Biol Sci 1996 263 1659 1663 Bowers MD Puttick GM Response of generalist and specialist insects to qualitative allelochemical variation J Chem Ecol 1988 14 319 334 24277012 Caldwell MM Robberecht R Flint SD Internal filters: Prospects for UV-acclimation in higher plants Physiol Plant 1983 58 445 450 Carozzi N Koziel M Advances in insect control: The role of transgenic plants 1997 London Taylor and Francis 301 Chintapakorn Y Hamill JD Antisense-mediated down-regulation of putrescine N-methyltransferase activity in transgenic Nicotiana tabacum L. can lead to elevated levels of anatabine at the expense of nicotine Plant Mol Biol 2003 53 87 105 14756309 Glendinning JI How do herbivorous insects cope with noxious secondary plant compounds in their diet? Entomol Exp Appl 2002 104 15 25 Hairston NG Smith FE Slobodkin LB Community structure, population control, and competition Am Nat 1960 94 421 425 Halitschke R Baldwin IT Antisense LOX expression increases herbivore performance by decreasing defense responses and inhibiting growth-related transcriptional reorganization in Nicotiana attenuata Plant J 2003 36 794 807 14675445 Halitschke R Kessler A Kahl J Lorenz A Baldwin IT Ecophysiological comparison of direct and indirect defenses in Nicotiana attenuata Oecologia 2000 124 408 417 Hedin PA Use of natural products in pest control: Developing research trends. In: Hedin PA, editor. Naturally occurring pest bioregulators 1991 Washington, DC American Chemical Society 1 11 Hermsmeier D Schittko U Baldwin IT Molecular interactions between the specialist herbivore Manduca sexta (Lepidoptera, Sphingidae) and its natural host Nicotiana attenuata . I. Large-scale changes in the accumulation of growth- and defense-related plant mRNAs Plant Physiol 2001 125 683 700 11161026 Hilder VA Boulter D Genetic engineering of crop plants for insect resistance: A critical review Crop Prot 1999 18 177 191 Jackson DM Johnson AW Stephenson MG Survival and development of Heliothis virescens (Lepidoptera: Noctuidae) larvae on isogenic tobacco lines with different levels of alkaloids J Econ Entomol 2002 95 1294 1302 12539845 Karban R Agrawal AA Herbivore offense Annu Rev Ecol Syst 2002 33 641 664 Keinänen M Oldham NJ Baldwin IT Rapid HPLC screening of jasmonate-induced increases in tobacco alkaloids, phenolics, and diterpene glycosides in Nicotiana attenuata J Agric Food Chem 2001 49 3553 3558 11513627 Kessler A Baldwin IT Herbivore-induced plant vaccination. Part I. The orchestration of plant defenses in nature and their fitness consequences in the wild tobacco Nicotiana attenuata Plant J 2004 38 639 649 15125770 Kester KM Peterson SC Hanson F Jackson DM Severson RF The roles of nicotine and natural enemies in determining larval feeding site distributions of Manduca sexta L. and Manduca quinquemaculata (Haworth) on tobacco Chemoecology 2002 12 1 10 Krügel T Lim M Gase K Halitschke R Baldwin IT Agrobacterium -mediated transformation of Nicotiana attenuta , a model ecological expression system Chemoecology 2002 12 177 183 Leete E Slattery SA Incorporation of [2–14C]- and [6–14C] nicotinic acid into tobacco alkaloids. Biosynthesis of anatabine and α,β,-diperidyl J Am Chem Soc 1976 98 6326 6330 965646 Orozco-Cardenas M McGurl B Ryan CA Expression of an antisense prosystemin gene in tomato plants reduces resistance toward Manduca sexta larvae Proc Natl Acad Sci U S A 1993 90 8273 8276 11607423 Parr JC Thurston R Toxicity of nicotine in synthetic diets to larvae of the tobacco hornworm Ann Entomol Soc Am 1972 65 1158 1188 Purrington CB Bergelson J Fitness consequences of genetically engineered herbicide and antibiotic resistance in Arabidopsis thaliana Genetics 1997 145 807 814 9055089 Roda AL Baldwin IT Molecular technology reveals how the induced direct defenses of plants work Basic Appl Ecol 2003 4 15 26 Schmeltz I Nicotine and other tobacco alkalioids. In: Jacobson M, Crosby DG, editors. Naturally occurring insecticides 1971 New York Mercel Dekker 99 136 Shonle I Bergelson J Evolutionary ecology of the tropane alkaloids of Datura stramonium L. (Solanaceae) Evolution 2000 54 778 788 10937252 Tian D Traw MB Chen JQ Kreitman, Bergelson J Fitness costs of R-gene-mediated resistance in Arabidopsis thaliana Nature 2003 423 74 77 12721627 Thorpe KW Barbosa P Effects of consumption of high and low nicotine tobacco by Manduca sexta (Lepidoptera, Sphingidae) on survival of gregarious endoparasitoid Cotesia congregata (Hymenoptera, Braconidae) J Chem Ecol 1986 12 1329 1337 24307112 van Dam NM Horn M Mares M Baldwin IT Ontogeny constrains systemic protease inhibitor response in Nicotiana attenuata J Chem Ecol 2001 27 547 568 11441445 Voelckel C Krugel T Gase K Heidrich N van Dam NM Anti-sense expression of putrescine N-methyltransferase confirms defensive role of nicotine in Nicotiana sylvestris against Manduca sexta Chemoecology 2001 11 121 126 Wesley SV Helliwell CA Smith NA Wang MB Rouse DT Construct design for efficient, effective and high-throughput gene silencing in plants Plant J 2001 27 581 590 11576441 Wink M Theile V Alkaloid tolerance in Manduca sexta and phylogenetically related sphingids (Lepidoptera: Sphingidae) Chemoecology 2002 12 29 46 Winz RA Baldwin IT Molecular interactions between the specialist herbivore Manduca sexta (Lepidoptera, Sphingidae) and its natural host Nicotiana attenuata . IV. Insect-induced ethylene reduces jasmonate-induced nicotine accumulation by regulating putrescine N -methyltransferase transcripts Plant Physiol 2001 125 2189 2202 11299398 Yamamoto I Soeda Y Kamimura H Yamamoto R Studies on nicotinoids as an insecticide. Part VII. Cholinesterase inhibition by nicotinoids and pyridylalkylamines: Its significance of action Agric Biol Chem 1968 32 1341 1348

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020218Research ArticleCell BiologyDevelopmentFrogsThe Regenerative Plasticity of Isolated Urodele Myofibers and Its Dependence on Msx1 Plasticity of Urodele MyofibersKumar Anoop 1 Velloso Cristiana P 2 Imokawa Yutaka 3 Brockes Jeremy P j.brockes@ucl.ac.uk 1 1Department of Biochemistry and Molecular Biology, University College LondonLondonUnited Kingdom2Department of Anatomy and Developmental Biology, Royal Free and University College Medical SchoolLondonUnited Kingdom3Center for Developmental Biology, Laboratory for Evolutionary RegenerationRIKEN, Chuo-ku, KobeJapan8 2004 17 8 2004 17 8 2004 2 8 e21815 3 2004 9 5 2004 Copyright: © 2004 Kumar et al.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. Unraveling the Molecular Basis for Regenerative Cellular Plasticity Regenerating Lost Muscle: Msx1 to the Rescue The conversion of multinucleate postmitotic muscle fibers to dividing mononucleate progeny cells (cellularisation) occurs during limb regeneration in salamanders, but the cellular events and molecular regulation underlying this remarkable process are not understood. The homeobox gene Msx1 has been studied as an antagonist of muscle differentiation, and its expression in cultured mouse myotubes induces about 5% of the cells to undergo cellularisation and viable fragmentation, but its relevance for the endogenous programme of salamander regeneration is unknown. We dissociated muscle fibers from the limb of larval salamanders and plated them in culture. Most of the fibers were activated by dissociation to mobilise their nuclei and undergo cellularisation or breakage into viable multinucleate fragments. This was followed by microinjection of a lineage tracer into single fibers and analysis of the labelled progeny cells, as well as by time-lapse microscopy. The fibers showing morphological plasticity selectively expressed Msx1 mRNA and protein. The uptake of morpholino antisense oligonucleotides directed to Msx1 led to a specific decrease in expression of Msx1 protein in myonuclei and marked inhibition of cellularisation and fragmentation. Myofibers of the salamander respond to dissociation by activation of an endogenous programme of cellularisation and fragmentation. Lineage tracing demonstrates that cycling mononucleate progeny cells are derived from a single myofiber. The induction of Msx1 expression is required to activate this programme. Our understanding of the regulation of plasticity in postmitotic salamander cells should inform strategies to promote regeneration in other contexts. Amphibians such as the salamander can regenerate their limbs. This paper explores how multinucleate muscle cells transform into mononuclear cells and begin to proliferate during regeneration ==== Body Introduction There is currently a significant focus on strategies to promote regeneration in adult mammals and therefore a renewed interest in the mechanisms that underlie regeneration in urodele amphibians. An adult salamander such as the newt or axolotl can regenerate its limbs and tail, jaws, ocular tissues such as the lens, and small sections of the heart (Goss 1969; Eguchi et al. 1974; Oberpriller and Oberpriller 1974; Okada 1991; Ghosh et al. 1994; Brockes 1997; Nye et al. 2003). A key feature of urodele regeneration is the local plasticity of differentiated cells at the site of tissue injury or removal (Brockes and Kumar 2002; Odelberg 2002; Del Rio-Tsonis and Tsonis 2003; Tanaka 2003). This has been investigated for pigment epithelial cells of the iris (Eguchi et al. 1974; Simon and Brockes 2002; Imokawa and Brockes 2003; Imokawa et al. 2004), cardiomyocytes (Oberpriller et al. 1995; Bettencourt-Dias et al. 2003), and skeletal myofibers and myotubes (Hay 1959; Lo et al. 1993; Tanaka et al. 1997, 1999; Kumar et al. 2000; Echeverri et al. 2001), all of which reenter the cell cycle during regeneration, in contrast to their mammalian counterparts. A second aspect of plasticity is the ability of multinucleate skeletal muscle cells to fragment into viable mononucleate cells that then contribute to the regenerate. This process, sometimes referred to as cellularisation, was described in classical studies of limb regeneration (Thornton 1938; Hay 1959), but was first analysed with marked cells by implantation of cultured newt myotubes labelled by microinjection with a lineage tracer (Lo et al. 1993) or by an integrated retrovirus (Kumar et al. 2000). The myotubes were effectively converted to mononucleate cells that proliferated in the blastema, and this process occurred in cells that were blocked from cell cycle reentry (Velloso et al. 2000), thus showing that the two aspects of plasticity are not linked mechanistically. In an important recent contribution, myofibers were labelled in situ by microinjection in the tail of the larval axolotl (Echeverri et al. 2001). After amputation of the tail, the myofibers fragmented into viable mononucleate cells, thus establishing that cellularisation occurs during regeneration and contributes to the proliferative zone or blastema. Our understanding of this intriguing process has received considerable impetus from the recognition of two manipulations that induce mammalian myotubes to undergo fragmentation. The first is exposure to myoseverin, a trisubstituted purine derivative isolated from a combinatorial library (Rosania et al. 2000). It evokes depolymerisation of microtubules, apparently by interacting directly with tubulin, as well as inducing changes in the expression of genes that are implicated in tissue remodelling and wound healing. The second is the conditional expression of the homeobox gene Msx1 in mouse myotubes (Odelberg et al. 2000). Msx1 has been studied as an antagonist of myogenic and osteogenic differentiation (reviewed in Bendall and Abate-Shen 2000) and is expressed in the migrating precursor cells of limb muscle during chick development, apparently to prevent precocious differentiation (Bendall et al. 1999). The expression in mouse C2C12 myotubes evokes two aspects of plasticity that occur in 5%–10% of the cells; the first is cleavage of the cells into smaller multinucleated myotubes, which remain viable, and the other is the formation of mononucleate cells capable of division (Odelberg et al. 2000). In the latter case, the clonal progeny of a single myotube were shown to be capable of several pathways of mesenchymal differentiation. The studies on cellularisation by myoseverin and Msx1 have underlined that mammalian as well as urodele cells are capable of this response (Rosania et al. 2000; Odelberg 2002). Msx1 is expressed during urodele limb regeneration (Carlson et al. 1998; Koshiba et al. 1998), as well as during fin (Akimenko et al. 1995; Nechiporuk and Keating 2002) and heart regeneration in the zebrafish (Raya et al. 2003), along with other Msx family genes. Therefore, it becomes important to investigate whether it controls cellularisation during regeneration. Although prior studies of this process have used the multinucleate myotube as the target cell in culture, the critical target during epimorphic regeneration is the more differentiated striated myofiber. The regeneration of muscle fibers in vertebrates proceeds by the mobilisation of reserve satellite cells (Chargé and Rudnicki 2004), and these have been described in myofibers of larval salamander limbs (Popiela 1976). Their participation in cellularisation was excluded in the earlier experiments on urodele cells by selective injection of a lineage tracer into myotubes in culture (Lo et al. 1993) or myofibers in the salamander tail (Echeverri et al. 2001). In order to address these various questions, we have established a culture system in which striated myofibers are dissociated from the limb of larval salamanders and attach to a culture substrate where they can be observed by time-lapse microscopy. The fibers are found to be activated by dissociation to undergo cellularisation and viable fragmentation, and this depends on expression of Msx1. Results Dissociated Myofibers in Culture In order to obtain striated myofibers, tissue was isolated from the limbs of two species of larval salamander (Ambystoma maculatum or Ambystoma mexicanum), which have been used interchangeably with comparable results. After removing the epidermis, the tissue was dissociated by proteolytic digestion, filtered through a sieve to remove most of the mononucleate cells, and plated in serum-free medium. The striated myofibers readily attached to the culture dish (Figure 1; Figure S1) and were found to express myosin heavy chain (MHC) and titin after antibody staining. In view of the potential contribution of satellite type cells to the issues under investigation, cultures were treated with a viable nuclear stain and the myofibers were examined carefully at 2 d after plating. Of 1,290 fibers examined in seven independent cultures, there were only 46 examples of mononucleate cells adherent to myofibers, and such cells were not observed in the cases of plasticity that are discussed here. Figure 1 A Live Striated Myofiber from the Larval Salamander Photomicrograph of a live striated myofiber dissociated from the larval limb musculature and adhering to the culture dish in serum-free medium. This cell has the appearance of a normal quiescent fiber and was photographed with VAREL optics at 48 h after plating. Scale bar, 50 μm. When cultures were labelled with tritiated thymidine, no labelled nuclei were observed in multinucleate cells after labelling for 24 h (540 myofibers, five cultures) or 48 h (263 myofibers, three cultures), while 16% of the mononucleate cells were labelled in the latter case. It is noteworthy that the absence of S-phase entry in nuclei within multinucleate cells includes the population of myofibers that undergoes the events of cellularisation or fragmentation described below. Cellularisation of Myofibers after Implantation The dissociation of viable myofibers has allowed us to evaluate their plasticity after implantation into a limb blastema, a procedure that has previously been performed only on myotubes formed in cell culture. Fibers were labelled with a cell tracker dye in suspension after dissociation, and single fibers were examined to verify the absence of any adherent mononucleate cells and were drawn into a glass micropipette (Figure 2A). A few fibers (see Materials and Methods) were injected from the pipette into the early forelimb regenerate of a larval axolotl. The regenerating limbs were sectioned 2–4 d later, and many examples were observed of mononucleate cells labelled with the tracker dye (Figure 2B). Such cells were clearly mononucleates, as determined by analysis of serial sections, and were observed in 17 out of 23 animals implanted with labelled myofibers. We conclude that these cells readily undergo cellularisation in the environment of the limb blastema. Figure 2 Cellularisation of Striated Myofibers after Implantation into a Larval Limb Blastema (A) Schematic diagram of procedure. After dissociation of larval limb musculature, the cells were loaded with a cell tracker dye and single myofibers taken up into a suction micropipette, prior to injection into a larval limb blastema as detailed in the Materials and Methods. (B) Section of a limb at 48 h after implantation of CellTracker Orange-labelled myofibers. The section has been counterstained with the nuclear stain Sytox green. Note the dye-labelled mononucleate cells (arrowed). Scale bar, 20 μm. Plasticity in Culture After 48 h in culture, some of the striated fibers remained viable, but showed no significant change in morphology and retained the appearance of the cell shown in Figure 1. The remainder of the fibers showed various changes in morphology, and these were investigated either by microinjection of single fibers with the lineage tracer Texas red (TR)–dextran and subsequent analysis of the progeny cells or by sequential digital time-lapse observation. Cellularisation. Approximately 10% of the total population of myofibers underwent changes in nuclear localisation within the cells such that a lobulated or ‘cauliflower’ structure formed in the middle or end of the cell (Figure 3A and 3B). This occurred without labelling by tritiated thymidine or any participation by adherent mononucleate cells, which were rarely present on such fibers. The lobules, each of which contained a nucleus, were rapidly resolved into adherent mononucleate cells. In order to analyse these events, single myofibers were microinjected with TR–dextran so as to fill the cells with tracer (Figure 3C). We employed the 70 kDa dextran, which is not transferred across gap junctions (Coelho and Kosher 1991; Landesman et al. 2000). In cases in which fibers formed the cauliflower structure and underwent cellularisation, the mononucleate cells in the initial colony were labelled with the tracer in a rim of cytoplasm around the nucleus (Figure 3D). In some cases, adjacent fibers were injected and the progeny of the myofibers gave rise after 5–7 d to overlapping dense colonies with many labelled cells (Figure 3E). These cells did not express detectable levels of MHC after staining by indirect immunofluorescence. Figure 3 Plasticity of Isolated Myofibers (A) Phase-contrast micrograph of a live cell at 3 d after plating, showing a lobulated structure in the middle of the fiber. (B) Micrograph of a live fiber at 2 d after plating, showing budding of nuclei at one end. The cell has been counterstained with Syto 13. (C) Fluorescence micrograph of a myofiber at 24 h after microinjection with TR–dextran. The cell has been counterstained with Syto 13 dye to show the nuclei. (D) Fluorescence micrograph of a colony formed from a single myofiber injected 24 h earlier with TR–dextran. The cell has flattened on the substrate and the nuclei are stained with Syto 13 dye. (E) Fluorescence micrograph of a colony formed from the progeny of several myofibers in proximity that were injected 5 d earlier with TR–dextran. (F) Analysis of the DNA content of cells derived from myofibers injected 5 d earlier with TR–dextran. The DNA content was determined by image analysis of the nuclei of mononucleate TR-positive cells that had been stained with Hoechst (see Materials and Methods). The green arrow is the value for G0 nuclei in quiescent myofibers, while the blue arrow is the G2/M value determined for mononucleate cells with anti-phosphohistone H3. The red arrow is the G1 value determined for mononucleate cells. (G) Photomicrograph of a live myofiber, 48 h after plating, showing a binucleate bud formed at the end. The cell was stained as for (B). (H) Fluorescence micrograph of a bud containing three nuclei stained with Syto13 (yellow) derived from a myofiber that contained at least five nuclei and that was injected with TR–dextran (red). Scale bars: (B), (C), and (G), 100 μm; (A), (E), and (H), 50 μm; and (D), 10 μm. We have analysed the DNA content of single Hoechst-stained nuclei by normalised measurements of fluorescence intensity in TR-labelled cells within such colonies, and an example of a representative distribution for a single colony is shown in Figure 3F. This also shows the corresponding values (shown by arrows in Figure 3F) for G0 nuclei in myofibers, G1 nuclei in mononucleate cells, and G2/M nuclei in mononucleate cells labelled with antibody to phosphohistone H3. The histogram of DNA content for cells in the colony is comparable to that previously observed for cycling newt mononucleate cells (Tanaka et al. 1997). The relatively long S-phase in urodele cells leads to a prominent contribution of cells with DNA content between 2N and 4N. In addition, there were examples of TR-labelled mononucleate cells in M-phase, as determined with anti-phosphohistone H3. We conclude that the progeny mononucleate cells are able to traverse S-phase and enter mitosis after cellularisation. Fragmentation. In a second aspect of plasticity, which was shown by 40%–70% of the total population of myofibers, the initial stages also involved the migration of nuclei to form local aggregates, often of two or three nuclei, within the fiber. The migration of nuclei into a terminal aggregate is illustrated by selected images from a time-lapse video analysis (Figure 4A; Video S1). The series of Figure 4B illustrates a trinucleate terminal aggregate that fragments from the body of the myofiber (yellow arrows). This fragment remained adherent and extended cytoplasmic processes. In some cases, the nuclear aggregate formed a bud that was discharged into the medium. An example of a multinucleate bud formed at the end of a fiber is shown in Figure 3G. In cases in which fibers containing at least five nuclei had been injected with TR–dextran, such buds were often observed to adhere as viable bi- or trinucleate-labelled cells (see Figure 3H). The multinucleate progeny resulting from these processes did not label with tritiated thymidine or undergo division. Figure 4 Analysis of Nuclear Migration and Fragmentation by Time-Lapse Microscopy (A) Single frames illustrating the migration of three nuclei (yellow arrows) along a myofiber, of which two are incorporated into a terminal aggregate by 11.4 h. One nucleus (green arrow) remained stationary during this period. (B) Single frames illustrating the production of viable multinucleate fragments from a myofiber. Note the presence of a trinucleate aggregate (arrowed green) that separates after lateral breakage of the fiber (0 min, arrowed yellow). This fragment subsequently extends cytoplasmic processes (14.3 and 15.4 h) and migrates over the culture substratum. Series (A) and (B) begin at 6 h after plating. Scale bars: (A) 50 μm; (B) 200 μm. Inhibition by taxol. In view of the evidence that implicates microtubules as a target for myoseverin, we stained the cultures with antibody to β-tubulin. Although tubulin was polymerised in microtubules parallel to the axis of the fibers, the regions of nuclear aggregation were associated with depolymerised tubulin (Figure 5A). In order to assess the functional relevance of depolymerisation, we exposed the cultures to 2 μM taxol, an agent that stabilises microtubules and inhibits division of mononucleate urodele cells without effects on cell viability or adhesion of myofibers to the culture substrate. Whereas 80% of the control fibers showed the morphologies associated with plasticity, as described above (see Materials and Methods for the criteria), only 16% were observed in the case treated with taxol (Figure 5B), although the total number of adherent cells was unaffected. This suggests that localised depolymerisation of microtubules may be a significant target for the regulation of these responses. Figure 5 Plasticity and Microtubule Depolymerization (A) The distribution of microtubules surrounding a multinucleate aggregate on a myofiber, as analysed by staining with anti-β-tubulin. Note the relatively disordered state of the tubulin (arrowed) in the vicinity of the nuclei. The fiber was stained at 48 h after plating. Scale bar, 50 μm. (B) Taxol inhibits the activation of myofibers after dissociation. Myofibers were dissociated and cultured in the presence of taxol as described in the Materials and Methods. The number of active fibers was determined as described. Expression of Msx1 The cultures were reacted with a digoxygenin-substituted antisense riboprobe to axolotl Msx1. The mononucleate cells and inactive myofibers showed little or no reactivity, but active fibers showed strong reactivity with the probe in the vicinity of nuclear aggregations (Figure 6A and 6B). Several control probes were negative on both classes of fibers, while the quiescent fibers as well as the active ones were reactive to antisense probes to urodele EF1a and Nrad (Figure 6C). In view of the relationship between Msx1 expression and plasticity in mouse myotubes (Odelberg et al. 2000), the expression in the active fibers is suggestive of a role in the endogenous urodele programme. Figure 6 Analysis of mRNA Expression in Myofibers at 48 h by In Situ Hybridisation (A) Expression of Msx1 mRNA in active myofiber. Note the accumulation of reaction product around nuclear aggregates (arrowed). (B) Absence of significant Msx1 mRNA expression in a quiescent fiber. This image is taken from the same culture as (A). (C) Expression of NRad mRNA in nuclei of quiescent fibers (arrowed). Comparable intensity was observed for NRad expression by active fibers. (D) Expression of Msx1 mRNA in nuclei of fibers (arrowed) made quiescent by culture in taxol. Note the difference in Msx1 expression levels between the taxol-induced inactive fibers and normal quiescent myofibers in (B). Scale bar, 50 μm. In an initial investigation of this possibility, cultures were arrested as before by treatment with taxol, followed by reaction with the Msx1 antisense probe. In parallel control cultures, only 4.2% of the inactive fibers (n = 404) showed any reaction with the probe, whereas 51% of all myofibers (n = 820) showed reactivity. After treatment with taxol, 56.3% of inhibited fibers (n = 765) were positive, whereas 63% of all myofibers (n = 901) showed expression of Msx1. It is clear, therefore, that the arrest of nuclear mobilisation does not prevent the early expression of Msx1 in activated myofibers. These data are consistent with an upstream role for Msx1 in the activation of plasticity, but direct evidence for functional activity has come from antisense perturbation. Activity of Morpholino-Substituted Oligonucleotides In order to evaluate the uptake of morpholino-substituted oligonucleotides, larval myofibers were dissociated as usual in the presence of 10 μM biotinylated morpholinos or underivatised morpholinos. The cells were cultured for 48 h and then analysed by a detection procedure involving tyramide signal amplification (see Materials and Methods). Approximately 70%–90% of the fibers showed uptake of the biotinylated oligonucleotides in different experiments (Figure 7A), and no signal was detectable in the absence of oligonucleotide or with underivatised morpholinos (Figure 7B). The cells are thus effectively loaded by dissociation in the presence of morpholinos. Figure 7 Analysis of the Functional Role of Msx1 Expression by Exposure to Morpholino Antisense Oligonucleotides (A and B) Uptake of morpholino by myofibers. Myofibers were dissociated in the presence of biotinylated (A) or control (B) morpholinos and analysed by tyramide signal amplification at 24 h after plating. Note the positive signal in (A), dependent on the presence of biotin moiety. In three different experiments 70%–90% of the fibers were loaded as determined with this assay. Scale bar, 50 μm. (C) Functional effect of loading various morpholinos. Note that loading Msx1 antisense leads to a specific decrease in the proportion of active fibers relative to controls. (D–G) Staining of myofibers with antibody to Msx1 protein. (D and E) Fluorescence micrograph of a nucleus in a quiescent myofiber stained with Hoechst for DNA (D) and Msx1 protein (E). (F and G) Fluorescence micrograph of a nucleus in an active myofiber stained for DNA (F) and Msx1 protein (G). These images (D–G) were taken from the same culture. Scale bar, 20 μm. (H) Distribution of fluorescence intensity of nuclei in myofibers after staining with antibody to Msx1. The distributions for control active fibers and control quiescent fibers were determined for cells in the same culture and are significantly different (ANOVA, p < 0.001 at 95% confidence level). The distribution for antisense-treated quiescent fibers is not significantly different from that for control quiescent fibers. Limb tissue was dissociated in the presence of control morpholinos or a morpholino antisense reagent directed at the translation initiation sequence of axolotl Msx1. The resulting cultures were analysed in parallel for the proportion of active fibers and the antisense reagent reproducibly and specifically decreased this by 60%–70% (Figure 7C). This led, as expected from the mechanism of such reagents, to the presence of inhibited fibers that expressed Msx1 mRNA after in situ hybridisation, and the proportion of such Msx1 positive and inhibited cells was increased by 5-fold relative to parallel cultures incubated with control oligonucleotides. The myofiber cultures were stained by indirect immunofluorescence with a rabbit antibody to Msx1 in order to evaluate the level of expression of the homeoprotein in the nuclei. There was a significant difference is staining of nuclei between active and quiescent fibers in the same culture (Figure 7D–7G). The level of expression in nuclei of different fibers was estimated by quantitative image analysis, and the distribution of intensities is shown in Figure 7H. There was a significant difference in the fluorescence intensity of nuclei in active and quiescent fibers in control cultures (Figure 7H), consistent with the difference in mRNA levels observed by in situ hybridisation (see Figure 6A and 6B). The distribution of intensities for nuclei in quiescent fibers in parallel cultures treated with antisense oligonucleotides to Msx1 was not significantly different from the control quiescent distribution (Figure 7H). It should be noted that more than half of the quiescent fibers were inhibited as a result of the antisense treatment, thus indicating that the antisense distribution reflects a significant decrease in protein expression in the nucleus relative to active fibers. We conclude that expression of a critical level of Msx1 protein is necessary for the fibers to exhibit plasticity in this culture system. Discussion The plasticity of isolated urodele myofibers as described here has not been observed in previous work on dissociated mouse myofibers (Rosenblatt et al. 1995; Blaveri et al. 1999). These apparently retain their morphological identity in culture without undergoing viable fragmentation or cellularisation. In preliminary work on myofibers dissociated from the forelimb of Xenopus tadpoles (stages 56–63), we have observed fragmentation comparable to that described here for fibers of the larval salamander, but no cellularisation. It is possible, therefore, that there is a gradation in the degree of plasticity after dissociation, and this may be related to the ability to undergo reversal during regeneration, although more work is required to investigate these comparative issues. It is interesting that the mononucleate progeny of cellularisation were observed to reenter the cell cycle, while multinucleate fragments retained the postmitotic arrest of the parental fibers. At least half of the salamander fibers were activated after dissociation and could be scored by morphological criteria as an index of plasticity, as well as by analysis of gene expression in situ. The occurrence of cellularisation did not reflect the activation of adherent mononucleate cells since the injection of a nontransferable tracer into the fibers resulted in labelling of the mononucleate progeny, and furthermore the mobilisation of nuclear aggregates occurred without any detectable S-phase reentry. It is probable that the process of enzymatic and mechanical dissociation mimics the activation events after amputation, either in terms of mechanical factors sensed by the fibers or the release of signals from the tissue or matrix. Earlier experiments on microinjected fibers in the larval tail have explored the stimuli required to trigger cellularisation and concluded that activation apparently required both ‘clipping’ at the end of the fiber as well as tissue injury in the vicinity (Echeverri et al. 2001). It has also been reported that crude extracts from early regenerates of the adult newt limb are able to induce cellularisation of newt and mouse myotubes in culture (McGann et al. 2001). The precise nature of the signal(s) that couples tissue injury to activation of this response remains an important subject for future investigation, particularly as it may be a key difference between urodeles and mammals. One striking consequence of fiber activation is the appearance of the Msx1 transcript, and our work strongly supports the hypothesis that Msx1 is a pivotal regulator of plasticity in differentiated cells. Although taxol treatment is able to block the internal reorganisation in activated fibers, it does not inhibit the induction of Msx1, suggesting that microtubule depolymerisation, while being a direct target of myoseverin (Rosania et al. 2000), may also be a downstream target for regulation by Msx1. The striated myofibers are more highly differentiated than the newt A1 myotubes employed for implantation or the C2C12 mouse myotubes used to assay myoseverin and Msx1. The events of cellularisation, cleavage, or budding off from myofibers are preceded by migration of nuclei to generate local concentrations, reminiscent of the events leading to formation of the neuromuscular junction (Merlie and Sanes 1985; Englander and Rubin 1987), although mouse myotubes seem to undergo lateral breakage without such reorganisation (Rosania et al. 2000). This migration is inhibited by taxol, and nuclear migration in other contexts is dependent on microtubule function (Morris 2003). All of the events described for the myofibers occur without entry into S-phase, as determined previously for cellularisation of myotubes after implantation (Velloso et al. 2001). The formation of mononucleate cells is followed by rapid division and loss of myosin expression, and these cells are presumably the culture equivalent of muscle-derived blastemal cells. The activity of the Msx1 gene has recently been implicated in digit tip regeneration in fetal and neonatal mice by comparing regeneration in normal and Msx1 mutant animals (Reginelli et al. 1995; Han et al. 2003). It has also been shown that transgenic expression of an activated Msx1 protein can induce tail regeneration in larval Xenopus during the refractory period between stages 45 and 47 (Beck et al. 2003). This evidence, taken in conjunction with the present study and that of Odelberg et al. (2000), indicates that this gene is an important regulator of regeneration. Various activities have been associated with the protein, including a role as a repressor of transcription (reviewed in Bendall and Abate-Shen 2000), for example, of various myogenic differentiation genes in C2C12 myotubes (Odelberg et al. 2000) and also as a positive regulator of genes that promote cell cycling such as cyclin D (Hu et al. 2001). Our analysis of the myofiber cultures provides evidence for its ability to mobilise a postmitotic cell, for example, by nuclear migration and cellularisation, without S-phase reentry in the syncytium, and this suggests a different aspect of its activity as a regulator. Studies on mammalian myotubes should continue to be informative, while the present system, with its ready incorporation of antisense oligonucleotides, should be helpful for relating such studies to the endogenous programme of urodele regeneration. This in turn should assist the long-term goal of promoting the reversal of cellular differentiation as a strategy for mammalian regeneration (Chargé and Rudnicki 2004). Materials and Methods Tissue dissociation and culture of myofibers The forelimbs and hind limbs of the larval spotted salamander (A. maculatum) or axolotl (A. mexicanum) (3–5 cm size) were removed, the epidermis was peeled off, and the tissue was rinsed in serum-free amphibian MEM (AMEM) (Ferretti and Brockes 1988) prior to dissociation for 3 h at 26 °C in PBS containing 0.15% collagenase (Type 1A, Sigma, St. Louis, Missouri, United States), 0.8% Dispase II (Roche, Basel, Switzerland), 0.15% crystalline bovine serum albumin, 0.3% D-glucose, and 0.15 mg/ml DNase I (Roche). After 30 min of incubation, the tissues were gently triturated through a fire-polished glass pasteur pipette to aid the detachment of myofibers from the bone. After incubation, the suspension was triturated several times, centrifuged at 400 rpm for 10 min, resuspended in AMEM, and filtered through a 35 μm sieve (VWR International, Poole, United Kingdom) to remove most of the mononucleate cells. The retentate was rinsed with AMEM and plated on 35 mm Falcon Primaria (Becton-Dickinson, Palo Alto, California, United States) tissue culture dishes. Cultures were maintained at 25 °C with 2.5% CO2 in a humidified incubator as described elsewhere (Ferretti and Brockes 1988). After attachment of the myofibers to the culture dish by overnight incubation, the culture media was replaced with serum-free AMEM or AMEM supplemented with 10% foetal bovine serum. Labelling and implantation of myofibers Myofibers were dissociated as above, retained in suspension in a sterile bacteriological dish (Bibby Sterilin, Stone, United Kingdom), and incubated with 10 μM CellTracker Orange CMTMR (Molecular Probes, Eugene, Oregon, United States) for 30 min at 25 °C. The labelling was terminated by addition of 10% AMEM, and the cells were incubated for 45 min at 25 °C to permit enzymatic activation of the dye. The cell suspension was diluted several fold to allow observation of myofibers at low density. The forelimbs of axolotl larvae (7–10 cm size) were amputated at mid humerus level under tricaine (0.1%) anaesthesia 48 h before injection of labelled myofibers (see Figure 2A). The animals were anaesthetized, and the forelimbs were positioned under a stereo zoom microscope. The myofiber suspension was placed under inverted microscope, and the myofibers were drawn into a glass micropipette (30 μm tip diameter) using an oil-driven manual microinjector (Sutter Instruments, Novato, California, United States) mounted on a Narishige (Tokyo, Japan) MMO-1 micromanipulator. The skin was punctured with a tungsten needle in order to introduce the blunt end of the micropipette. Three to eight myofibers were picked, examined carefully to verify the absence of any adherent mononucleate cells, and injected into each limb regenerate. Contralateral limbs were mock injected with medium from the suspension. The regenerates were removed at 48 h and 96 h after injection, fixed in 4% paraformaldehyde (PFA), and processed (Kumar et al. 2000). Serial longitudinal sections of 60 μm were cut on a cryostat (Leica, Solms, Germany), air dried, dehydrated in PBS, and counterstained with 2.5 μM Sytox Green (Molecular Probes). The sections were observed under epifluorescence on an Axiophot microscope (Zeiss, Jena, Germany). Microinjection of cultured myofibers with conjugated dextran Myofibers were incubated in AMEM containing 2,3-butanedionne monoxime (BDM) (4 mM) for 30 min to prevent contraction of the myofibers (Bettencourt-Dias et al. 2003) and maintained in the same medium during microinjection. The culture dishes were placed under a Zeiss Axiovert microscope and microinjected with TR-conjugated dextran (TR–dextran, 70 kDa; Molecular Probes). The medium was changed immediately after injection and the cultures were returned to the incubator. To identify the labelled myofibers and their mononucleate progeny, cultures were counterstained in Syto13 (200 nM; Molecular Probes) live nucleic acid stain for 30 min and observed under fluorescence microscope with a dual band pass (FITC/TRITC) filter. Live imaging of myofiber plasticity To record the coordinates of the myofibers in culture, the dish was scored underneath with a scalpel, and cells in each grid square were observed daily and images were acquired with a CCD camera (Sony, Tokyo, Japan). For time-lapse microscopy, myofiber cultures were placed under an Axiovert microscope fitted with an incubation chamber maintained at 26 °C and 3% CO2, and phase contrast or variable relief contrast (VAREL) (Zeiss) images were acquired using a digital camera controlled through Image-Pro Plus software (Media Cybernetics, Silver Spring, Maryland, United States). A sequence gallery was created using Image Pro-Plus and images of interest were selected, digitally enhanced, and processed in Adobe Photoshop 6.0 (Adobe, San Jose, California, United States). [3H]thymidine labelling. Myofibers were incubated in 1 μCi/ml [3H] thymidine (Amersham Biosciences, Little Chalfont, United Kingdom) for 24 h, fixed in 1% glutaraldehyde, and processed for autoradiography (Velloso et al. 2000). DNA cytometry DNA content in myofiber nuclei and TR–dextran-labelled mononucleate progeny was measured quantitatively after fixation and staining of the nuclei with Hoechst 33258 (2 μg/ml; Sigma). Baseline values for nuclear DNA content in cycling axolotl mononucleate cells were measured in parallel after incorporation of 5-deoxy-2′-bromouridine (BrdU) (1 μM; see Tanaka et al. 1997). The BrdU-labelled cells were processed for double immunofluorescence with monoclonal antibody against BrdU and rabbit antibody to anti-phosphohistone H3 (Velloso et al. 2000; Bettencourt-Dias et al. 2003). The nuclei were counterstained with Hoechst dye as above. All images were acquired using 12-bit cooled CCD camera (Photonic Sciences, Robertsbridge, United Kingdom), maintaining camera and microscope settings identical between various samples, corrected for uneven illumination and background using software functions, and processed using classification and measuring routines in Image-Pro Plus software. Scoring of plasticity in myofibers A viable nucleic acid stain such as Syto 13 or Hoechst 33342 (Molecular Probes) was routinely used in cultures to visualize and score the myofibers. The quiescent or inactive myofiber nuclei were aligned along the fiber (see Figures 1 and 7D), and the cell did not show any cytoplasmic extensions from the axis. The nuclei in active fibers moved along the axis of the fiber to form aggregations that were localized either in the middle or towards the end of the cell (see Figure 3A, 3B, and 3G). In most cases, this resulted in formation of localised cytoplasmic protrusions in the vicinity of the nuclei. Myofibers were classified and counted based on the above criteria. Taxol inhibition assay. Dissociated myofibers were plated in medium containing taxol (2 μM; Sigma). Parallel control cultures were incubated in vehicle (DMSO) in a similar way. The cultures were fixed at 48 h after treatment and processed for tubulin immunofluorescence or in situ hybridisation. Functional assay for Msx-1 using morpholino antisense oligonucleotides Morpholino-based antisense oligonucleotides of 25 oligomere were prepared to target the translation initiation site of axolotl Msx1 gene (5′-CGGTCTGCATCCTCTGCTTGCTTAG-3′) by Gene Tools Inc. (Corvallis, Oregon, United States). Invert control oligos of Msx1 (5′-GATTGCTTCGTCTCCTAGCTCTGGC-3′) and standard control oligos (5′-CCTCTTACCTCAGTTACAATTTATA-3′) from the supplier were used as controls. 3′-Biotin-end-labelled standard control oligos were used for evaluating the uptake of morpholino oligonucleotides by myofibers. Oligo stock solutions were prepared according to guidelines from the manufacturer and stored at 4 °C. The morpholino oligos were added at a concentration of 10 μM to the dissociation cocktail and the myofibers were dissociated as described. After purification of myofibers, fresh morpholino oligos were added to the culture medium. After sequential washes to remove any adherent morpholino (McKeon et al. 2001), cultures were fixed at 48 h after treatment, prior to analysis. Detection of morpholino uptake by immunofluorescence. Tyramide signal amplification (PerkinElmer Life Sciences Inc., Wellesley, Massachusetts, United States) coupled with enzyme-linked immunofluorescence (ELF97, Molecular Probes) was employed to localize the uptake of morpholino oligos in cultured myofibers. Myofiber cultures were fixed at 48 h in 0.5% PFA containing 0.05% glutaraldehyde for 15 min on ice. The fixative was replaced with freshly made 0.1% NaBH4 solution and incubated for 5 min. The manufacturer's protocol was employed for TSA amplification with the ELF97 modification. The samples were developed in ELF reaction buffer under fluorescence microscope for 10–20 s and images were acquired using a cooled digital camera. In situ hybridisation The axolotl Msx1 cDNA (a kind gift from H. Ide, Tohoku University, Sendai, Japan) was cloned into Bluescribe vector (Stratagene, La Jolla, California, United States), and probes were generated as described elsewhere (Koshiba et al. 1998). A 0.7 kb axolotl EF-1α fragment (kindly provided by D. Gardiner and S. Bryant, University of California, Irvine, United States) was cloned into PCR II vector (Invitrogen, Carlsbad, California, United States) and linearised with XhoI (antisense), and a riboprobe was generated with SP6 RNA polymerase. Newt Rad (NRad, a gift from K. Yoshizato, Hiroshima University, Hiroshima, Japan) probe was generated from a fragment of approximately 400 bp from Bluescribe vector after linearising with either HindIII (antisense) or EcoRI (sense), and riboprobes were synthesized using T3 and T7 RNA polymerase respectively (Shimizu-Nishikawa et al. 2001). Axolotl EF1α and NRad probes were used as positive controls, while neomycin (Cash et al. 1998), NRad sense, and Msx1 sense probes served as negative controls. For in situ hybridisation, the myofiber cultures were incubated in BDM (4 mM), fixed in chilled 1% glutaraldehyde for 15 min, postfixed in 4% PFA, and washed in 0.3% PBT. In situ hybridisation was essentially as described elsewhere (Kumar et al. 2000), with minor modifications in the hybridisation temperature. Antibodies and immunofluorescence Myofiber cultures were routinely fixed in ice-cold 0.5% PFA containing 0.05% glutaraldehyde for 10 min on ice. For β-tubulin staining, 5 μM Taxol (Sigma) was incorporated into the fixative. After fixation, the culture was treated with freshly prepared 0.1% NaBH4 for 5 min to reduce nonspecific fluorescence. The samples were post-fixed in ice-cold methanol at −20 °C for 10 min, washed three to four times in 0.3% PBT, and blocked in PBT containing 10% goat serum. The primary antibodies were to MHC and titin, and BrdU monoclonal antibody and rabbit polyclonal antibodies to phosphohistone H3, were all as described elsewhere (Tanaka et al. 1997; Kumar et al. 2000; Velloso et al. 2000; Bettencourt-Dias et al. 2003). For localisation of β-tubulin, the culture was fixed and washed overnight in 0.3% PBT and incubated with mouse monoclonal β-tubulin antibody (1:100; clone TUB 2.1; Sigma) overnight at 4 °C. The samples were washed extensively in GS/PBT and incubated in TR-conjugated goat anti-mouse antibody (1 μg/ml; Molecular Probes). The nuclei were counterstained with Hoechst 33258 (2 μg/ml). A rabbit polyclonal antibody raised against the full-length mouse Msx1 homeoprotein was used to detect expression of Msx1 protein (BAbCO, Richmond, California, United States). When a full-length expression construct of axolotl Msx1 was expressed in mouse cells by transient transfection, the antibody gave strong and specific staining of nuclei in transfected cells (Figure S2). The samples were fixed and processed as before and incubated with Msx1 antibody (1:1000) overnight at 4 °C. After several washes, the cultures were incubated with FITC-conjugated goat anti-rabbit antibodies (1:100; DakoCytomation, Cambridgeshire, United Kingdom), and the nuclei were counterstained with Hoechst. A control rabbit polyclonal antibody was processed in parallel to obtain a baseline value for quantitative fluorescence measurements on immunostained nuclei. The myofiber cultures stained for β-tubulin, MHC, or titin, or cultures injected with TR–dextran were observed under confocal laser scanning microscope (Leica). The images were acquired as z-stacks, and composite maximum projection images were generated through Leica software. Samples stained for Msx1 protein were observed under a Zeiss Axioplan microscope and images were acquired with an Axiocam digital camera. The fluorescence intensity in myofiber nuclei was measured in Axiovision software (Zeiss), and the data were analysed by one-way analysis of variance (ANOVA) followed by multiple range test using Instat (Graphpad Software Inc., San Diego, California, United States). Supporting Information Figure S1 Live Striated Myofiber Dissociated from the Limb of a Larval Salamander The myonuclei incorporate Syto13 live nuclear stain. The myofiber was observed with VAREL optics at 24 h after plating. Scale bar, 100 μm. (4.1 MB TIF). Click here for additional data file. Figure S2 Expression of Newt Msx1 in Mouse PS Cells by Transient Transfection Nuclear localisation of Msx1 protein (green) was detected with a rabbit polyclonal antibody generated against the full-length mouse Msx1 homeoprotein. (5.6 MB TIF). Click here for additional data file. Video S1 Time-Lapse Video Analysis of Nuclear Migration in a Myofiber Time-lapse sequence was begun 6 h after plating of the myofiber on to a culture dish. The images were taken at 6 min intervals under 32× VAREL objective magnification. (110 KB AVI). Click here for additional data file. We thank Phillip Gates for plasmid construction, Tim Landy and Karel Liem for comments and suggestions on the manuscript, and Daniel Ciantar (Confocal Unit, Department of Anatomy, University College London) for his help. This work was funded by a Programme Grant from the Medical Research Council to JPB. Conflicts of interest. The authors have declared that no conflicts of interest exist. Author contributions. AK and JPB conceived and designed the experiments. AK, CV, and YI performed the experiments. AK, CV, YI, and JPB analyzed the data. CV, YI, and JPB contributed reagents/materials/analysis tools. AK and JPB wrote the paper. Academic Editor: Brigid Hogan, Duke University Medical Center Citation: Kumar A, Velloso CP, Imokawa Y, Brockes JP (2004) The regenerative plasticity of isolated urodele myofibers and its dependence on Msx1. PLoS Biol 2(8): e218 Abbreviations AMEMamphibian minimum essential medium ANOVAanalysis of variance BDM2,3-butanedionne monoxime BrdU5-deoxy-2′-bromouridine MHCmyosin heavy chain PFAparaformaldehyde TRTexas red-conjugated dextran VARELvariable relief contrast ==== Refs References Akimenko MA Johnson SL Westerfield M Ekker M Differential induction of four msx homeobox genes during fin development and regeneration in zebrafish Development 1995 121 347 357 7768177 Beck CW Christen B Slack JM Molecular pathways needed for regeneration of spinal cord and muscle in a vertebrate Dev Cell 2003 5 429 439 12967562 Bendall AJ Abate-Shen C Roles for Msx and Dlx homeoproteins in vertebrate development Gene 2000 247 17 31 10773441 Bendall AJ Ding J Hu G Shen MM Abate-Shen C Msx1 antagonizes the myogenic activity of Pax3 in migrating limb muscle precursors Development 1999 126 4965 4976 10529415 Bettencourt-Dias M Mittnacht S Brockes JP Heterogeneous proliferative potential in regenerative adult newt cardiomyocytes J Cell Sci 2003 116 4001 4009 12928330 Blaveri K Heslop L Yu DS Rosenblatt JD Gross JG Patterns of repair of dystrophic mouse muscle: Studies on isolated fibers Dev Dyn 1999 216 244 256 10590476 Brockes JP Amphibian limb regeneration: Rebuilding a complex structure Science 1997 276 81 87 9082990 Brockes JP Kumar A Plasticity and reprogramming of differentiated cells in amphibian regeneration Nat Rev Mol Cell Biol 2002 3 566 574 12154368 Carlson MR Bryant SV Gardiner DM Expression of Msx-2 during development, regeneration, and wound healing in axolotl limbs J Exp Zool 1998 282 715 723 9846383 Cash DE Gates PB Imokawa Y Brockes JP Identification of newt connective tissue growth factor as a target of retinoid regulation in limb blastemal cells Gene 1998 222 119 124 9813273 Chargé SB Rudnicki MA Cellular and molecular regulation of muscle regeneration Physiol Rev 2004 84 209 238 14715915 Coelho CN Kosher RA A gradient of gap junctional communication along the 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New York Academic Press 287 Han M Yang X Farrington JE Muneoka K Digit regeneration is regulated by Msx1 and BMP4 in fetal mice Development 2003 130 5123 5132 12944425 Hay ED Electron microscopic observations of muscle dedifferentiation in regenerating Amblystoma limbs Dev Biol 1959 1 555 585 Hu G Lee H Price SM Shen MM Abate-Shen C Msx homeobox genes inhibit differentiation through upregulation of cyclin D1 Development 2001 128 2373 2384 11493556 Imokawa Y Brockes JP Selective activation of thrombin is a critical determinant for vertebrate lens regeneration Curr Biol 2003 13 877 881 12747839 Imokawa Y Simon A Brockes JP A critical role for thrombin in vertebrate lens regeneration Phil Trans Roy Soc B 2004 359 765 776 15293804 Koshiba K Kuroiwa A Yamamoto H Tamura K Ide H Expression of Msx genes in regenerating and developing limbs of axolotl J Exp Zool 1998 282 703 714 9846382 Kumar A Velloso CP Imokawa Y Brockes JP Plasticity of retrovirus-labelled myotubes in the newt limb regeneration blastema Dev Biol 2000 218 125 136 10656757 Landesman Y Goodenough DA Paul DL Gap junctional communication in the early Xenopus embryo J Cell Biol 2000 150 929 936 10953017 Lo DC Allen F Brockes JP Reversal of muscle differentiation during urodele limb regeneration Proc Natl Acad Sci U S A 1993 90 7230 7234 8346239 McGann CJ Odelberg SJ Keating MT Mammalian myotube dedifferentiation induced by newt regeneration extract Proc Natl Acad Sci U S A 2001 98 13699 13704 11717431 McKeon J Cho MJ Khaledi MG Quantitation of intracellular concentration of a delivered morpholino oligomer by capillary electrophoresis-laser-induced fluorescence: Correlation with upregulation of luciferase gene expression Anal Biochem 2001 293 1 7 11373071 Merlie JP Sanes JR Concentration of acetylcholine receptor mRNA in synaptic regions of adult muscle fibres Nature 1985 317 66 68 3839905 Morris NR Nuclear positioning: The means is at the ends Curr Opin Cell Biol 2003 15 54 59 12517704 Nechiporuk A Keating MT A proliferation gradient between proximal and msxb -expressing distal blastema directs zebrafish fin regeneration Development 2002 129 2607 2617 12015289 Nye HL Cameron JA Chernoff EA Stocum DL Regeneration of the urodele limb: A review Dev Dyn 2003 226 280 294 12557206 Oberpriller JO Oberpriller JC Response of the adult newt ventricle to injury J Exp Zool 1974 187 249 253 4813417 Oberpriller JO Oberpriller JC Matz DG Soonpaa MH Stimulation of proliferative events in the adult amphibian cardiac myocyte Ann N Y Acad Sci 1995 752 30 46 7755274 Odelberg SJ Inducing cellular dedifferentiation: A potential method for enhancing endogenous regeneration in mammals Semin Cell Dev Biol 2002 13 335 343 12324215 Odelberg SJ Kollhoff A Keating MT Dedifferentiation of mammalian myotubes induced by msx1 Cell 2000 103 1099 1109 11163185 Okada TS Transdifferentiation 1991 Oxford Clarendon Press 238 Popiela H Muscle satellite cells in urodele amphibians: Faciliatated identification of satellite cells using ruthenium red staining J Exp Zool 1976 198 57 64 978162 Raya A Koth CM Buscher D Kawakami Y Itoh T Activation of Notch signaling pathway precedes heart regeneration in zebrafish Proc Natl Acad Sci U S A 2003 100 Suppl 1 11889 11895 12909711 Reginelli AD Wang YQ Sassoon D Muneoka K Digit tip regeneration correlates with regions of Msx1 (Hox 7) expression in fetal and newborn mice Development 1995 121 1065 1076 7538067 Rosania GR Chang YT Perez O Sutherlin D Dong H Myoseverin, a microtubule-binding molecule with novel cellular effects Nat Biotechnol 2000 18 304 308 10700146 Rosenblatt JD Lunt AI Parry DJ Partridge TA Culturing satellite cells from living single muscle fiber explants In Vitro Cell Dev Biol Anim 1995 31 773 779 8564066 Shimizu-Nishikawa K Tsuji S Yoshizato K Identification and characterization of newt rad (ras associated with diabetes), a gene specifically expressed in regenerating limb muscle Dev Dyn 2001 220 74 86 11146509 Simon A Brockes JP Thrombin activation of S-phase reentry by cultured pigmented epithelial cells of adult newt iris Exp Cell Res 2002 281 101 106 12441133 Tanaka EM Regeneration: If they can do it, why can't we? Cell 2003 113 559 562 12787496 Tanaka EM Gann AA Gates PB Brockes JP Newt myotubes reenter the cell cycle by phosphorylation of the retinoblastoma protein J Cell Biol 1997 136 155 165 9008710 Tanaka EM Drechsel DN Brockes JP Thrombin regulates S-phase reentry by cultured newt myotubes Curr Biol 1999 9 792 799 10469562 Thornton CS The histogenesis of muscle in the regenerating forelimb of larval Ambystoma punctatum J Morphol 1938 62 219 235 Velloso CP Kumar A Tanaka EM Brockes JP Generation of mononucleate cells from postmitotic myotubes proceeds in the absence of cell cycle progression Differentiation 2000 66 239 246 11269950 Velloso CP Simon A Brockes JP Mammalian postmitotic nuclei reenter the cell cycle after serum stimulation in newt/mouse hybrid myotubes Curr Biol 2001 11 855 858 11516646

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020219Research ArticleDevelopmentGenetics/Genomics/Gene TherapyNeuroscienceMus (Mouse)A Focused and Efficient Genetic Screening Strategy in the Mouse: Identification of Mutations That Disrupt Cortical Development A Screen for Cortical Development MutantsZarbalis Konstantinos 1 May Scott R 1 Shen Yiguo 1 Ekker Marc 2 Rubenstein John L. R 3 Peterson Andrew S andpete@itsa.ucsf.edu 1 1Department of Neurology and the Ernest Gallo Clinic and Research Center, University of California at San FranciscoEmeryville, California, United States of America2Loeb Medical Research Institute, University of OttawaOttawa, Ontario, Canada3Nina Ireland Laboratory of Developmental Neurobiology, Department of PsychiatryLangley Porter Psychiatric Institute, University of California at San Francisco, San Francisco, CaliforniaUnited States of America8 2004 17 8 2004 17 8 2004 2 8 e21917 2 2004 13 5 2004 Copyright: © 2004 Zarbalis et al.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. Finding Mutations that Disrupt Cortical Development Although the mechanisms that regulate development of the cerebral cortex have begun to emerge, in large part through the analysis of mutant mice (Boncinelli et al. 2000; Molnar and Hannan 2000; Walsh and Goffinet 2000), many questions remain unanswered. To provide resources for further dissecting cortical development, we have carried out a focused screen for recessive mutations that disrupt cortical development. One aim of the screen was to identify mutants that disrupt the tangential migration of interneurons into the cortex. At the same time, we also screened for mutations that altered the growth or morphology of the cerebral cortex. We report here the identification of thirteen mutants with defects in aspects of cortical development ranging from the establishment of epithelial polarity to the invasion of thalamocortical axons. Among the collection are three novel alleles of genes for which mutant alleles had already been used to explore forebrain development, and four mutants with defects in interneuron migration. The mutants that we describe here will aid in deciphering the molecules and mechanisms that regulate cortical development. Our results also highlight the utility of focused screens in the mouse, in addition to the large-scale and broadly targeted screens that are being carried out at mutagenesis centers. A novel screen uncovers thirteen mutants with defects ranging from the establishment of epithelial polarity in the cortex to the invasion of axons from the thalamus ==== Body Introduction The cerebral cortex is the seat of consciousness and the means by which we carry out abstract reasoning. Understanding how the cortex is assembled during embryonic development will give deeper insights into how this marvelous machine functions and provide the basis for therapy and repair. Although a diversity of approaches will be needed to answer all of our questions, an important starting point in studying events in development is often the careful analysis of mutant phenotypes. Much of what we know about cortical development has emerged through the study of mutations in mice and humans. For example, spontaneous mutations in mice such as reeler and scrambler have helped to tease apart the regulation of the radial migrations that create the cortical layers. Other important insights have come from the study of spontaneous mutations that cause radial migration defects and lead to lissencephaly and similar cortical defects in humans. Our understanding of radial migration and many other aspects of cortical development have also benefited enormously from the application of gene knockout approaches in mice. Despite this progress, many aspects of cortical development remain to be explored and would benefit enormously from additional mutant resources. The tangential migrations of cortical interneurons, for example, are regulated differently from the radial migrations of projection neurons, and only a few mutations have been described that disrupt interneuron migration. Forward genetic approaches in the mouse, although technically feasible for many years, have become increasingly attractive with the availability of a dense genetic map and a nearly complete genomic sequence. These tools allow the process of gene identification, which was once very cumbersome, to be relatively straightforward. With the initial resurgence of interest in genetic screens, large-scale screens aimed at identifying mutations in broadly defined phenotypic categories were established at mutagenesis centers in Germany, the United Kingdom, the United States, and other countries (Hrabe de Angelis et al. 2000; Nolan et al. 2000). More recently, smaller, more focused screening efforts have had notable success (Vitaterna et al. 1994; Eggenschwiler et al. 2001; Kapfhamer et al. 2002; Garcia-Garcia and Anderson 2003; Hoebe et al. 2003), generally in situations where the effects of mutation on a specific cellular or biochemical process can be readily ascertained. Further development of forward genetics in the mouse as an approach with general utility will require the validation of focused screening strategies that allow for the identification of mutations disrupting specific processes in diverse situations, as has been done in other model organisms. In Drosophila, deletion strains and chromosomal inversions have been used to identify mutations within a specific region of the genome, and this approach has been elegantly adapted for use in the mouse (Juriloff et al. 1985; Kile et al. 2003). The development of screening strategies for the mouse that focus on the identification of mutations affecting a biological process rather than mapping to a certain genomic region will further expand the questions that can be addressed. Here we describe a focused genetic screen in the mouse that takes advantage of a transgenic reporter line that labels the ganglionic eminences of the ventral forebrain and migrating cortical interneurons with β-galactosidase. The use of this reporter gene allows the isolation of mutations that alter growth and morphogenesis of the cortex very efficiently and, more specifically, allows the identification of mutations disrupting interneuron migration from the ganglionic eminences into the cortex. In this screen, we isolated four mutations that affect tangential migration. We also isolated nine novel mutations affecting other aspects of cortical development; these mutations include three that represent novel alleles of genes that have been shown to have a role in cortical development. These results illustrate the power of a forward genetic approach, borrowed from other model organisms, that can be applied to various questions of mammalian biology. Results The Dlx-LacZ Transgene Labels the Ganglionic Eminences and Migrating Interneurons The expression of Dlx family homeodomain transcription factors is necessary for differentiation of neurons in the striatum and for migration of many, if not all, of the interneuron precursors that arise in the ganglionic eminences of the embryonic telencephalon (Marin and Rubenstein 2001, 2003). A transgenic line in which the expression of β-galactosidase is driven by transcriptional control sequences from the Dlx5/6 intergenic region faithfully recapitulates most aspects of Dlx5 expression in the central nervous system, including strong expression in the subventricular zone (SVZ; a secondary progenitor zone) of the ganglionic eminences, in immature interneurons as they migrate tangentially through the intermediate zone (IZ) or marginal zone (MZ) of the cortex (Figure 1A–1C), and in mature cortical GABAergic interneurons (Stuhmer et al. 2002). The dispersed interneuron precursors label the cerebral cortex, and the underlying high-level expression in the ganglionic eminences provides a useful adjunct to the morphological landmarks, allowing cortical defects to be identified in whole-mount stained embryos. We took advantage of the Dlx-LacZ line as a background upon which to screen for mutations. Mutations were induced using ethyl-nitroso-urea (ENU), a mutagen that induces primarily single-base substitutions with very little bias (Russell et al. 1979; Vrieling et al. 1988; Nivard et al. 1992), and animals were bred in order to detect recessive mutations that disrupted the distribution of Dlx-LacZ–labeled cells in the developing cortex at embryonic day 14.5 (E14.5) (Figure 1D). In total, 705 litters with an average of seven embryos each, and representing 305 lines of mice, were stained using β-galactosidase histochemistry, and then examined in whole mount; higher-resolution analysis on 100-μm coronal vibratome sections of brains was also performed on a third (225) of the litters. Figure 1 The Strategy for Isolation of Recessive Mutations Disrupting Cortical Development (A) Migrating interneuron precursors appear to migrate tangentially (yellow arrows) through both the MZ and the IZ/SVZ. Precursors also migrate radially (pink arrows) to reach the developing cortical plate (CP). (B) Migrating interneuron precursors expressing β-galactosidase can be seen in a whole-mount preparation of an E14.5 Dlx-LacZ mouse as diffuse cortical staining. (C) In coronal section, the densely labeled SVZ of the LGE can be seen, as can the streams of migrating interneuron precursors in the cortex. (D) To identify recessive mutations, male C57BL6/J mice were treated with ENU and then crossed to FVBN/J females that were homozygous for the Dlx-LacZ transgene. Male offspring of this cross were backcrossed to produce female offspring that were then backcrossed to their fathers. Embryonic litters from these backcrosses were stained and examined for defects at E13.5 or E14.5. Dlx-LacZ Allows Efficient Identification of Cortical Mutants During the course of screening we identified eight mutants with defective growth or patterning of the cerebral cortex, four mutants with defects in the migration of interneuron precursors into the cortex, and one mutant in which thalamocortical axons fail to invade the cortex (Table 1). Lines of mice carrying each mutation were established, in which the phenotype was propagated as a recessive trait with Mendelian inheritance. Preliminary mapping, together with the overt phenotype, pointed us toward a likely locus for three of the mutants (Figure 2). The other ten mutations appear to identify loci whose role in forebrain development has not previously been described. Figure 2 Novel Alleles of scribble, megalin, and Rfx4 (A and B) Comparison of E12.5 WT (A) and mutant (B) embryos showing the severe craniorachischisis of line 90 embryos. (C) Sequencing chromatograms show the thymine in the WT sequence (top) that is an adenine in line 90 (bottom). This thymine-to-adenine substitution changes an isoleucine codon to a lysine codon within a conserved LRR domain of SCRIBBLE. (D and E) Ribbon diagrams of an LRR fold, illustrating the predicted position (red arrowheads) of the line 90 amino acid substitution. The substitution is in a linker region between two stretches of β-sheet. An LRR fold has a β-sheet on the inside, and linker regions on the outside, of a broad half-circular curve. (F) The predicted domain structure of SCRIBBLE indicating where the line 90 and the Circletail alleles alter the protein relative to the three LRR and four PDZ domains. (G and H) Dorsal views of the cortex of E17.5 WT (G) and line 267 mutant (H) embryos stained to reveal the expression of the Dlx-LacZ transgene. The red arrowheads point to the choroid plexus of the third ventricle, which is stained because of its endogenous β-galactosidase expression, and which is greatly enlarged in the mutant. The cortex of the mutant is longer along the rostrocaudal axis and is altered in shape in the caudal portion (yellow arrows). The olfactory bulbs (blue arrowheads) are also altered in shape. (I) The choroid plexus persists in its hypertrophic state after birth and can be seen as a pinkish lump on the head of this postnatal day 14 (P14) pup. (J) A coronal section through the dorsal portion of the diencephalon of a P0 pup. (K) Sequencing chromatograms show the thymine in the WT sequence (top) that is an adenine in line 267 (bottom). (L) The predicted domain structure of MEGALIN indicating where the new stop codon is introduced by the line 267 mutation. (M and N) Dorsal views of the cerebral cortex of E14.5 WT (M) and line 269 mutant (N) embryos stained to reveal the expression of the Dlx-LacZ transgene. (O and P) Coronal sections of E14.5 WT (O) and line 269 mutant (P) forebrains. Red arrowheads indicate the apparent span over which dorsal midline structures are lost in the mutant. (Q) Sequence chromatograms showing the thymine in the WT sequence (top) that is a cytosine in line 269 (bottom). (R) The predicted domain structure of RFX4 indicating where the line 269 substitution alters the protein relative to the DNA binding and the extended (B, C, and Dim) dimerization domains. Table 1 Summary of Cortical Mutants a See supporting information b Scored on the basis of polydactyly c These two mutants fail to complement and are likely to be allelic d Scored on the basis of migration defects e These two mutants have very different phenotypes. Since the interval is large the two mutants seem likely to represent two different genes A Novel scribble Allele The three mutations in previously characterized loci produce alleles that differ from the existing ones in informative ways (Figure 2). Mice homozygous for the line 90 mutation have an open neural tube in the spinal cord and hindbrain region, or craniorachischisis, and a disorganized and hyperplastic neuroepithelium in the cortex and other parts of the central nervous system (Figure 2A and 2B). An essentially identical phenotype is seen in homozygous Loop-tail and Circletail mutants (Kibar et al. 2001; Murdoch et al. 2001a, 2001b, 2003), both of which also have dominant tail defects, a phenotype that is not seen in line 90. Both Loop-tail and Circletail mice have mutations in genes that regulate planar cell polarity. Loop-tail mice carry a mutation in the strabismus-1 gene (Str-1, also known as Ltap/Lpp1), and Circletail mice have a mutation in the scribble gene (Scrb1). Mapping of the line 90 mutation places it on Chromosome 15 in the region of Scrb1. Scrb1 encodes a protein of 1,665 amino acids with three leucine-rich repeat (LRR) domains near the amino terminus and four centrally located PDZ domains (Figure 2F). Sequencing of RT-PCR products from line 90 mice identified a missense mutation in Scrb1 that causes an isoleucine-to-lysine substitution in the third LRR domain (Figure 2C–2F). In Drosophila, a critical role for a Scrb1 homolog, scribbled, in establishment of apical basal polarity in epithelia has been described (Bilder and Perrimon 2000; Bilder et al. 2000, 2003). Analysis of mice carrying the Circletail allele of Scrb1 show a loss of planar cell polarity in the hair cells of the inner ear, indicating that Scrb1 is required for the establishment of planar cell polarity rather than apical-basal polarity in the mouse (Montcouquiol et al. 2003). Interestingly, a strong genetic interaction has been observed between the Circletail allele of Scrb1 and Loop-tail mutants (Murdoch et al. 2001b). The interaction is strong enough that compound heterozygotes for the two mutations show a severe phenotype that is indistinguishable from the individual homozygous phenotypes. The molecular nature of the Circletail allele of Scrb1, with a frameshift mutation that causes a premature stop codon after the first two PDZ domains (Murdoch et al. 2003), is substantially different from that of line 90. To see whether interaction between the two loci was a unique attribute of the Circletail allele, we crossed line 90 with Loop-tail mice. As with the Circletail allele, a strong genetic interaction was seen between the line 90 allele of Scrb1 and the Ltap/Lpp1 mutation, such that embryos indistinguishable from homozygotes of the individual mutations were recovered (unpublished data). This indicates quite clearly that the integrity of the LRR domains is critical for the tight coordination between Scrb1 and Ltap/Lpp1 in establishment of planar cell polarity. A Novel megalin Allele We also identified a mutation that caused an enlarged cortex, hypertrophy of the choroid plexus of the third ventricle, and abnormalities in the dorsal diencephalon (Figure 2G–2J). Mapping of this mutation places it on Chromosome 2 in a region containing the megalin gene (also known as Lrp2). Prolapse of the third ventricle choroid plexus was described in a knockout allele of megalin (Willnow et al. 1996), suggesting that this might be the responsible locus in this case. On this basis we sequenced RT-PCR products from the megalin gene and identified a base substitution producing a premature stop codon rather than the tyrosine codon at residue 2721 (Figure 2K and 2L). The ENU-induced allele is predicted to express a truncated MEGALIN protein consisting of the amino-terminal portion of the extracellular domain, whereas the knockout is a null. Unlike the case of Scrb1, where the phenotypes produced by the two alleles are essentially identical, the two megalin alleles show phenotypic differences. Although both alleles produce a hypertrophic choroid plexus, this defect is more pronounced with the ENU-induced allele. We have found that the choroid plexus defects are also associated with an expansion and inhibition of differentiation in the dorsal neuroepithelium of the diencephalon that would ordinarily form the subcommissural organ and of the pineal gland just caudal to the defective choroid plexus (see Figure 2I–2J; A. Ashique, unpublished data). It is not possible to say from the published characterization of the knockout allele whether a similar condition occurs there, but it is clear that the knockout allele causes holoprosencephaly (Willnow et al. 1996), a phenotype that we have not seen in line 267. Indeed, the ENU-induced allele causes an enlarged cortex (Figure 2G and 2H) without any obvious deficiency of midline structures such as would be expected in even mild holoprosencephaly. A Novel Rfx4 Allele A morphologically identifiable dorsal midline is absent from the cerebral cortex of line 269 homozygotes (Figure 2M–2P). This is an unusual defect that is similar to that seen in a transgene insertion mutation that disrupts the Rfx4 gene (Blackshear et al. 2003). The line 269 mutation was mapped to Chromosome 10 in the region containing Rfx4. Sequencing of Rfx4 revealed a base substitution that changes an evolutionarily conserved leucine residue to proline (Figure 2Q and 2R). RFX4 is a member of the Rfx subfamily of winged-helix transcription factors (Emery et al. 1996) and can form dimers with two of the other family members, RFX2 and RFX3 (Morotomi-Yano et al. 2002). The amino acid substitution affects the conserved C domain of RFX4's large dimerization domain (Katan-Khaykovich et al. 1999). The transgene insertion mutation, on the other hand, selectively eliminates the expression of a neural-specific transcript of the gene, and so behaves as a tissue-specific null (Blackshear et al. 2003). Dimerization is not necessary for DNA binding activity of Rfx-class transcription factors (Katan et al. 1997; Katan-Khaykovich and Shaul 1998). Instead, dimerization appears to determine whether the bound transcription factor mediates transcriptional activation or repression. The fact that the line 269 allele produces a phenotype that is apparently identical to that of a null allele provides clear evidence that RFX4-containing dimers regulate important transcriptional regulatory events during formation of the cortical midline. Dlx-LacZ Allows Efficient Identification of Tangential Migration Mutants Four mutants were identified in which the morphology of the cortex was normal at E14.5, but in which the distribution of LacZ-expressing cells in the cortex was altered. Three mutants, 154, 239, and 275, were identified on the basis of defects that are apparent in whole-mount preparations. Defects in the fourth mutant, 251, were only apparent upon examining sections. All four mutations are, for unknown reasons, perinatal lethal when homozygous, and this has prevented us from analyzing adult phenotypes. In addition, the line 154, 239, and 275 mutations appear to cause an increase in spontaneous seizures and mortality in young adult heterozygotes. Because the seizures are sporadic, their basis has not yet been studied. Line 154 has the most severe defects. Affected embryos often have fewer labeled cells in the cortex except in the most rostral regions, where they form abnormal aggregates (Figure 3A and 3B). Abnormalities in the LacZ expression pattern that are associated with the failure of cells to invade the developing cortex can also be found in the subcortical telencephalon of line 154 embryos (Figure 3C–3H). Here, prominent, radially oriented columns of cells form near or at boundaries between subcortical subdivisions: the dorsal LGE, the ventral LGE, and the medial ganglionic eminence. To confirm that the abnormal pattern of LacZ expression was due to a perturbation in the distribution of interneurons in the cortex and not the result of ectopic expression of the transgene, we examined the expression of an interneuron marker, glutamic acid decarboxylase 1 (Gad67). Interneurons are GABAergic and so express GAD67, an enzyme involved in GABA synthesis. Glutamatergic projection neurons do not express GAD67. Whole-mount in situ analysis of GAD67 at E15.5 showed that the distribution of interneurons was abnormal, as predicted by the aberrant expression of the transgene (Figure 3I and 3J). Figure 3 Severe Disruption of Interneuron Migration in Line 154 Mutants (A) Disseminated immature interneurons are seen as diffuse cortical (Cx) staining in WT embryos. Subcortical expression in the SVZ of the LGE can be seen as a darkly stained, inverted crescent. (B) Embryos homozygous for the line 154 mutation have little or no cortical staining, and the subcortical staining has aberrant streaks (pink arrowheads) and spots (white arrowhead), particularly in the frontal cortex. (C, E, and G) In this rostral-to-caudal series of coronal sections from WT embryos, the normal MZ and IZ/SVZ migratory streams are diffusely labeled (red arrowheads), and a sharp cortical-subcortical boundary (black arrowheads) is marked by the abrupt transition between the densely stained SVZ of the LGE and the diffuse staining of the migrating interneuron precursors. (D, F, and H) A rostral-to-caudal series of coronal sections from a line 154 mutant embryo shows the rostral spots (white arrowheads) visible in whole mount to be aggregates of cells in the cortex, and the streaky subcortical staining to be radially directed linear aggregates (pink arrowheads). The SVZ of the LGE is also noticeably thinner, and there is not a well-defined cortical-subcortical transition in the staining pattern. (I and J) Rostral views of Gad67 whole-mount in situ hybridization show the pattern of migration abnormalities in the cortex and significant defects in population of the olfactory bulb by GABAergic neurons. Three Migration Mutants Have Defects in a Common Process Lines 239, 251, and 275 share features that suggest that the loci involved may have roles in a common regulatory process. All three mutations produce defects that are most apparent in the rostral cortex at E14.5, and all three cause anterior polydactyly (Figure 4A–4C; unpublished data). The limb defects might be only superficially similar or they could have a common developmental basis. If the latter explanation were true, it would strongly suggest that the neuronal migration phenotypes of the three mutants are similar because the same regulatory mechanism is defective in all of them. Initial mapping uncovered linkage to Chromosome 7 for the line 251 mutation and to Chromosome 10 for the other two, indicating that at least two distinct loci are involved (Table 1). To determine the number of loci involved, complementation tests were carried out using crosses between all three lines. The line 251 mutation complemented the other two as expected, but crosses between line 239 and line 275 produced mutant embryos with both limb and forebrain defects that were indistinguishable from either parental line. Further study will be required to determine whether the two lines carry the same or two independent mutations. Figure 4 Limb Patterning Defects in Tangential Migration Mutants Anterior is to the right for all limbs. (A–C) Left hindlimbs are shown from E14.5 WT (A), line 251 (B), and line 239 (C). Yellow arrowheads point to extra digits on the anterior (thumb) side of the limb in mutants. Line 275 mutants also have anterior polydactyly. The mutants have a slight developmental delay that causes some differences in appearance of the limb buds at E14.5, when the limbs are growing rapidly. (D) This diagram illustrates components of the Shh/Fgf feedback loop that maintains Fgf4 expression in the AER. (E–J) In situ hybridization on E11.5 limb buds. Unlike in WT (E), expression of the posterior patterning gene Hoxd13 in left forelimb buds extends ectopically into an anterior domain (yellow arrowheads) in 251 (F) and 239 (G) mutants. Fgf4 expression in left hindlimb buds, restricted to the posterior AER in WT (H), has an ectopic expression domain at the far anterior edge of the AER (yellow arrowheads) in 251 (I) and 239 (J) mutants. To identify the developmental basis of the limb defects, we examined the expression of genes involved in limb patterning. A regulatory network involving Shh and Fgf4 regulates the expression of Hoxd13 and controls patterning of the limb (Figure 4D). We first investigated the expression of Hoxd13 as a molecular marker of anterior-posterior (A-P) pattern in the limb at early stages. Hoxd13 is ectopically expressed in the anterior portion of line 239 and line 251 mutant limbs (Figure 4E–4G), indicating that the anterior polydactyly is caused by a defect in A-P patterning. We next examined the expression of the elements of the network that regulate Hoxd13 expression (Figure 4D) to see whether their expression was perturbed. The expression of Shh, Ptc1, gremlin (also known as Cktsf1b1), and Bmp4 are not distinguishable from wild-type (WT) (unpublished data). In contrast, an ectopic domain of FGF4 persists in the anterior apical ectodermal ridge (AER) (Figure 4H–4J). Thus the defects in limb patterning result from disruption of a step downstream of Shh, Ptc1, gremlin, and Bmp4, and upstream of Fgf4. This does not allow a specific molecular mechanism to be invoked, yet the combination of similar defects in both the limb and in the pattern of interneuron migration is strong evidence that the same molecular mechanism is disrupted in all three mutants. Migrating Cells Persist Abnormally in the IZ of 239, 251, and 275 The 239, 251, and 275 mutants have clusters of LacZ-expressing cells in the IZ and/or SVZ of the rostral cortex, whereas more caudally, defects appear milder (Figure 5). In WT animals there is a clear demarcation, at the corticostriatal junction, between the SVZ of the dorsal LGE and the stream of cells migrating into the cortex (black arrowheads in Figure 5C–5E). The crispness of this boundary is lost in the 239 and 275 lines (yellow ovals in Figure 5F–5H and 5L–5N), although not in 251. In all three mutants, occasional linear aggregates of LacZ-expressing cells extend from the IZ/SVZ to the MZ (red arrowheads in Figure 5I and 5N). Figure 5 Line 239, 251, and 275 Mutants Have Similar Migration Defects (A) Frontal view of an E14.5 WT embryo. (B) Frontal view of an E14.5 embryo homozygous for the line 239 mutation. The stream of cells leaving the SVZ of the LGE is streaky and aggregated in the rostral cortex of the mutant. (C–E) A rostral-to-caudal series of coronal sections from an E14.5 WT embryo. WT embryos have diffuse cortical staining and a sharp boundary (black arrowheads) between the subcortical and the cortical telencephalon. (F–H) Coronal sections from E14.5 line 239 mutant forebrains. Yellow circles indicate the area of the cortical-subcortical boundary where a large excess of migrating cells can be seen in the IZ/SVZ area. Orange arrowhead indicates aggregated cells in the IZ/SVZ of the lateral wall of the cortex. White arrowheads indicate aggregates in the medial wall. The staining in the MZ appears normal. Defects become less apparent in the more caudal sections. (I–K) Sections from an E14.5 line 251 mutant embryo. Orange arrowheads indicate aggregates in the lateral wall of the cortex. In (I), a linear aggregate of stained cells can be seen extending from the IZ/SVZ to the MZ (red arrowhead). The cortical-subcortical boundary is well defined in line 251 mutants. (L–N) Sections from an E14.5 line 275 mutant embryo. Yellow circles indicate aberrant staining in the cortical-subcortical boundary region. The white arrowhead indicates aggregates in the medial wall of the cortex, and the red arrowhead points to a radially directed aggregate of cells extending from the IZ/SVZ to the MZ. To study the effects of the mutations at later stages of cortical interneuron development, we examined near-term (E18.5) animals (Figure 6). We focused our analysis on line 251 and evaluated the expression of the Dlx-LacZ transgene and Gad67. As at E14.5, aggregation of Gad67+; LacZ+ cells in the IZ/SVZ is a prominent feature of the phenotype (black arrowheads, Figure 6B, 6F, and 6J). Despite the severity of the defects observed in the IZ/SVZ, Dlx-LacZ–expressing interneuron precursors in the MZ and in the cortical plate do not form aggregates (yellow and blue arrowheads in Figure 6I and 6J), suggesting that the mutation inhibits the ability of migrating interneurons to leave the IZ/SVZ, but does not significantly impact other aspects of their migration. Figure 6 Dlx-LacZ and GAD67 Expression Show that Interneuron Precursors Persist in the IZ/SVZ of 251 Mutant Cortices (A) Coronal section through the forebrain of an E18.5 WT embryo stained for β-galactosidase and counterstained with nuclear fast red. (B) A similar section from a line 251 mutant embryo. Unusual accumulations of stained cells can be seen in the cortex just dorsal to the striatum (white arrowheads). Aggregates of cells in the IZ/SVZ can also be seen (black arrowhead). (C and D) Sections adjacent to those in (A) and (B) hybridized with a probe for Gad67 mRNA. Arrowheads in (D) point to the same features that are seen in (B). (E–H) Higher-magnification views of the dorsal portions of the sections in (A–D). (I and J) Higher-magnification view of cortex. In the WT cortex (I), cells can be seen dispersed through the cortical plate (yellow arrowheads) and scattered through the MZ (blue arrowheads). Similar distributions of labeled cells can be seen in the mutant cortex (J). In contrast to the WT, however, aggregates of cells are found in IZ/SVZ (black arrowheads). A Mutant with Defects in Invasion of the Cortex by Thalamocortical Axons In addition to the seven mutants described in the previous sections, six other mutants were isolated. Most of these have not been characterized in detail, but one, line 412, illustrates the range of phenotypes that the Dlx-LacZ transgene allowed us to identify. In line 412, the mutant phenotype was detectable in whole mount as a subtle but consistent defect near the cortical-subcortical boundary. Upon sectioning, this defect was revealed to be a delamination in the region of the external capsule (Figure 7A–7D). Thalamocortical fibers ordinarily enter the cortex at this point, and this defect can occur when fewer axon tracts cross this zone (Hevner et al. 2002). Indeed, the 412 mutant has fewer thalamocortical fibers traversing the corticostriatal boundary at E14.5, as evidenced by the reduced density of L1+ axons in this location (Figure 7E and 7F). Examination of late-stage embryos shows that the lack of cortical invasion by thalamocortical fibers at E14.5 is due to a persistent inhibition and not merely a delay in innervation (unpublished data). The IZ of the cortex often appears thinner in mutants, consistent with the absence of thalamocortical axons. Interestingly, TAG1+ corticofugal axons are still present in the cortex (Figure 7G and 7H). Analysis of markers for the dorsal thalamus, where the thalamocortical axons originate, and for the striatum, which they must traverse, does not reveal any obvious defects (A. Ashique, personal communication). This, together with the observation that corticofugal fibers appear to be intact, suggests that the mutation may disrupt a molecule that is directly involved in pathfinding by thalamocortical axons. Figure 7 Corticostriatal Delamination and Lack of the Thalamocortical Projection in Line 412 Mutants (A–D) Coronal hemisections of E15.5 WT (A and C) and line 412 (B and D) mutant embryos stained for the Dlx-LacZ transgene. The cortex is thinner in 412 mutants, as can be seen in both the rostral (B) and the caudal (D) sections. Delamination of the corticostriatal boundary can be seen in the region between the red arrowheads in (D). (E and F) Immunostaining for L1 antigen labels the thalamocortical fibers in coronal hemisections from E14.5 WT (E) and mutant (F) embryos. The striatum and corticostriatal areas are shown. In the WT section, the thalamocortical fibers can be seen traversing the striatum through the internal capsule and coursing into the cortex. In the mutant section, a few fibers enter the striatum but do not traverse it to reach the cortex. Corticostriatal delamination can be seen as a hole in the right side of the section. (G and H) Immunostaining for TAG1 antigen (blue arrowheads) reveals corticofugal fibers. Discussion Novel ENU-Induced Alleles ENU overwhelmingly induces single-basepair substitution mutations. The mutant alleles that are produced often have relatively selective effects on protein function, and so provide valuable probes of the function of different protein domains. This is illustrated by two of the alleles described here, Rfx4 and Scrb1. Each of these alleles is a missense mutation that appears to disrupt specific domains in a selective fashion. The SCRB1 protein has two sets of recognizable domains: three amino-terminal LRRs and four, more carboxy-terminal, PDZ domains. The previously described allele of Scrb1, the Circletail allele, has a stop codon that terminates translation after the first two PDZ domains. In contrast, the line 90 allele of Scrb1 is predicted to encode a charged lysine in place of a hydrophobic isoleucine on the outside of the third LRR domain (see Figure 2D and 2E). The homozygous phenotypes produced by the line 90 and the Circletail alleles are apparently identical, and both show strong genetic interactions with a mutation in Str-1, a cell-surface protein that regulates planar cell polarity in both flies and mammals. From this we can conclude that both the LRR and the PDZ domains are required for SCRB1's role in the establishment of epithelial polarity. The missense allele of Rfx4 is predicted to have very subtle effects on the structure of the protein. The mutation causes a proline to be substituted for a leucine residue in a dimerization domain of the protein. Proline residues are not compatible with α-helices, but in this case the substitution appears to be at the beginning of a β-turn that links two helices. Presumably, the substitution causes the linkage between the α-helices to be stiffened or abnormally constrained in some way. Whatever the exact molecular consequences are, the nature of the allele and the genetics suggest that the mutation prevents dimerization. Ordinarily RFX4 can dimerize with itself and with the related transcription factors RFX2 and RFX3 (Morotomi-Yano et al. 2002). If inactive dimers were produced by the missense allele, it would seem likely to cause a dominant phenotype, which it does not. Studies are underway that will test these ideas as well as determine whether the failure of the dorsal midline to form is the result of a loss of a dorsal signaling center or an inability of the cortical neuroepithelium to respond to those signals. The megalin allele provides a contrast to these first two cases. Despite its molecular severity as a premature stop codon, its phenotypic consequences are less pronounced than the knockout allele. The knockout mutation produces early-head-fold–stage embryos with reduced neuroepithelium in the anterior midline (Willnow et al. 1996). These defects originate during gastrulation, and by mid-gestation result in holoprosencephaly. The absence of these early defects in the ENU-induced allele could be interpreted to mean that the defective protein retains some function and supplies the MEGALIN activity that is required during gastrulation. Alternatively, it is possible that the deleted region in the knockout is required for the proper expression of a neighboring gene and that the gastrulation phenotype does not reflect an early role for megalin. In each of these three cases, the ENU-induced allele provides novel information about the role of the gene in cortical development and suggests avenues for further exploration. As we determine the molecular nature of the other mutations, it is likely that the selective nature of the ENU-induced alleles will provide important insights into the function of other proteins that regulate cortical development. Nature of the Tangential Migration Defects The migration of immature interneurons has been followed using lipophilic dyes, tissue chimeras, transfection with a green fluorescent protein (GFP) expression vector, and, recently, using a Gad67-GFP knockin mouse (de Carlos et al. 1996; Anderson et al. 1997, 2001; Tamamaki et al. 1997; Denaxa et al. 2001; Polleux et al. 2002; Ang et al. 2003). These studies have identified tangentially migrating cells in both the IZ/SVZ and the MZ. Some studies have concluded that the cells in the IZ/SVZ and the MZ are two independent migratory streams (Lavdas et al. 1999). In contrast, the use of a Gad67-GFP knockin allele to follow interneuron precursors (Tanaka et al. 2003) led to the conclusion that the general pattern of cell migration is tangentially through the IZ and thence radially outward from the IZ to the MZ. Cells in the MZ also migrate tangentially but at a slower rate than those in the IZ (Polleux et al. 2002; Tanaka et al. 2003), in a process that may be a search for the proper location at which to invade the cortical plate (Ang et al. 2003). These two models for tangential migration produce different interpretations of the pattern of defects that we see in our novel mutants. In the first model, obvious defects in the IZ but not the MZ would imply that the mutations are disrupting a process used to regulate migration through the IZ but not through the independently regulated MZ. In the second model, the predominance of defects in the IZ/SVZ would indicate an inhibition at an early step of the migratory process. The presence of cell aggregates extending from the IZ to the MZ is consistent with this being the step that is defective, whereas the presence of properly dispersed cells in the MZ and cortical plate would indicate that the mutations inhibit, but do not completely block, this early step. Concordance of Limb Patterning and Migration Defects Three out of the four tangential migration defects also result in anterior polydactyly. The association of limb patterning and neuronal migration defects has not been previously reported and, given that a great deal more is known about limb patterning than about tangential migration, it is tempting to speculate on what this may imply about the migration mutants. One possibility is that shared mechanisms are used to pattern the telencephalon and the limb. It is equally possible that genes that regulate patterning in the limb regulate cell migration decisions more directly. Mutations in an arista-less homolog, Arx, cause profound defects in interneuron migrations, and mutations in another arista-less homolog, Alx4, cause anterior polydactyly. However, as the limbs of Alx4 mutants, unlike the 239, 251, and 275 mutants, have ectopic Shh expression in the anterior limb bud, it is unlikely that the mutations described here disrupt an arista-less pathway. Shh maintains the expression of Fgf4 in the posterior AER of WT limb buds in a process that requires gremlin. Genes that act in this process downstream of Bmp4 are plausible candidates for the line 239, 251, and 275 mutations. General Implications for Genetic Screens in the Mouse The work described here demonstrates clearly that genetic screening strategies in the mouse need not be limited to general or broad-based phenotyping approaches; a focused genetic screening strategy can provide a powerful means of dissecting a specific aspect of mammalian biology. The strategy of broad-based approaches has been an effective one for the past several years as the collection of mutants using chemically induced mutations resurged in popularity. In other genetic systems, strategies have evolved from general toward focused screens that allow mutations affecting a specific process to be identified, and it is likely that mouse genetics will progress in a similar fashion. An additional concern with mice, however, is the cost of breeding and housing, which is higher than that for other model genetic organisms. We have shown, nonetheless, that a laboratory-based, focused screening strategy is a productive pursuit. The costs of such a screen could be shared by the careful combination of reporters so that screening for several distinct processes could be carried out at once. This general idea is highlighted by our isolation of mutations in which the growth and patterning of the cortex is defective. With the exception of line 90, the identification of these mutants benefited from the easy visualization of cortical size and structure by expression of the transgene. In several cases, the interneuron migration mutants being a good example, the identification of the mutant phenotype without the transgene would have been very unlikely. Independent reporters could be used to pursue the simultaneous identification of several different classes of mutants more directly. For example, reporters that label migrating neurons with GFP, and thalamocortical axons with β-galactosidase or alkaline phosphatase, would allow both migration and axonal pathfinding mutations to be identified in the same screen. Given the large number of reporter and indicator strains that have been made over the last few years and the powerful tools that exist for gene identification, it is clear that focused screens in the mouse will provide the resources to address many questions in the coming years. Materials and Methods Animals and breeding. Male C57BL/6J mice were obtained from Jackson Laboratories (Bar Harbor, Maine, United States) and treated with three intraperitoneal injections of 100 mg/kg ENU (Sigma, St. Louis, Missouri, United States) spaced at 7-d intervals. Eight weeks after the last injection, the ENU-treated males were set up in breeding pairs with FVB/NJ females homozygous for the Dlx-LacZ transgene. Male offspring of this cross (G1 males) were backcrossed to the transgenic line, and female offspring (G2 females) were saved. For each line, one to six of the G2 females were backcrossed to their fathers to generate timed pregnancies. Embryos were harvested either 13 d (the first 100 lines) or 14 d (all subsequent lines) after the vaginal plug was identified. Screening. Embryos were dissected in phosphate-buffered saline (PBS) and fixed for 45 min at room temperature in 4% paraformaldehyde (PFA) in PBS. Subsequently, embryos were washed in detergent rinse (0.1 M phosphate buffer [pH 7.3], 2 mM MgCl2, 0.01% sodium deoxycholate and 0.02% Nonidet P-40). Embryos were then stained for 48–72 h at room temperature on a rocking platform using X-gal as a substrate for the detection of β-galactosidase activity. Staining was terminated after visual inspection by repeated washing in PBS. Embryos were then fixed again and stored in 4% PFA in PBS until further examined. All litters were examined in whole mount and approximately one-half were selected for sectioning on a vibratome (VT1000S; Leica, Wetzlar, Germany). For sectioning, the heads of all pups from a litter were separated from the torsos and mounted aligned in the same orientation in an agarose block. Sections 100 μm thick were collected in PBS and mounted in Kaiser's glycerol gelatin (Merck, Darmstadt, Germany) on slides. All phenotypes reported here were seen in more than ten litters resulting from both G1 male × G2 female and G2 male × G2 female crosses. Histology. Whole-mount in situ hybridization was carried out according to Henrique et al. (1995). Gad67 in situ hybridization on sections was carried out following standard protocols (Dagerlind et al. 1992) with a digoxigenin-labeled antisense RNA probe generated by in vitro transcription using a plasmid obtained from Brian G. Condie (Maddox and Condie 2001). In brief, embryos were dissected in diethylpyrocarbonate-treated PBS, and the heads were removed and fresh-frozen on dry ice. Tissue was sectioned at 20 μm on a cryostat (Leica CM3050). Slide-mounted cryosections were warmed to room temperature and fixed in 4% PFA in PBS. Deacetylation was performed for 10 min by immersion in 0.1 M triethanolamine containing 25 mM acetic anhydride followed by rinsing in 2× saline sodium citrate and dehydration through an increasing alcohol series (60%, 75%, 95%, and 100%). Sections were hybridized with the riboprobe under stringent conditions (50% formamide, 10% dextran sulfate, 20 mM Tris-HCl, 0.3 M NaCl, 5 mM EDTA, 0.02% Ficoll 400, 0.02% polyvinylpyrrolidone, 0.02% BSA, 0.5 mg/ml tRNA, 0.2 mg/ml carrier DNA, and 200 mM DTT) for 16–20 h at 63 °C. After hybridization, sections were washed four times in 4× saline sodium citrate solution and incubated for 30 min in RNase buffer (10 mM Tris-HCl [pH 7.5], 0.5 M NaCl, and 5 mM EDTA [pH 8.0]) containing 20 μg/ml RNase A at 37 °C. High-stringency washes were performed twice for 30 min at 63 °C. Incubation with the anti-digoxigenin antibody (Roche, Basel, Switzerland) was carried out in maleic acid buffer (100 mM maleic acid, 150 mM NaCl, and 1% blocking reagent [Roche]). Finally, staining was performed with BM purple substrate (Roche) terminated by repeated washes in PBS, and sections were coverslipped using Kaiser's glycerol gelatin. Nuclear fast red counterstaining for X-gal–stained sections was performed with pre-made staining solution (Vector Laboratories, Burlingame, California, United States). Staining was differentiated in 70% ethanol. Immunohistochemistry using anti-TAG1 (Developmental Studies Hybridoma Bank, University of Iowa, Iowa City, Iowa, United States) and anti-L1 (Chemikon, Mönchengladback, Germany) antibodies was performed on 100-μm free-floating sections following the instructions and using the reagents of the Vectastain ABC Kit (Vector). Primary antibodies were used at a dilution of 1:500. Horseradish peroxidase activity from secondary antibodies was revealed by diaminobenzidine as a substrate in staining buffer (0.5 mg/ml diaminobenzidine, 20 mM sodium cacodylate, and 30 mN acetic acid). Mapping. Initial linkage was established using 12 DNA samples from both carriers and mutant embryos. We scored a set of 82 simple sequence repeat markers. The panel of markers was selected from the set at the Center for Inherited Disease Research Website (http://www.cidr.jhmi.edu/mouse/mouse.html). Markers were chosen that could be scored easily on agarose gels. All chromosomal assignments reported are the result of LOD scores significantly greater than three. The intervals that are listed in Table 1 were derived following the initial establishment of linkage by haplotype analysis that included additional recombinant chromosomes from mutant animals or obligate carriers. The phenotypes of 239 and 275 are very similar, and the fact that they map to the same interval likely reflects allelism. The localization of both 351 and 357 to the same interval seems more likely to be coincidental, because the phenotypes are quite different. Sequencing. For sequencing of Rfx4 and Scrb1 genes, RT-PCR samples were prepared from cDNA prepared using E10.5 to E16.5 embryos. For megalin, exons were amplified using genomic DNA samples. Primer sequences are available upon request. In both cases sequencing was done by the University of California, Berkeley, DNA Sequencing Facility. Supporting Information Figure S1 Cortical Size Is Altered in Lines 152 and 351 (A) Dorsal views of the cortex of WT (left) and line 152 mutant (right) embryos stained for expression of the Dlx-LacZ transgene. The line 152 mutation reduces the size of the cortex. (B and C) Coronal sections through the cortex of E14.5 WT (B) and line 351 mutant (C) embryos. The cortex has a characteristic high-domed shape and is thinner in the mutant. (D and E) Dorsal (D) and ventral (E) views of adult brains of WT (left) and line 351 mutant (right) brains. The cortex is overall larger in the mutant than in the WT. The olfactory bulbs are present in the mutant but are tucked under the cortex, making them less visible. (9.1 MB TIF). Click here for additional data file. Figure S2 Central Nervous System Defects and Cleft Upper Jaw in Lines 366 and 357 (A) Lateral view of an E14.5 WT embryo. (B) The cleft upper jaw of a line 366 mutant is visible at the left. The telencephalon, including the cortex, is significantly shortened along the rostrocaudal axis. (C and D) Lateral and front views of the cleft and reduced upper jaw of an E18.5 embryo homozygous for the line 366 mutation. (E and F) Lateral views of WT (E) and line 357 homozygote (F) embryos at E13.5 showing the reduced telencephalon and relatively expanded midbrain. (G) A front view of the embryo in (F) shows the cleft upper jaw. (H and I) Sagittal sections through E13.5 WT (H) and line 357 (I) embryos. The overgrown midbrain in the mutant embryo has forced the neuroepithelium into folds. (9.9 MB TIF). Click here for additional data file. Figure S3 Line 407 Mutants Have Dorsoventral Defects in the Cortical Primordia and Facial Midline Defects (A) Lateral view of an E14.5 mutant embryo showing edema and hemorrhage suggestive of vascular defects. Frontal views of WT (B) and mutant (C) embryos illustrate the narrowed frontonasal process, maxilla, and mandible of the mutant. (D) shows coronal hemisections in a WT embryo. (E) shows the accumulation of Dlx-LacZ–positive cells in a SVZ-like area dorsal to the LGE. (4.3 MB TIF). Click here for additional data file. Accession Numbers Accession numbers of the genes discussed in this paper are available at LocusLink (http://www.ncbi.nih.gov/LocusLink, and are as follows: Alx4 (11695), Arx (11878), Bmp4 (12159), Dlx5/6 (13395/13396), Fgf4 (14175), Gad67 (14415), gremlin (23892), Hoxd13 (15433), L1 (16728), Lrp2 (14725), Ltap/Lpp1 (93840), Ptc1 (19206), Rfx4 (71137), Scrb1 (105782), scribbled (44448), Shh (20423), and Tag1 (21367). We thank Dr. Amir Ashique for permission to cite unpublished work, Dr. Viktor Kharazia for help and advice with histological analysis, and Marlene Lane for help with many aspects of animal breeding and husbandry and for help with the early stages of the screen. We also thank Deanna Louie, Kristina Bray, Tyler Wai Chan, and William Tseng for their assistance. This research was supported in part by funds provided by the National Institutes of Health/National Institute of Mental Health, award number R21 MH068525 (ASP); a Human Frontiers Science Program Grant, number RG0160/2000-B (ASP); a Wills Foundation Fellowship (KZ); and a Broad Foundation Fellowship (SM). It was also supported in part by funds provided by the State of California for medical research on alcohol and substance abuse through the University of California, San Francisco. Conflicts of interest. The authors have declared that no conflicts of interest exist. Author contributions. ASP conceived the screen. ASP, KZ, SRM, and YS designed and performed the experiments. KZ, SRM, YS, JLRR, and ASP analyzed the data. ME contributed reagents/materials/analysis tools. ASP, KZ, and SRM wrote the paper. Academic Editor: Joshua R. Sanes, Harvard University Citation: Zarbalis K, May SR, Shen Y, Ekker M, Rubenstein JLR, Peterson AS (2004) A focused and efficient genetic screening strategy in the mouse: Identification of mutations that disrupt cortical development. PLoS Biol 2(8): e219. Abbreviations AERapical ectodermal ridge A-Panterior-posterior E[number]embryonic day [number] ENUethyl-nitroso-urea GFPgreen fluorescent protein IZintermediate zone LGElateral ganglionic eminence LRRleucine-rich repeat MZmarginal zone P[number]postnatal day [number] PBSphosphate-buffered saline PFAparaformaldehyde Shh sonic hedgehog; SVZ WTwild-type ==== Refs References Anderson SA Eisenstat DD Shi L Rubenstein JL Interneuron migration from basal forebrain to neocortex: Dependence on Dlx genes Science 1997 278 474 476 9334308 Anderson SA Marin O Horn C Jennings K Rubenstein JL Distinct cortical migrations from the medial and lateral ganglionic eminences Development 2001 128 353 363 11152634 Ang ES Haydar TF Gluncic V Rakic P Four-dimensional migratory coordinates of GABAergic interneurons in the developing mouse cortex J Neurosci 2003 23 5805 5815 12843285 Bilder D Perrimon N Localization of apical epithelial determinants by the basolateral PDZ protein Scribble Nature 2000 403 676 680 10688207 Bilder D Li M Perrimon N Cooperative regulation of cell polarity and growth by Drosophila tumor suppressors Science 2000 289 113 116 10884224 Bilder D Schober M Perrimon N Integrated activity of PDZ protein complexes regulates epithelial polarity Nat Cell Biol 2003 5 53 58 12510194 Blackshear PJ Graves JP Stumpo DJ Cobos I Rubenstein JL Graded phenotypic response to partial and complete deficiency of a brain-specific transcript variant of the winged helix transcription factor RFX4 Development 2003 130 4539 4552 12925582 Boncinelli E Mallamaci A Muzio L Genetic control of regional identity in the developing vertebrate forebrain Novartis Found Symp 2000 228 53 61 61 56 109 113 10929316 Dagerlind A Friberg K Bean AJ Hokfelt T Sensitive mRNA detection using unfixed tissue: Combined radioactive and non-radioactive in situ hybridization histochemistry Histochemistry 1992 98 39 49 1429016 de Carlos JA Lopez-Mascaraque L Valverde F Dynamics of cell migration from the lateral ganglionic eminence in the rat J Neurosci 1996 16 6146 6156 8815897 Denaxa M Chan CH Schachner M Parnavelas JG Karagogeos D The adhesion molecule TAG-1 mediates the migration of cortical interneurons from the ganglionic eminence along the corticofugal fiber system Development 2001 128 4635 4644 11714688 Eggenschwiler JT Espinoza E Anderson KV Rab23 is an essential negative regulator of the mouse Sonic hedgehog signalling pathway Nature 2001 412 194 198 11449277 Emery P Durand B Mach B Reith W RFX proteins, a novel family of DNA binding proteins conserved in the eukaryotic kingdom Nucleic Acids Res 1996 24 803 807 8600444 Garcia-Garcia MJ Anderson KV Essential role of glycosaminoglycans in Fgf signaling during mouse gastrulation Cell 2003 114 727 737 14505572 Henrique D Adam J Myat A Chitnis A Lewis J Expression of a Delta homologue in prospective neurons in the chick Nature 1995 375 787 790 7596411 Hevner RF Miyashita-Lin E Rubenstein JL Cortical and thalamic axon pathfinding defects in Tbr1, Gbx2, and Pax6 mutant mice: Evidence that cortical and thalamic axons interact and guide each other J Comp Neurol 2002 447 8 17 11967891 Hoebe K Du X Goode J Mann N Beutler B Lps2: A new locus required for responses to lipopolysaccharide, revealed by germline mutagenesis and phenotypic screening J Endotoxin Res 2003 9 250 255 12935356 Hrabe de Angelis MH Flaswinkel H Fuchs H Rathkolb B Soewarto D Genome-wide, large-scale production of mutant mice by ENU mutagenesis Nat Genet 2000 25 444 447 10932192 Juriloff DM Sulik KK Roderick TH Hogan BK Genetic and developmental studies of a new mouse mutation that produces otocephaly J Craniofac Genet Dev Biol 1985 5 121 145 4019727 Kapfhamer D Valladares O Sun Y Nolan PM Rux JJ Mutations in Rab3a alter circadian period and homeostatic response to sleep loss in the mouse Nat Genet 2002 32 290 295 12244319 Katan Y Agami R Shaul Y The transcriptional activation and repression domains of RFX1, a context-dependent regulator, can mutually neutralize their activities Nucleic Acids Res 1997 25 3621 3628 9278482 Katan-Khaykovich Y Shaul Y RFX1, a single DNA-binding protein with a split dimerization domain, generates alternative complexes J Biol Chem 1998 273 24504 24512 9733744 Katan-Khaykovich Y Spiegel I Shaul Y The dimerization/repression domain of RFX1 is related to a conserved region of its yeast homologues Crt1 and Sak1: A new function for an ancient motif J Mol Biol 1999 294 121 137 10556033 Kibar Z Vogan KJ Groulx N Justice MJ Underhill DA Ltap, a mammalian homolog of Drosophila Strabismus/Van Gogh, is altered in the mouse neural tube mutant Loop-tail Nat Genet 2001 28 251 255 11431695 Kile BT Hentges KE Clark AT Nakamura H Salinger AP Functional genetic analysis of mouse chromosome 11 Nature 2003 425 81 86 12955145 Lavdas AA Grigoriou M Pachnis V Parnavelas JG The medial ganglionic eminence gives rise to a population of early neurons in the developing cerebral cortex J Neurosci 1999 19 7881 7888 10479690 Maddox DM Condie BG Dynamic expression of a glutamate decarboxylase gene in multiple non-neural tissues during mouse development BMC Dev Biol 2001 1 1 11178105 Marin O Rubenstein JL A long, remarkable journey: Tangential migration in the telencephalon Nat Rev Neurosci 2001 2 780 790 11715055 Marin O Rubenstein JL Cell migration in the forebrain Annu Rev Neurosci 2003 26 441 483 12626695 Molnar Z Hannan AJ Development of thalamocortical projections in normal and mutant mice Results Probl Cell Differ 2000 30 293 332 10857195 Montcouquiol M Rachel RA Lanford PJ Copeland NG Jenkins NA Identification of Vangl2 and Scrb1 as planar polarity genes in mammals Nature 2003 423 173 177 12724779 Morotomi-Yano K Yano K Saito H Sun Z Iwama A Human regulatory factor X 4 (RFX4) is a testis-specific dimeric DNA-binding protein that cooperates with other human RFX members J Biol Chem 2002 277 836 842 11682486 Murdoch JN Doudney K Paternotte C Copp AJ Stanier P Severe neural tube defects in the loop-tail mouse result from mutation of Lpp1, a novel gene involved in floor plate specification Hum Mol Genet 2001a 10 2593 2601 11709546 Murdoch JN Rachel RA Shah S Beermann F Stanier P Circletail, a new mouse mutant with severe neural tube defects: Chromosomal localization and interaction with the loop-tail mutation Genomics 2001b 78 55 63 11707073 Murdoch JN Henderson DJ Doudney K Gaston-Massuet C Phillips HM Disruption of scribble (Scrb1) causes severe neural tube defects in the circletail mouse Hum Mol Genet 2003 12 87 98 12499390 Nivard MJ Pastink A Vogel EW Molecular analysis of mutations induced in the vermilion gene of Drosophila melanogaster by methyl methanesulfonate Genetics 1992 131 673 682 1628810 Nolan PM Peters J Strivens M Rogers D Hagan J A systematic, genome-wide, phenotype-driven mutagenesis programme for gene function studies in the mouse Nat Genet 2000 25 440 443 10932191 Polleux F Whitford KL Dijkhuizen PA Vitalis T Ghosh A Control of cortical interneuron migration by neurotrophins and PI3-kinase signaling Development 2002 129 3147 3160 12070090 Russell WL Kelly EM Hunsicker PR Bangham JW Maddux SC Specific-locus test shows ethylnitrosourea to be the most potent mutagen in the mouse Proc Natl Acad Sci U S A 1979 76 5818 5819 293686 Stuhmer T Puelles L Ekker M Rubenstein JL Expression from a Dlx gene enhancer marks adult mouse cortical GABAergic neurons Cereb Cortex 2002 12 75 85 11734534 Tamamaki N Fujimori KE Takauji R Origin and route of tangentially migrating neurons in the developing neocortical intermediate zone J Neurosci 1997 17 8313 8323 9334406 Tanaka D Nakaya Y Yanagawa Y Obata K Murakami F Multimodal tangential migration of neocortical GABAergic neurons independent of GPI-anchored proteins Development 2003 130 5803 5813 14534141 Vitaterna MH King DP Chang AM Kornhauser JM Lowrey PL Mutagenesis and mapping of a mouse gene, Clock, essential for circadian behavior Science 1994 264 719 725 8171325 Vrieling H Simons JW van Zeeland AA Nucleotide sequence determination of point mutations at the mouse HPRT locus using in vitro amplification of HPRT mRNA sequences Mutat Res 1988 198 107 113 2895423 Walsh CA Goffinet AM Potential mechanisms of mutations that affect neuronal migration in man and mouse Curr Opin Genet Dev 2000 10 270 274 10826984 Willnow TE Hilpert J Armstrong SA Rohlmann A Hammer RE Defective forebrain development in mice lacking gp330/megalin Proc Natl Acad Sci U S A 1996 93 8460 8464 8710893

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PLoS Biol. 2004 Aug 17; 2(8):e219

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PLoS Biol

10.1371/journal.pbio.0020219

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020220SynopsisGenetics/Genomics/Gene TherapyImmunologyMus(Mouse)Deconstructing Genetic Contributions to Autoimmunity in Mouse Models Synopsis8 2004 17 8 2004 17 8 2004 2 8 e220Copyright: © 2004 Public Library of Science.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. Spontaneous Autoimmunity in 129 and C57BL/6 Mice - Implications for Autoimmunity Described in Gene-Targeted Mice ==== Body Given the overwhelming complexity of the immune system, it's no wonder that unraveling the mechanisms responsible for immunological disease has proved so difficult. The factors that trigger autoimmunity—which involves a breakdown in the body's ability to tolerate its own molecules—are not well understood, though animal studies show that genetic predisposition greatly increases risk. And that's where the real challenge begins. For certain diseases, individuals with defects in both copies of a specific gene invariably develop the disease. But more often, diseases with an inherited component result from the complex interplay of a variety of genes, each contributing a small effect that is typically dependent both on the expression of other genes and on both random and environmental factors. Researchers have increasingly turned to mice to model autoimmunity in humans and have found the same genetic complexity at work, with different strains of lupus-prone mice having different genes predisposing them to autoimmune disease. One model involves targeted disruption of candidate immune system genes to study their role in disease. Gene targeting experiments modify or remove a gene of interest and then watch for corresponding effects on the organism's physiology. Interpretations of results from these experiments have traditionally been predicated on the assumption that the “background,” or nontargeted, genes do not contribute to observed physiological changes. Yet in some studies, mice without targeted mutations develop an unexpected susceptibility to the autoimmune disease under study. Genetic background can induce autoimmunity in knock-out mice To investigate what effects background genes might be having in these mouse models, Marina Botto and colleagues compared the genomes of three hybrid strains of the most commonly used genetic background—the 129 and C57BL/6 hybrid mice. One of the hybrids, which carries a mutation in both copies of the Apcs gene, was chosen as an example of a gene-targeted model that develops a lupus-like disease, offering an opportunity to examine the relative contributions of the targeted versus background genes. Apcs is a candidate gene for human systemic lupus erythematosus (SLE), a form of autoimmunity marked by chronic inflammation resulting from a sustained attack on antibodies throughout the body. Botto and colleagues found that several genomic regions from both the 129 and C57BL/6 mice contributed to autoimmunity, even in the absence of gene-targeted mutations. All of the hybrid strains developed autoimmunity, though disease was more severe in mice with Apcs mutations. Disease outcome in gene-targeted mice, it turns out, can be influenced not just by disease-susceptible (or disease-resistant) gene variants near the targeted gene (in this case, Apcs) but by the random heterogeneity of the hybrid genetic background: multiple combinations of genes in the hybrids can produce the same result. These results fall in line with mounting evidence that background genes are not silent partners in gene-targeted disease models, but can themselves facilitate expression of the disease. This finding underscores the notion that genes are not solitary, static entities; their expression often depends on context. With genetically complex diseases, having the requisite combination of susceptibility genes does not always lead to disease. Much work remains to be done to identify the triggers that cause the immune system to turn on itself. For more on mouse models and autoimmunity, see the primer by Morel in this issue.

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2021-01-05 08:28:06

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PLoS Biol. 2004 Aug 17; 2(8):e220

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PLoS Biol

10.1371/journal.pbio.0020220

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020224Journal ClubPlant SciencePlantsGrafting the Way to the Systemic Silencing Signal in Plants Journal ClubKalantidis Kriton 8 2004 17 8 2004 17 8 2004 2 8 e224Copyright: © 2004 Kriton Kalantidis.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.Grafting is a powerful but complex means to study the spread of RNA silencing ==== Body Grafting is an ancient technique used by farmers and gardeners to combine desired attributes of the rootstock with those of the donor plant shoot, or scion. Grafting essentially saved European wine making: when the insect Dactylosphera vitifoliae devastated European grapewine varieties over the course of the late 1800s and early 1900s, the varieties were saved by grafting them onto resistant rootstocks from the New World. Since then, these rootstocks have been used to maintain the susceptible Old World cultivars. But grafting is also an excellent tool for scientists studying systemic signals traveling between the rootstock and distal parts of the plants, and vice versa. For example, two important studies (Palauqui et al. 1997; Voinnet et al. 1998) used grafting to demonstrate the spreading of RNA silencing in plants. However, it was a subsequent paper (Crete et al. 2001) that followed up on certain inconsistencies in the grafting results that pointed to subtleties important for both experimental design and understanding systemic signaling in plants. RNA silencing (termed posttranscriptional gene silencing in plants, quelling in fungi, and RNA interference in animals) refers to the phenomenon whereby specific gene transcript levels are reduced in the presence of a related RNA. From studies of RNA silencing in several systems, much is now known about the mechanisms involved (Matzke 2002; Mlotshwa et al. 2002), but the systemic spreading in plants is still a bit of a mystery. Posttranscriptional gene silencing spreads systemically throughout the individual plants in a very characteristic manner reminiscent of viral spread. This has led to the hypothesis of a systemic silencing signal that is produced in the tissues where silencing is initiated and is then transmitted to the distant parts of the plant where it can initiate silencing in a sequence-specific manner. The sequence specificity of the silencing strongly implies that the signal is a nucleic acid, most likely an RNA, but the identity of the signal remains unknown. Silencing spreads mainly in the direction from carbon source to carbon sink, that is, from tissues such as leaves that export the sugar products of photosynthesis, to tissues such as roots that import these products, and it can take up to several weeks until it is established in the whole plant (Palauqui et al. 1997; Palauqui and Vaucheret 1998; Voinnet et al. 1998; Sonoda and Nishiguchi 2000). As expected, the discovery of this process triggered a quest for the “systemic inducer” of the process: a signal that travels through the plant and is able to initiate silencing in a remote location within the plant. Grafting was an obvious tool to use in the quest for this signal, as it allowed silencing source and sink tissues to be of different origin. Palauqui et al. (1997) were the first to unambiguously demonstrate that silencing spreads from a silenced rootstock to a nonsilenced scion. They used as a stock a transgenic tobacco carrying an additional copy of the endogenous nitrate reductase gene, Nia. Some of the transgenic lines generated always showed higher levels of Nia transcripts than the wild type—as expected from the presence of an additional gene—and were termed class I lines. However, other transgenic lines had undergone silencing for both the endogenous and exogenous Nia genes and those were termed class II lines. Pallaqui et al. (1997) found that silenced class II rootstocks were able to silence class I scions. This was true even in a “sandwich graft,” where a wild-type (nontransgenic) segment was grafted between the silenced stock and the nonsilenced scion. Spreading of silencing was unidirectional from stock to scion. Though not explicitly stated, it was implied that it took more than 3 wk after grafting for systemic silencing to occur in the scion. The reported rate of transmission was 100%. Related experiments by Voinnet et al. (1998) used scions that transgenically expressed green fluorescent protein grafted onto plants with established silencing of the same transgene. There, too, silencing spread through the graft to the nonsilenced scion, even when a wild-type section was grafted between transgenic rootstock and scion. Unlike the Nia transgene, which has an endogenous counterpart in the wildtype plant, green fluorescent protein has no homolog in nontransgenic lines. Therefore, silencing spreading in the wild-type “spacer” in the sandwich grafts could not be assisted by an endogenous sequence. Rather, the systemic signal must have traveled all the way to the scion and induced gene silencing there. The establishment of systemic silencing took 4 wk in the “direct” grafts and 6 wk in the sandwich grafts. However, silencing spread to the scion only in some of the grafts: in ten out of 16 direct grafts and five out of 11 sandwich grafts. I found these papers were very important not only for what they proved—the existence of a systemic signal of silencing—but also because they gave an unequivocal answer to the scientific questions they posed, using relatively simple methodology. Although excited by these successful examples of the transmission of silencing, I kept coming back to two questions: (1) what prevents transmission in some of grafts, and (2) why does it take longer to transmit silencing to the scion than it takes systemic silencing to reach the most remote parts of an intact plant? When we started working on the silencing signal ourselves, we repeated some of the above experiments but found somehow lower efficiencies in the initiation of silencing in the scions. We soon realized that our results were influenced by the developmental stage of our scions. A paper from Jeff Meins's laboratory in Switzerland shed light on some aspects of the grafting puzzle. Researchers there introduced additional chitinase genes using bolistics, in sense or antisense orientation under the control of a strong promoter (35S) into chitinase transformant lines of tobacco that never exhibited spontaneous gene silencing (Crete et al. 2001). In lines bombarded late in plant development, triggering of silencing was rarely observed. However, when the transgene was introduced earlier in development, a large portion of the lines showed a substantial decrease and eventually full suppression of the chitinase mRNA levels. Lines that showed silencing were used as rootstocks and nonsilencing lines were used as scions in three types of grafting experiments. In the first type of grafting experiment, called top grafting, a 5-cm scion cut into a wedge at the bottom was inserted into the vascular ring at the cut surface of a 50-cm-high rootstock (Figure 1A). In the second type of experiment, reciprocal transverse grafts of 50-cm-tall plants were exchanged between class I and class II plants (Figure 1B). Finally, the third type of experiment involved plug grafts, which were made by exchanging transverse plugs of stems cut with a 5-mm-diameter cork borer from an internode approximately in the middle of a 50-cm plant (Figure 1C). Figure 1 Grafting Method May Influence the Spreading Efficiency of the Silencing Signal (According to Crete et al. 2001) (A) Top grafting, the most effective in transmitting the silencing signal. (B) Reciprocal transverse graft. (C) Plug graft. Surprisingly, only top grafting resulted in scions that were systemically silenced by a rootstock signal. Furthermore, even transmission after top grafting was less effective than expected; in one stock/scion combination only 27 out of 71 grafts exhibited transmission of the silencing signal. The authors also found that antisense-induced silencing was never transmitted to the scion. These findings do not answer the many questions about the mechanisms underlying systemic silencing, but they point us in certain directions. The individual parts of a whole plant are, in terms of import and export, in an equilibrium that changes with development. When grafting takes place, how this equilibrium is altered depends on the individual “parts” that contribute to the “new” whole plant. In addition, there is now indirect evidence (Fagard and Vaucheret 2000) that what is source tissue and what is sink tissue in terms of sugar transport affects what is source and what is sink in terms of the systemic silencing signal. Taking into account the above findings and choosing the right combination of stock/scion, we have managed to significantly increase the efficiency of graft-transmitted silencing, a prerequisite for continuing the search for the systemic signal. From the grafting experiments to date, it is now evident that the transporting capacity of the vascular tissue bypass that is formed at the graft junction does not fully reach the level of the original vascular tissue. The basis for these restrictions is not known. In a way, the graft interface functions as an unintentional filter. If the specificities of this “filter” were known, it would help us comprehend some transmission inconsistencies. Keeping in mind these limitations, grafting remains an invaluable tool in the search for the systemic silencing signal. Kriton Kalantidis is at the Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology–Hellas, Crete, Greece. E-mail: kriton@imbb.forth.gr Abbreviation Nianitrate reductase gene ==== Refs References Crete P Leuenberger S Iglesias VA Suarez V Schob H Graft transmission of induced and spontaneous posttranscriptional silencing of chitinase genes Plant J 2001 28 493 501 11849590 Fagard M Vaucheret H Systemic silencing signal(s) Plant Mol Biol 2000 43 285 293 10999411 Matzke MA Gene silencing mechanisms illuminate new pathways of disease resistance Transgenic Res 2002 11 637 638 12509139 Mlotshwa S Voinnet O Mette MF Matzke M Vaucheret H RNA silencing and the mobile silencing signal Plant Cell 2002 14 S289 S301 12045284 Palauqui JC Elmayan T Pollien JM Vaucheret H Systemic acquired silencing: Transgene-specific posttranscriptional silencing is transmitted by grafting from silenced stocks to non-silenced scions EMBO J 1997 16 17 4738 4745 2137 9303318 Palauqui JC Vaucheret H Transgenes are dispensable for the RNA degradation step of cosuppression Proc Natl Acad Sci U S A 1998 95 9675 9680 9689140 Sonoda S Nishiguchi M Graft transmission of posttranscriptional gene silencing: Target specificity for RNA degradation is transmissible between silenced and nonsilenced plants, but not between silenced plants Plant J 2000 21 1 8 10652145 Voinnet O Vain P Angell S Baulcombe DC Systemic spread of sequence-specific transgene RNA degradation in plants is initiated by localized introduction of ectopic promoterless DNA Cell 1998 95 177 187 9790525

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PLoS Biol. 2004 Aug 17; 2(8):e224

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PLoS Biol

10.1371/journal.pbio.0020224

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020225Research ArticleAnimal BehaviorNeuroscienceRattus (Rat)Forgetting, Reminding, and Remembering: The Retrieval of Lost Spatial Memory Forgetting, Reminding, and Rememberingde Hoz Livia livia.dehoz@charite.de 1 Martin Stephen J 1 Morris Richard G. M 1 1Laboratory for Cognitive Neuroscience, Centre and Division of NeuroscienceUniversity of Edinburgh, Edinburgh, ScotlandUnited Kingdom8 2004 17 8 2004 17 8 2004 2 8 e2253 3 2004 14 5 2004 Copyright: © 2004 de Hoz et al.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. How the Brain Retrieves Forgotten Memories Retrograde amnesia can occur after brain damage because this disrupts sites of storage, interrupts memory consolidation, or interferes with memory retrieval. While the retrieval failure account has been considered in several animal studies, recent work has focused mainly on memory consolidation, and the neural mechanisms responsible for reactivating memory from stored traces remain poorly understood. We now describe a new retrieval phenomenon in which rats' memory for a spatial location in a watermaze was first weakened by partial lesions of the hippocampus to a level at which it could not be detected. The animals were then reminded by the provision of incomplete and potentially misleading information—an escape platform in a novel location. Paradoxically, both incorrect and correct place information reactivated dormant memory traces equally, such that the previously trained spatial memory was now expressed. It was also established that the reminding procedure could not itself generate new learning in either the original environment, or in a new training situation. The key finding is the development of a protocol that definitively distinguishes reminding from new place learning and thereby reveals that a failure of memory during watermaze testing can arise, at least in part, from a disruption of memory retrieval. Teasing apart memory defects in animal models is not an easy task. A new protocol reveals that failure of memory can arise, at least in part, from a disruption of memory retrieval ==== Body Introduction For more than a century, the phenomenon of retrograde amnesia (RA)—the loss of memory for events that occur prior to a variety of precipitating brain insults—has provided the foundation for theories of memory consolidation and the locus of trace storage (McGaugh 1966; Davis and Squire 1984; Dudai and Morris 2000). However, RA may also reflect the inability of a memory system to access a trace—a failure of memory retrieval (Warrington and Weiskrantz 1968). This very dilemma was noted by Ribot (1883, p. 475) in his seminal discussion of RA: “Two suppositions are equally warranted, viz., that either the registration of the prior states has been effaced; or that the retention of the anterior states persisting, their aptitude for being revived by associations with the present is destroyed. We are not in a position to decide between these two hypotheses.” Studies of RA have favoured a memory-consolidation interpretation in instances in which systematic variation of the time interval between experience or training and the subsequent brain insult has revealed a temporal gradation of RA (Squire 1992). Computational models also point to the need for a rapid encoding and storage system, together with a slower interleaving mechanism that is thought to underlie systems-level consolidation and long-term storage in the cortex (e.g., McClelland et al. 1995). However, the existence of some amnesic patients with long, flat gradients of RA extending for years or decades into periods of their life when memory function was normal provided some of the first evidence that RA might be due to retrieval failure (Sanders and Warrington 1971). This perspective on RA was initially supported by studies indicating that, in the anterograde domain, impaired memory could be alleviated by partial cues (Warrington and Weiskrantz 1968). However, these observations were later construed as reflecting the operation of a separate memory phenomenon called priming (Graf et al. 1984). Several animal studies have also indicated that a variety of ‘reminder' treatments delivered prior to retention testing can realize the expression of lost memories (Gold et al. 1973; Miller and Springer 1973; Spear 1973; Gold and King 1974; Riccio and Richardson 1984; Sara 1999), but it is not easy to distinguish priming-induced memory from explicit recall and recognition in animal studies. Experimental resolution of the consolidation-versus-retrieval controversy has been notoriously difficult, and no consensus has been achieved. A key methodological issue, and the focus of the new technique described here, concerns the need to demonstrate that the memory observed after a reminder treatment results from the reactivation of an existing memory (Miller and Springer 1972), rather than a facilitation of new learning (Gold et al. 1973). In studies of spatial memory using the watermaze, amnesia for the location of the escape platform in posttraining probe trials (PTs) has generally been interpreted as a failure of learning, consolidation, or storage (D'Hooge and De Deyn 2001). To investigate the alternative possibility of retrieval failure, we deliberately created conditions that should maximize the possibility of seeing such an effect. This involved training rats to find an escape platform in a specific location followed by partial lesioning of the hippocampus. We reasoned that this would weaken but not completely disrupt the memory of the correct location by damaging a subset of the ensemble of stored traces. The animals' memory was tested and observed to be undetectable. This same memory test provided, however, the opportunity to remind animals that escape from the water was possible via an escape platform in the correct or incorrect location. One hour later, the animals' memory was tested again. We observed that memory was now detectably above chance and was equally strong when the animals had previously been given correct or potentially misleading information about the current location of the platform. Additional control procedures, and the performance of other groups with sham or complete hippocampal lesions, established that the earlier failure of memory must have been due, at least in part, to retrieval failure. Results A summary of the experimental design is provided in Figure 1 (see Materials and Methods). Figure 1 Experimental Design Outline of the different phases of testing. The platform position used during training is indicated by a red circle in the NE quadrant of the pool (large blue circle), although in practice platform locations were counterbalanced between NE and SW locations. The novel location, to which a subset of rats was exposed during reminding, is indicated by a black circle in the SW quadrant. This position was always opposite to that used during training. PT1 and PT2: probe test 1 and 2. The hatched areas represent the original training quadrant irrespective of the position of the platform (i.e., original or novel) during retention testing. PTn1 and PTn2: PTs during new context learning in the second pool. Training Prior to the Lesions During cued pretraining, the rats quickly learned to search for, and climb onto, the visually cued escape platform. In the main spatial training phase, the animals rapidly learned to locate and raise the platform in order to escape from the pool (Figure 2), as indicated by the highly significant reduction in latencies over trials (F[7.78, 412] = 30.4, p < 0.001). Only animals that reached the acquisition criterion received lesions (69 out of 73 rats trained). The prospective lesion groups, trained as normal animals, did not differ (F < 1, n = 59; see Surgery below). Figure 2 Training Mean latencies to escape from the water and climb onto the hidden platform during task acquisition. Data are averaged in blocks of five trials and grouped according to the lesion made at the end of training; note that all animals were unoperated during acquisition. Only rats that reached criterion (mean escape latency less than 15 s over the last ten trials) and whose lesions were considered acceptable (see Results: Surgery) are presented. Animals rapidly learned to locate the escape platform, and prospective lesion groups did not differ. Surgery Of the 69 animals that received lesions, one died after surgery and nine were excluded based on strict histological criteria, leaving a total of 59 animals (22 sham lesions, 19 complete hippocampal lesions, and 18 partial hippocampal lesions; see Figure 3). Figure 3 Lesion Analysis Representative photomicrographs of cresyl-violet-stained coronal brain sections taken from subjects belonging to each of the three lesion groups—partial hippocampal lesion (A), sham lesion (B), and complete hippocampal lesion (C). In each case, sections corresponding to anterior, middle, and posterior levels of the hippocampus are displayed. The mean area of spared hippocampal tissue in each group (see Materials and Methods for calculation) is plotted below in (D). Note that the volumes of spared tissue in the septal and temporal halves of the hippocampus are plotted separately, but these values are still expressed as percentages of the entire hippocampal volume—hence the value of 50% per half in shams. The cartoon hippocampi accompanying the graph indicate lesioned tissue in dark grey, and spared tissue in light cream. As intended, partially lesioned rats exhibited substantial sparing only in the septal (dorsal) half of the hippocampus, and rats with complete hippocampal lesions exhibited minimal sparing (less than 5% at either pole). Retention Testing The key new findings are shown in Figures 4 and 5 using two separate but related measures of memory retrieval: percentage time in quadrant (Figure 4) and a more sensitive measure, percentage time in a zone centred on the platform location (Figure 5; see Materials and Methods). An overall analysis of variance (ANOVA) of percentage time in the training (where the platform was located during training) and the opposite quadrants of the pool revealed a significant quadruple interaction (F[2, 53] = 7.66, p < 0.01) involving two between-subject factors: lesion group and platform location during the reminder treatment (original versus novel), and two within-subject factors: PT (PT1 and PT2) and quadrant (training versus opposite). In both figures, the initial memory expressed during PT1 is shown in the left lane. This reveals that the partially lesioned rats were at chance, whereas the sham-lesioned rats could remember the location of the platform (t = 6.15, df = 21, p < 0.005, paired-sample t-test, training versus opposite quadrant). The complete-lesioned animals were at chance. Analysis of percentage time in zone (Figure 5) likewise confirmed that memory was detectable in the sham lesion group (t = 4.18, df = 21, p < 0.005, one-sample t-test, comparison with chance = 50%), but not in the two lesion groups. Figure 4 Retention Testing: Quadrant Analysis Percentage time during PT1 and PT2 spent in the training and opposite quadrants of the pool (left and right lanes) and the reminder treatment (grey central lane). The training location is represented as a red circle in the NE quadrant, and the novel location (novel subgroups only) as a black circle in the SW quadrant. In practice, NE and SW quadrants were counterbalanced. Rats with partial hippocampal lesions were unable to remember the platform location on PT1 but could be reminded of the training location by exposure, at the end of PT1, to a platform in the original or a novel location. (Note that the ‘reminder' lane simply refers to this exposure to a platform—PT1 is itself the ‘reminder trial.') The key finding is that the improvement in PT2 occurred irrespective of the platform location during reminding. In contrast, sham-lesioned animals exhibited some reversal learning upon exposure to the platform in a novel location. Complete-lesioned rats did not remember the platform location during either PT1 or PT2. *p < 0.05; **p < 0.01; n.s. = nonsignificant; comparisons with chance = 50%; one-sample t-tests. Representative swim paths are included. Figure 5 Retention Testing: Zone Analysis Percentage time in PT1 (left) and PT2 (right) spent within a zone, 20 cm in radius, centred on either the original training location (broken circle; grey) or an equivalent location in the opposite quadrant (broken circle; yellow), expressed as a percentage of the total time spent in both of the zones. The reminder treatment is again shown as the grey central lane and as the location where the hidden platform became available at the end of PT1 within these zones (original = red; novel = black). Consistent with Figure 4, rats with partial hippocampal lesions were amnesic in PT1 but could be reminded of the correct location, even by exposure to the platform in a novel location. *p < 0.05; **p < 0.01; n.s. = nonsignificant; comparisons with chance = 50%; one-sample t-tests. PT1 ended with the animals finding the platform in the original training location, or in a novel location in the ‘opposite' quadrant of the pool (middle lane in Figures 4 and 5; see Materials and Methods for explanation of terminology). These different events at the end of the swim trial potentially served both as a reminder of what happens in a watermaze, namely, escape from the water at a particular location, and/or as an opportunity for new learning. We reasoned that if the reward of escaping from the water served only to support new learning, animals capable of learning would show an enhanced bias towards the training location after finding the platform in the original location, but a reduced bias after finding it in the opposite novel location. Conversely, if these events served only as reminder cues, they might be equally effective in reminding the rats of the original training location. The key new finding is that the partial lesion group displayed a bias for the training quadrant that was equivalent whether the animals had found the platform in the original training location or in the novel opposite location, at the end of PT1. The overall ANOVA of the PT2 quadrant data revealed a triple interaction of lesion group × quadrant (training versus opposite) × platform location during reminding (novel versus original) (F[2, 53] = 19.28, p < 0.001). With respect to the performance of the partial lesion group alone on this quadrant measure (see Figure 4, right lane), there was a significant improvement between PT1 and PT2 (F[1, 16] = 7.98, p < 0.02) and no difference between novel and original reminding locations (F < 1). The partial lesion group also showed a highly significant preference for the training quadrant versus the opposite quadrant on PT2 (F[1, 16] = 16.83, p < 0.001). The same pattern of results is apparent in the zone data (see Figure 5) where, overall, the partial lesion group displayed a significant improvement between PT1 and PT2 (F[1, 16] = 7.64, p < 0.02) that also did not differ between ‘novel' and ‘original' groups (F < 1). Because a bias for the training location appeared even in the animals that were exposed to a novel platform position, memory on PT2 cannot be attributed to relearning of the platform location. In contrast, sham-lesioned animals behaved quite differently in PT2 as a function of whether the platform was presented in the original or the novel location during the reminder treatment. Performance showed a further bias towards the training location between PT1 and PT2 following the event of climbing onto the escape platform in its original location, but exposure to the novel location resulted in a reduction in time spent in the training zone—a partial reversal. Supported by significant interactions in the overall ANOVA, analysis of time spent in the training quadrant revealed that, as expected, sham-lesioned animals reexposed to the original location increased their time there between PT1 and PT2 (F[1, 11] = 12.41, p < 0.005). Conversely, sham-lesioned animals exposed to the novel location exhibited modest reversal learning, increasing their time in the opposite quadrant (F[1, 9] = 9.35, p < 0.02). The same pattern of results was obtained from the analysis of time in the training zone (Figure 5), for which a significant interaction between PT (PT1 or PT2) and platform location during reminding (original versus novel) was observed (F[1, 20] = 5.46, p < 0.05). Complete-lesioned rats performed at chance during all PTs (see Figures 4 and 5, left and right lanes). That is, their behaviour during the retention tests before and after the reminder treatment showed no impact of that treatment. Novel Context Learning As an independent test of whether the reminder treatment of escape onto a platform could support new learning, all animals were taken to a second (‘downstairs') watermaze and given two PTs (Figure 6). This was a novel environment, and, therefore, there was no reason to expect the animals to perform at better than chance levels in the first of these PTs in a novel environment (PTn1). However, escape from the water at the end of this PT might be sufficient to support new one-trial learning. Such learning was absent in the partial hippocampal lesion group (F < 1). The sham lesion group, in contrast, did learn (F[1, 21] = 4.51, p < 0.05), performing significantly better than the lesioned groups on PTn2 (post hoc Ryan–Einot–Gabriel–Welsch range test, p < 0.005). The complete lesion group again showed no evidence of learning in a new environment (F < 1). Figure 6 Novel Context Learning Percentage time spent in the target quadrant containing the escape platform during one-trial new learning in a different pool. *p < 0.05; n.s. = nonsignificant; comparison of percentage time spent in training zone during PTn1 and PTn2; paired-sample t-tests. New learning was observed only in sham-lesioned rats. Discussion The key finding of this study is that rats with partial lesions of the hippocampus can be reminded of a preoperatively learned escape location in a watermaze by both correct and potentially misleading information. Whereas sham-lesioned rats showed new one-trial learning towards or away from the originally trained quadrant as a function of the type of reminder treatment to which they were exposed, partially lesioned animals were unable to learn. Instead, the first PT served only as a reminder of the original platform location irrespective of where in the pool the platform was raised at the end of this trial. Rats with complete hippocampal lesions showed neither new learning nor reminding. There is an extensive classic literature on the nature and effectiveness of reminder treatments (Riccio and Richardson 1984). Exposure to the training context, noncontingent stimuli, or additional training trials are just some examples of methods successfully used to remind animals of a prior training experience (Zinkin and Miller 1967; Miller and Springer 1973; Mactutus et al. 1979; Gisquet Verrier and Schenk 1994; Przybyslawski and Sara 1997). Controversy did, however, surround studies that interpreted memory following a reminder treatment as evidence that the original amnesia was the result of a retrieval deficit (Zinkin and Miller 1967; Miller and Springer 1973). It was argued that a reminding trial simply strengthens a weak memory that is behaviourally unobservable, similar to what happens during initial learning (Cherkin 1972; Gold et al. 1973; Haycock et al. 1973; Gold and King 1974), or that, when amnesia is complete, it results in one-trial learning or response generalization. However, manipulations that are unlikely to produce new learning can also serve as effective reminders. Examples include pharmacological manipulations of the internal state (Mactutus et al. 1980; Concannon and Carr 1982) and reexposure to the amnestic agent prior to retention testing (Thompson and Neely 1970; Hinderliter et al. 1975). In many such studies, however, the use of inhibitory avoidance as a memory test makes it difficult to determine the cognitive ‘content' (cf. Riccio and Richardson 1984) of the behaviour expressed during retention testing. Although memory reactivation may have occurred when a rat inhibits movement that previously led to electric shock, an alternative interpretation is that a generalized fear state has been induced. The issue of whether and when amnesia reflects a storage or retrieval deficit was, thus, left unresolved. Two features are distinctive about our study. First, unlike in many previous studies, the reactivated memory involves the recall and expression of highly specific information—a discriminable position in space, and not just a faster escape latency, or greater freezing. Second, despite exposure to a novel platform location leading to reversal learning in the sham lesion group, the partial lesion group displayed only reminding of the original platform location. This distinction is important because, with the current revival of interest in memory retrieval, our protocol circumvents the ambiguities involved in the use of relearning as an index of retention. One example of a study that used a reacquisition rather than a true reminding protocol (Land et al. 2000) revealed that a reminder prior to retention testing could alleviate amnesia in animals with hippocampal lesions. However, it is difficult to distinguish between ‘pure' reminding and the facilitation of new learning using reacquisition alone. Nonetheless, the watermaze task is deceptively complex, and successful performance depends on the operation of several distinct memory systems (Bannerman et al. 1995; Whishaw and Jarrard 1996; Warburton and Aggleton 1999; Eichenbaum 2000; White and McDonald 2002). Accordingly, while no new learning of the platform location occurs in the partial and complete lesion groups, some ‘procedural' learning may take place during PT1; this may enhance a weak, subthreshold spatial memory to a point at which it can be expressed in PT2. However, for this argument to be plausible, one would expect there to be minimal retention of the procedural components in PT1. This was clearly not the case, as rats with both partial and complete hippocampal lesions did not behave like naïve animals during PT1. They searched at an appropriate distance from the pool walls and readily climbed onto the escape platform when it was eventually made available. Procedural learning is also generally well retained over time and, being slow, unlikely to change much in one trial. We also doubt that the recovery of memory on PT2 reflects the emergence of latent memory mediated solely by an extrahippocampal structure, but not expressed during PT1. For example, rats with complete hippocampal lesions have been shown to learn a spatial conditioned-cued preference mediated by the amygdala (White and McDonald 1993), a form of memory that is partially masked by hippocampus-dependent learning in normal rats (McDonald and White 1995). However, seeing reminding in partial but not complete hippocampus-lesioned animals argues against this possibility in this case. Finally, the recovery of a simple stimulus–response strategy based on approaching single cues is unlikely, as novel start locations were always used during retention testing (cf. Eichenbaum et al. 1990; see Materials and Methods). Under these circumstances, it is reasonable to interpret the apparently complete amnesia observed in PT1 as, at least in part, a failure of spatial memory retrieval. Our use of partial hippocampal lesioning introduces several other issues. First, it is a technique that is arguably more relevant to human amnesia, in which damage to a structure is typically incomplete. Second, it is also relevant to the many studies in which a pharmacological intervention is applied at a single site within a brain region—microinfusion into the dorsal hippocampus, for instance, is likely to have minimal effects on ventral hippocampal tissue (see Steele and Morris 1999). Third, and perhaps most interesting, is the question of where memory traces are located. Given that reminding only occurs in partially lesioned rats, it is reasonable to suppose that spatial memory traces are either located (and reactivated) within the hippocampus, or that the hippocampus is required for the process of reactivation or expression of a reactivated memory stored elsewhere. According to the latter hypothesis, spatial memory traces might be stored in cortex but require fast synaptic transmission in the hippocampus to be retrieved (cf. Teyler and DiScenna 1986)—at least during the period after training and before the completion of systems-level consolidation. Alternatively, some hippocampal tissue might be required for cortically expressed memory to gain access to striatal motor planning and executive systems. Findings reported by Virley et al. (1999) suggest that this retrieval hypothesis might not be implausible. In this study, monkeys with CA1 pyramidal cell lesions were amnesic for a preoperatively acquired visuospatial discrimination. Subsequent grafting of CA1 pyramidal cells resulted in the recovery of memory for a second preoperatively acquired discrimination. As the grafted tissue cannot contain specific memory traces, the implication is that the recovery of some aspects of CA1 cellular function is sufficient for the information processing mediating the retrieval of memories stored elsewhere. In raising many more questions than they answer, the present findings open a potential avenue of research into the neural dynamics of memory reactivation and retrieval. Specific interventions such as local AMPA receptor blockade (cf. Riedel et al. 1999) might be directed at the hippocampus or cortex during PT1 or PT2. Such a study could provide information about the role of these structures—and their network interactions—in the reactivation of apparently lost memories, and in their subsequent retrieval. For example, hippocampal neural activity may be necessary for effective retrieval, but perhaps not for the reminding-induced reactivation of memory, even for an ostensibly hippocampus-dependent task (cf. Land et al. 2000). Similarly, the necessity for hippocampal neural activity during retrieval might vary as a function of time after memory consolidation. In addition, the determinants of the reminder phenomenon itself remain unclear. It would be useful to establish whether reinforcement in the form of an escape platform is, in fact, necessary during PT1, or indeed whether a reminder trial in a separate pool would have been effective. Experiments involving partial versus complete sets of cues might also provide valuable insights into the reminding process (cf. O'Keefe and Conway 1978). These and related analyses will be the subject of future studies. Dissociating the storage and retrieval functions of the hippocampus in memory is central to our understanding of the role of hippocampo–cortical connections. Many theories of hippocampal function are based on the idea that the hippocampus acts as a mediating link between different cortical regions during the interval before systems consolidation is complete (Teyler and DiScenna 1986; Squire and Alvarez 1995). Paradoxically, the same features that point to the alternative possibility—that the hippocampal formation is a site of encoding and long-term storage of complex multimodal memories within its distributed intrinsic circuitry (Moscovitch and Nadel 1998)—also place this group of structures in an ideal position to help reactivate memories from traces distributed over several cortical structures, perhaps via a mechanism such as pattern completion (see Marr 1971; Nakazawa et al. 2002). It is possible that, when the hippocampus is partially damaged and the cortico–hippocampal network is therefore degraded, retrieval is only possible once a more complete recreation of the training situation, possibly including reexposure to a platform, is provided. Although comparisons across different species and forms of memory should be viewed with caution, this scenario is reminiscent of Tulving's encoding specificity principle (Tulving and Pearlstone 1966; Thomson and Tulving 1970) in that exposure to similar cues during encoding and retrieval phases permits the recovery of the original memory, despite the provision of incorrect information about the target location itself. Paradoxically, the poor learning abilities of partially lesioned rats might explain why a trial ending with exposure to a novel spatial location can serve as a reminder for the original location—by limiting new learning of the new location, a reactivated memory for the old location is unmasked. Materials and Methods Subjects We used a total of 73 male Lister Hooded rats obtained from a commercial supplier (Charles River Laboratories, United Kingdom). They were pair-housed in plastic cages with sawdust bedding and ad libitum access to food and water. Their care and maintenance and all experimental procedures were carried out in accordance with United Kingdom Home Office Regulations. Behavioural testing was conducted using two separate circular pools, 2.0 m in diameter and 60 cm high, each located in well-lit rooms with numerous distal visual cues. One pool was used for training and retention (‘upstairs') and the other for new context learning (‘downstairs'). The pools were filled with water at 25 °C ± 1 °C made opaque by the addition of 200 ml of latex liquid (Cementone-Beaver, Buckingham, United Kingdom). We used the ‘Atlantis platform' (Spooner et al. 1994), a polystyrene platform that becomes available by rising from the bottom of the pool only if the animals swim to and stay within a specified ‘dwell radius' centred on the correct location for a predetermined ‘dwell time.' When risen, the top of the platform remained 1.5 cm below the water surface. The animals' swimming was monitored by an overhead video camera connected to a video recorder and an online data acquisition system (Watermaze, Watermaze Software, Edinburgh, United Kingdom; Spooner et al. 1994) located in an adjacent room. This system digitizes the path taken by an animal and computes various parameters such as escape latency, time spent in a zone overlying the platform, and other conventional measures of watermaze performance. Training protocol Testing was carried out according to the schedule illustrated in Figure 1. Cued pretraining This phase consisted of a single day of nonspatial cued training in the ‘upstairs' watermaze (curtains drawn around the pool to occlude extramaze cues, with ten trials in two sessions of five trials each (intertrial interval ≈ 20 min; intersession interval ≈ 3 h). The visible cue was suspended approximately 25 cm above the platform, which was moved every two trials to one of four possible locations, according to a pseudorandom schedule; the dwell radius was set at 20 cm, and the dwell time was 1 s. Training Training on a spatial reference memory task began 3 d later in the same watermaze. Rats received ten trials/day, in two sessions of five consecutive trials each (intersession interval ≈ 2 h), for 4 d. The dwell time was set to 0.5 s throughout training, but the dwell radius was gradually reduced over days (day 1: 20 cm; day 2: 15 cm; days 3 and 4: 13 cm). This schedule was intended to promote accurate and focused searching, but without generating the highly perseverative strategy that typically results from the use of long dwell times (Riedel et al. 1999). Rats were given a maximum of 120 s to find an escape platform located at the centre of either the NE or SW quadrant, after which they remained on the platform for 30 s On the rare trials in which a rat failed to escape within 2 min, the experimenter placed a hand above the correct location in order to guide the animal to the platform. For each animal, the platform position remained constant throughout training, but start locations (N, S, E, or W) were varied pseudorandomly across trials. Only those animals achieving the acquisition criterion of mean escape latencies of 15 s or less on day 4 of training proceeded to the next phase of testing. Surgery Surgery took place 1–2 d after the end of training. Rats were given either partial or complete bilateral neurotoxic lesions of the hippocampal formation (DG and CA fields), or sham surgery. Complete lesions were intended to remove 85% or more of the total hippocampal volume. Partial lesions targeted the temporal two-thirds of the hippocampus, sparing the septal (dorsal) third of the structure. The rats were assigned to groups of equivalent mean performance on the basis of their escape latencies during the final day of training. Lesions were made with ibotenic acid (Biosearch Technologies, Novato, California, United States; dissolved in 0.1 M phosphate-buffered saline [pH 7.4] at 10 mg/ml) following the protocol of Jarrard (1989). The animals were anaesthetized with an intraperitoneal injection of tribromoethanol (avertin) and placed in a Kopf Instruments (Tujunga, California, United States) stereotaxic frame such that Bregma and Lambda lay on the same horizontal plane. Rats received nine or 13 injections of ibotenic acid (partial and complete lesion groups, respectively; 0.05 μ1, 0.08 μ1, or 0.1 μ1 per injection) at different rostrocaudal and dorsoventral levels via an SGE syringe secured to the stereotaxic frame (see de Hoz et al. 2003). The injection rate was 0.1 μ1/min, and the needle was removed very slowly 90 s after the injection. A total of 0.65 μ1 or 0.91μ1 per hemisphere was necessary for the partial and complete lesions, respectively. The coordinates were modified from Jarrard (1989) to suit the slightly different brain size of Lister Hooded rats and to achieve the desired amount of partial hippocampal damage (see de Hoz et al. 2003). Sham lesions were made in the same way, with the injections replaced by a piercing of the dura (intended to cause comparable neocortical damage). Retention testing This phase began 14 d after the end of training. It consisted of two PTs (PT1and PT2) spaced 1 h apart, with a reminder treatment occurring at the end of PT1. Each PT (PT1 and PT2) began with a standard 60-s swim with the platform unavailable. In each PT, the rats were placed into the pool in either the adjacent right or the adjacent left quadrants with respect to the training quadrant. Start positions were counterbalanced across PTs and across rats. At the end of the 60 s the platform was raised and the animals were allowed to find and climb onto it. The rats were allowed a further 60 s to locate the platform once risen (but still hidden just below the water surface); if unsuccessful within this period, they were guided to the platform. They then remained on the platform for 30 s. The raising of the platform at the end of PT1 constituted the reminder treatment; thus PT1 is sometimes referred to as the ‘reminder trial.' A key variable was that the platform was raised in either the original training location (half the animals) or in a novel location in the centre of the opposite quadrant of the pool (the other half). Note that reminding using the original location always occurred in the training quadrant, and reminding using the novel location always occurred in the opposite quadrant. However, whereas the terms ‘training' and ‘opposite' are used to refer to physical areas of the pool, ‘novel' and ‘original' refer also to separate groups that received each type of reminder. For analysis of the different behavioural phases, several measures of performance were assessed, including escape latency, swim speed, and time spent within defined regions of the pool. Memory retention during PTs is inferred from the time spent in each quadrant of the pool as a percentage of the 60-s duration of the PT. A more sensitive measure can be obtained by analysing percentage time spent within a specified radius (zone) centred on the platform location (Moser and Moser 1998). When time in zone is presented, it is expressed as a percentage of the total time spent in both the original training zone and the novel opposite zone. Statistical analysis (SPSS, Chicago, Illinois, United States) began with an ANOVA followed by appropriate post hoc comparisons. Numerical data are reported as mean ± standard error (s.e.m.) throughout. Novel context learning New learning was assessed the next day in a separate ‘downstairs' watermaze that constituted a novel context. The protocol was identical to that used during ‘upstairs' retention testing, i.e., two rewarded PTs (PTn1 and PTn2) spaced 1 h apart. Lesion analysis At the end of behavioural testing, rats were perfused intracardially with saline followed by 10% formalin under terminal pentobarbitone anaesthesia (Euthatal, 1 ml). Their brains were removed and stored in 10% formalin for 24 h before being blocked and embedded in egg yolk. The embedding procedure is described in de Hoz et al. (2003). Coronal, 30-μm sections through the hippocampus and other structures were cut using a cryostat: every fifth section was recovered, mounted on a slide, and stained with cresyl violet (see Figure 3A–3C). The relative volume of spared tissue was calculated by measuring the area of hippocampus spared in each section of a particular brain according to the following protocol: Each coronal section containing hippocampus was placed under a photomacroscope (Wild, Heerbrugg, Switzerland), and the image taken by a mounted video camera was imported into NIH Image 1.63 (National Institutes of Health, Bethesda, Maryland, United States). The area of spared hippocampal tissue in each section was then outlined and automatically calculated. Surrounding fibres such as the fimbria were excluded on the grounds that they would not be considered in a section were all the hippocampal cells dead. The sections were spaced 150 μm apart, yielding up to 32 sections in a sham lesion animal, and fewer in animals with acceptable partial lesions. For each rat, the total hippocampal ‘volume' was calculated by adding the area of hippocampal tissue spared in each successive section. The proportion of hippocampus spared for each lesioned animal was expressed as a percentage of the mean hippocampal ‘volume' for sham-lesioned animals. Values for the left and right hippocampi were initially calculated separately and then averaged (see Figure 3D). Strict criteria for acceptance of a lesion were used. The lesion had to be confined to the hippocampus in all cases, and leave intact tissue volumes of 25%–50% in the septal hippocampus with minimal sparing (less than 10%) elsewhere in the structure in the case of partial lesions, or less than 15% total hippocampal sparing in the case of complete lesions. Animals with minimal subicular damage, typically located at medial levels of the structure, were accepted. We would like to thank Jane Knox for histology, Andrew Bernard for animal care, and David Foster for helpful discussion. This research was supported by a Medical Research Council (MRC) Programme Grant held by RGMM and an MRC Research Fellowship held by LdH. Conflicts of interest. The authors have declared that no conflicts of interest exist. Author contributions. LdH, SJM, and RGMM conceived and designed the experiments. LdH and SJM performed the experiments. LdH and SJM analysed the data. LdH, SJM, and RGMM wrote the paper. Academic Editor: Howard B. Eichenbaum, Boston University Citation: de Hoz L, Martin SJ, Morris RGM (2004) Forgetting, reminding, and remembering: The retrieval of lost spatial memory. PLoS Biol 2(8): e225. Abbreviations ANOVAanalysis of variance PTprobe trial PTnprobe trial in a novel environment RAretrograde amnesia ==== Refs References Bannerman DM Good MA Butcher SP Ramsay M Morris RGM Distinct components of spatial learning revealed by prior training and NMDA receptor blockade Nature 1995 378 182 186 7477320 Cherkin A Retrograde amnesia in the chick: Resistance to the reminder effect Physiol Behav 1972 8 949 955 Concannon JT Carr C Pre-test epinephrine injections reverse DDC-induced retrograde amnesia Physiol Behav 1982 9 443 448 Davis HP Squire LR Protein synthesis and memory: A review Psychol Bull 1984 96 518 559 6096908 de Hoz L Knox J Morris RGM Longitudinal axis of the hippocampus: Both septal and temporal poles of the hippocampus support watermaze spatial learning depending on the training protocol Hippocampus 2003 13 587 603 12921349 D'Hooge R De Deyn PP Applications of the Morris water maze in the study of learning and memory Brain Res Rev 2001 36 60 90 11516773 Dudai Y Morris RGM To consolidate or not to consolidate: What are the questions? 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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020232PrimerCell BiologyDevelopmentPhysiologyFrogsMammalsUnraveling the Molecular Basis for Regenerative Cellular Plasticity PrimerOdelberg Shannon J 8 2004 17 8 2004 17 8 2004 2 8 e232Copyright: © 2004 Shannon J. Odelberg.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. The Regenerative Plasticity of Isolated Urodele Myofibers and Its Dependence on Msx1 Identifying the molecular basis for the impressive regenerative capacities of some organisms may help us to devise effective methods for enhancing regeneration in mammals ==== Body The regeneration of lost body parts and injured organs has captured the human imagination since the time of the ancient Greeks. The deep-seated roots of this early fascination can be seen in Greek mythology. The many-headed Hydra nearly defeated the hero Heracles by growing two new heads for every one that Heracles cut off, and the liver of Prometheus, devoured by a ravenous eagle each night, regenerated every morning. Aristotle, who lived from 384–322 BC, noted that the tails of lizards and snakes, as well as the eyes of swallow-chicks, could regenerate (Aristotle 1965). This fascination became a legitimate area of scientific inquiry in 1712, when the French scientist René-Antoine Ferchault de Réaumur published his seminal work on crayfish limb and claw regeneration (Réaumur 1712). Soon thereafter, several other prominent scientists of the eighteenth century, including Abraham Trembley, Charles Bonnet, Peter Simon Pallas, and Lazzaro Spallanzani, discovered remarkable regenerative abilities in a variety of organisms. Hydra, earthworms, and planarians could regenerate their heads and tails (Pallas 1766; Lenhoff and Lenhoff 1986); salamanders could regenerate their limbs, tails, and jaws; premetamorphic frogs and toads could regenerate their tails and legs; slugs could regenerate their horns; and snails could regenerate their heads (Spallanzani 1769). This last discovery caused quite a stir in eighteenth-century France, leading to an “unprecedented assault” on snails as both naturalists and the general public participated in the quest for scientific knowledge by reproducing Spallanzani's intriguing results (Newth 1958). Stem Cells Versus Dedifferentiation During the nineteenth century and for most of the twentieth century, regeneration research primarily focused on the phenomenology of regeneration and its cellular basis. Many important discoveries were made during this period, which led in part to the general conclusion that progenitor cells are required for most regenerative processes. However, the origin of these progenitor cells varies between regenerating systems. In some cases, such as the regeneration of skin, blood, muscle, and bone in mammals and the replacement of lost tissues in the flatworm planarian, the progenitor cells pre-exist as reserve cells or stem cells that only need to be activated in response to injury or tissue depletion. In other cases, the progenitor cells can be created de novo through a process in which fully differentiated cells reverse their normal developmental processes and revert to proliferating progenitor cells. This latter process, known as cellular dedifferentiation, is especially prominent in vertebrates with exceptional regenerative abilities, such as salamanders. For example, during salamander limb regeneration, cells from muscle, bone, cartilage, nerve sheath, and connective tissues participate in the dedifferentiation process to form a pool of proliferating progenitor cells known as the regeneration blastema (Figure 1) (Chalkley 1954; Bodemer and Everett 1959; Hay and Fischman 1961; Wallace et al. 1974; Lo et al. 1993; Kumar et al. 2000). It has not yet been determined whether pre-existing stem cells or reserve cells also contribute to the pool of progenitor cells—nor whether the blastemal cells are multipotent (capable of differentiating into multiple cell types), are committed to a particular cell lineage, or are a mix of multipotent and committed progenitor cells. Regardless, these blastemal cells will later redifferentiate to form all the internal tissues of the regenerated limb other than the peripheral nerve axons. This extraordinary degree of cellular plasticity distinguishes those vertebrates that can replace entire anatomical structures, such as limbs, from vertebrates with more limited regenerative abilities. Figure 1 Dedifferentiation of Limb Cells During Salamander Limb Regeneration Brown nuclei are a result of BrdU incorporation during DNA synthesis, and therefore mark cells that are progressing through the cell cycle. Abbreviations: e, epidermis; d, dermis; m, muscle; b, bone; bl, blastema; aec, apical epithelial cap. (A) Unamputated right forelimb of a newt and coronal section of the stylopodium. The only cells actively synthesizing DNA are those in the basal layer of the epidermis (bone marrow cells also actively synthesize DNA in the unamputated limbs but are not shown here). Note the long myofibers in the nonregenerating newt limb and the distant spacing between the muscle nuclei. (B) Seven-day limb regenerate and coronal section of the distal regenerating tip. Note that the muscle cells have lost their normal architecture and that the nuclei are more closely spaced and have begun to synthesize DNA. (C) Twenty-one-day limb regenerate and coronal section of the distal regenerating tip. The nuclei of the blastema are spaced closely together, and many nuclei are actively synthesizing DNA. The bone is also being broken down in the vicinity of the blastema. The public has recently exhibited a renewed interest in regeneration research, due in large part to stem cell research, which has provided promising avenues for the field of regenerative medicine. In addition, celebrities such as Christopher Reeve and Michael J. Fox have given a human face to the many people who could benefit from effective regenerative therapies. The political, ethical, and religious controversies surrounding the use of human embryonic stem cells for therapeutic purposes have only served to increase the public's awareness of the promising potential of regenerative medicine. But this interest in using scientific knowledge to enhance the regenerative capacity in humans is not new. Spallanzani closed his 1768 monograph on regeneration, An Essay on Animal Reproductions, with a series of questions— which, except for the antiquated language, could be asked by citizens of the twenty-first century: But if the abovementioned animals, either aquatic or amphibious, recover their legs, even when kept on dry ground, how comes it to pass, that other land animals, at least such as are commonly accounted perfect, and are better known to us, are not endued with the same power? Is it to be hoped they may acquire them by some useful dispositions? [A]nd should the flattering expectation of obtaining this advantage for ourselves be considered entirely as chimerical? Although most of the current interest in regenerative medicine focuses on the potential benefits of either embryonic or adult stem cells, there are several investigators who are now taking an entirely different approach to the problem. These researchers think that although stem cells may offer some benefits in the relatively near future, a more comprehensive approach will be required to meet all of our regenerative needs. To achieve this goal, they must first learn how nature has already solved the problem of regeneration and then use this information to enhance the regenerative capacity in mammals. These studies seek to understand the biology of regeneration, especially the cellular and molecular mechanisms that govern regenerative processes. The experimental systems range from the unicellular protozoa to complex vertebrates, such as salamanders and mice. The Molecular Biology of Regeneration With the technological advances that followed the advent of molecular biology, researchers acquired the basic tools to begin to unravel the molecular basis for cellular plasticity and regeneration. However, progress in this arena has been slow, given that most organisms with marked regenerative abilities are not yet amenable to routine genetic manipulation. Recent advances, such as the application of mutagenic screens to study fin regeneration in zebrafish (Johnson and Weston 1995; Poss et al. 2002b) and the application of RNAi knockdown technology to study regeneration in planarians (Sanchez Alvarado and Newmark 1999; Newmark et al. 2003), are quite promising and could largely ameliorate this deficiency. Nevertheless, results from several recent studies have converged on a set of genes that appear to play an important role in regeneration, and evidence is accumulating that suggests some of these genes may function to control regenerative cellular plasticity. Three such genes are Msx1, BMP4, and Notch1. These genes encode, respectively, a transcriptional repressor, a signaling ligand, and a signaling cell surface receptor. Numerous studies over the past three decades have shown that mammals, including humans, can regenerate their digit tips provided the amputation plane is distal to the terminal phalangeal joint (Douglas 1972; Illingworth 1974; Borgens 1982; Singer et al. 1987). However, Msx1-deficient mice exhibit impaired fetal digit-tip regeneration, a phenotype that can be rescued in ex vivo cultures in a dose-dependent manner by application of exogenous BMP4 (Han et al. 2003). Recently, it has been demonstrated that Xenopus tadpoles are unable to regenerate their tails during a refractory period of development between stages 45 and 47 (Beck et al. 2003). If tails are amputated during this refractory period, genes that are normally expressed during the early stages of tadpole tail regeneration, such as BMP4, Msx1, and Notch-1, are not expressed. However, transgenic frogs carrying a hyperactive form of Msx1 or constitutively active ALK3 (a receptor for BMP4) are able to regenerate their tails during the refractory period. Transgenic frogs carrying a constitutively active Notch-1 receptor will regenerate their notochords and spinal cords but exhibit little or no muscle regeneration, suggesting that Notch-1 signaling alone cannot rescue complete regenerative capacity in frog tadpoles (Beck et al. 2003). Results from expression studies in a variety of organisms are consistent with these in vivo gene function studies. Msx genes are upregulated in regenerating salamander limbs and regenerating zebrafish fins and hearts (Simon et al. 1995; Poss et al. 2002a; Raya et al. 2003), while notch-1b and its ligand, deltaC, are upregulated during zebrafish heart and fin regeneration (Raya et al. 2003). Msx1 and Cellular Plasticity Although these functional and expression studies indicate that Msx1, Bmp4, and Notch-1 are important for a variety of regenerative processes, they do not address the mechanism by which these genes exert their effects. However, several in vitro studies suggest that Msx1 may be involved in regulating cellular plasticity. Ectopic expression of Msx1 can inhibit the differentiation of a variety of mesenchymal and epithelial progenitor cell types (Song et al. 1992; Hu et al. 2001), suggesting that this gene may play a role in maintaining cells in an undifferentiated state. Furthermore, Msx1 may be functioning not only to prevent differentiation of progenitor cells but also to induce dedifferentiation of cells that have already differentiated. Ectopic expression of Msx1 in mouse myotubes (differentiated muscle cells that are multinucleated and are able to contract), coupled with serum stimulation, can induce these multinucleated cells to reduce their levels of myogenic proteins and undergo a cell cleavage process that produces proliferating mononucleated cells (a process known as cellularization) (Odelberg et al. 2000). Clonal populations of these dedifferentiated cells can redifferentiate into cells expressing markers for cartilage, fat, and bone cells, as well as myotubes. These results suggest that the combination of ectopic Msx1 expression and serum stimulation can induce differentiated muscle cells to dedifferentiate into proliferating multipotent progenitor cells. Given this degree of cellular plasticity, it is not surprising that Msx1 can also induce muscle progenitor cells, known as myoblasts, to dedifferentiate to multipotent progenitor cells (Odelberg et al. 2000). Cellularization of myotubes and myoblast dedifferentiation can also be induced by at least two synthetic trisubstituted purines. Myoseverin is a trisubstituted purine that binds to and disassembles microtubules, leading to the cellularization of multinucleated myotubes (Rosania et al. 2000). The resulting mononucleated cells proliferate when stimulated with serum and redifferentiate into myotubes following serum starvation. A second trisubstituted purine, reversine, induces myoblasts to dedifferentiate into progenitor cells with adipogenic and osteogenic potential (Chen et al. 2004). Therefore, reversine and Msx1 appear to have a similar effect on mouse myoblasts, although no reports have yet addressed whether reversine might induce dedifferentiation of multinucleated myotubes. In this issue of PLoS Biology, Kumar et al. (2004) present data linking Msx1 function to microtubule disassembly during the process of salamander myofiber cellularization and fragmentation (myofibers are formed from myotubes and represent the completely mature form of the differentiated skeletal muscle cell). Their results suggest that Msx1 expression induces microtubule disassembly, which then leads to myofiber cellularization or fragmentation. If Msx1 function is markedly reduced in salamander myofibers by preventing the efficient synthesis of the Msx1 protein, cellularization or fragmentation of the myofiber is inhibited, suggesting that Msx1 is required for this process. Thus, this study complements previous work (Odelberg et al. 2000) showing that ectopic Msx1 expression, coupled with serum stimulation, is sufficient to induce cleavage, cellularization, and dedifferentiation of mouse myotubes. The two studies point to an essential role for Msx1 in regenerative cellular plasticity and when combined with previous in vivo studies, raise the possibility that BMP or Notch signaling might also play a role in this process. Results from these and other similar studies are beginning to give researchers a glimpse into the molecular mechanisms that control regeneration and cellular plasticity. With the new tools available to identify candidate genes and assess their function, the next few decades appear promising for scientists engaged in regeneration research. Elucidating the molecular basis for regeneration may prove to be an essential step in devising effective methods for enhancing regeneration in mammals and may well usher in a golden era for regenerative medicine. Accession Numbers The Mouse Genome Informatics (http://www.informatics.jax.org/) accession numbers of the genes discussed in this paper are ALK3 (MGI: 1338938), BMP4 (MGI: 88180), Msx1 (MGI: 97168), and Notch1 (MGI: 97363). The GenBank (http://www.ncbi.nih.gov/GenBank/) accession numbers of the genes discussed in this paper are deltaC (NM 130944), notch1b (Y10352), Ambystoma mexicanum Msx1 (AY525844), Danio rerio msxb (U16311; partial sequence), D. rerio msxc (NM 131272), Homo sapiens ALK3 (Z22535), and Mus musculus ALK3 (Z23154). Work in our laboratory on identifying newt genes that regulate cellular plasticity is supported by grants from the National Institutes of Health (R01NS43878 and R01NS43878S1). Shannon J. Odelberg is with the Cardiology Division of the Department of Internal Medicine at the University of Utah, Salt Lake City, Utah, United States of America. E-mail: odelberg@howard.genetics.utah.edu ==== Refs References Aristotle Peck AL Historia Animalium 1965 1 Cambridge Harvard University Press 239 Beck CW Christen B Slack JM Molecular pathways needed for regeneration of spinal cord and muscle in a vertebrate Dev Cell 2003 5 429 439 12967562 Bodemer CW Everett NB Localization of newly synthesized proteins in regenerating newt limbs as determined by radioautographic localization of injected methionine-S35 Dev Biol 1959 1 327 342 Borgens RB Mice regrow the tips of their foretoes Science 1982 217 747 750 7100922 Chalkley DT A quantitative histological analysis of forelimb regeneration in Triturus viridescens J Morphol 1954 94 21 70 Chen S Zhang Q Wu X Schultz PG Ding S Dedifferentiation of lineage-committed cells by a small molecule J Am Chem Soc 2004 126 410 411 14719906 Douglas BS Conservative management of guillotine amputation of the finger in children Aust Paediatr J 1972 8 86 89 5074173 Han M Yang X Farrington JE Muneoka K Digit regeneration is regulated by Msx1 and BMP4 in fetal mice Development 2003 130 5123 5132 12944425 Hay ED Fischman DA Origin of the blastema in regenerating limbs of the newt Triturus viridescens . An autoradiographic study using tritiated thymidine to follow cell proliferation and migration Dev Biol 1961 3 26 59 13712434 Hu G Lee H Price SM Shen MM Abate-Shen C Msx homeobox genes inhibit differentiation through upregulation of cyclin D1 Development 2001 128 2373 2384 11493556 Illingworth CM Trapped fingers and amputated finger tips in children J Pediatr Surg 1974 9 853 858 4473530 Johnson SL Weston JA Temperature-sensitive mutations that cause stage-specific defects in Zebrafish fin regeneration Genetics 1995 141 1583 1595 8601496 Kumar A Velloso C Imokawa Y Brockes J The regenerative plasticity of isolated urodele myofibers and its dependence on Msx1 PLoS Biol 2004 2 e218 10.1371/journal.pbio.0020218 15314647 Kumar A Velloso CP Imokawa Y Brockes JP Plasticity of retrovirus-labelled myotubes in the newt limb regeneration blastema Dev Biol 2000 218 125 136 10656757 Lenhoff SG Lenhoff HM Hydra and the birth of experimental biology—1744: Abraham Trembley's memoirs concerning the natural history of a type of freshwater polyp with arms shaped like horns 1986 Pacific Grove (California) Boxwood Press 192 Lo DC Allen F Brockes JP Reversal of muscle differentiation during urodele limb regeneration Proc Natl Acad Sci U S A 1993 90 7230 7234 8346239 Newmark PA Reddien PW Cebria F Sanchez Alvarado A Ingestion of bacterially expressed double-stranded RNA inhibits gene expression in planarians Proc Natl Acad Sci U S A 2003 100 Suppl 1 11861 11865 12917490 Newth DR Johnson ML Abercrombie M Fogg GE New (and better?) parts from old New Biology 1958 Harmondsworth (United Kingdom) Penguin Books 47 62 Odelberg SJ Kollhoff A Keating MT Dedifferentiation of mammalian myotubes induced by msx1 Cell 2000 103 1099 1109 11163185 Pallas PS Miscellanea zoologica, quibus novae imprimis atque obscurae animalium species describuntur et observationibus iconibusque illustrantur 1766 Hagae Comitum (Holland) Petrum van Cleef 224 Poss KD Wilson LG Keating MT Heart regeneration in zebrafish Science 2002a 298 2188 2190 12481136 Poss KD Nechiporuk A Hillam AM Johnson SL Keating MT Mps1 defines a proximal blastemal proliferative compartment essential for zebrafish fin regeneration Development 2002b 129 5141 5149 12399306 Raya A Koth CM Buscher D Kawakami Y Itoh T Activation of Notch signaling pathway precedes heart regeneration in zebrafish Proc Natl Acad Sci U S A 2003 100 Suppl 1 11889 11895 12909711 Réaumur RAF Sur les diverses reproductions qui se font dans les écrevisses, les omars, les crabes, etc. et entr'autres sur celles de leurs jambes et de leurs écailles Mém Acad Roy Sci 1712 223 245 Rosania GR Chang YT Perez O Sutherlin D Dong H Myoseverin, a microtubule-binding molecule with novel cellular effects Nat Biotechnol 2000 18 304 308 10700146 Sanchez Alvarado A Newmark PA Double-stranded RNA specifically disrupts gene expression during planarian regeneration Proc Natl Acad Sci U S A 1999 96 5049 5054 10220416 Simon HG Nelson C Goff D Laufer E Morgan BA Differential expression of myogenic regulatory genes and Msx-1 during dedifferentiation and redifferentiation of regenerating amphibian limbs Dev Dyn 1995 202 1 12 7703517 Singer M Weckesser EC Geraudie J Maier CE Singer J Open finger tip healing and replacement after distal amputation in Rhesus monkey with comparison to limb regeneration in lower vertebrates Anat Embryol (Berl) 1987 177 29 36 3439635 Song K Wang Y Sassoon D Expression of Hox-7.1 in myoblasts inhibits terminal differentiation and induces cell transformation Nature 1992 360 477 481 1360150 Spallanzani L Maty M An Essay on Animal Reproductions Translation of: Prodromo di un opera da imprimersi sopra la riproduzioni animali 1769 London T. Becket 86 Wallace H Maden M Wallace BM Participation of cartilage grafts in amphibian limb regeneration J Embryol Exp Morphol 1974 32 391 404 4463210

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020234Research ArticleGenetics/Genomics/Gene TherapyVirologyVirusesHomo (Human)Retroviral DNA Integration: ASLV, HIV, and MLV Show Distinct Target Site Preferences Retroviral Integration Targeting in HumansMitchell Rick S 1 Beitzel Brett F 1 Schroder Astrid R. W 2 Shinn Paul 3 Chen Huaming 3 Berry Charles C 4 Ecker Joseph R 3 Bushman Frederic D bushman@mail.med.upenn.edu 1 1Department of Microbiology, University of Pennsylvania School of MedicinePhiladelphia, Pennsylvania, United States of America2Gen-Probe, San DiegoCalifornia, United States of America3Genomic Analysis Laboratory, The Salk InstituteLa Jolla, California, United States of America4Department of Family/Preventive Medicine, University of California at San Diego School of MedicineSan Diego, CaliforniaUnited States of America8 2004 17 8 2004 17 8 2004 2 8 e23420 2 2004 24 5 2004 Copyright: © 2004 Mitchell et al.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. Retrovirus Integration into the Human Genome The completion of the human genome sequence has made possible genome-wide studies of retroviral DNA integration. Here we report an analysis of 3,127 integration site sequences from human cells. We compared retroviral vectors derived from human immunodeficiency virus (HIV), avian sarcoma-leukosis virus (ASLV), and murine leukemia virus (MLV). Effects of gene activity on integration targeting were assessed by transcriptional profiling of infected cells. Integration by HIV vectors, analyzed in two primary cell types and several cell lines, strongly favored active genes. An analysis of the effects of tissue-specific transcription showed that it resulted in tissue-specific integration targeting by HIV, though the effect was quantitatively modest. Chromosomal regions rich in expressed genes were favored for HIV integration, but these regions were found to be interleaved with unfavorable regions at CpG islands. MLV vectors showed a strong bias in favor of integration near transcription start sites, as reported previously. ASLV vectors showed only a weak preference for active genes and no preference for transcription start regions. Thus, each of the three retroviruses studied showed unique integration site preferences, suggesting that virus-specific binding of integration complexes to chromatin features likely guides site selection. Retroviruses have potential for gene therapy only if they do not activate endogenous genes. Of three tested retroviral vectors, ASLV showed no preference for integration into human transcription start regions ==== Body Introduction Retroviral replication requires reverse transcription of the viral RNA genome and integration of the resulting DNA copy into a chromosome of the host cell. A topic of long standing interest has been the chromosomal and nuclear features dictating the location of integration target sites (reviewed in Coffin et al. 1997; Bushman 2001). Integration site selection has also gained increased interest because of its importance for human gene therapy. Retroviral vectors have been used extensively to deliver therapeutic genes carried in retroviral backbones. However, retroviral integration can take place at many locations in the genome, on occasion resulting in insertional activation of oncogenes (reviewed in Coffin et al. 1997; Bushman 2001). Recently, two patients undergoing gene therapy for X-linked severe combined immunodeficiency developed leukemia-like illnesses associated with integration of a therapeutic retroviral vector in or near the LMO2 proto-oncogene (Check 2002; Hacein-Bey-Abina et al. 2003). Insertional activation of oncogenes by retroviral vectors has also been detected in animal models (Li et al. 2002). With the availability of the complete human genome sequence, large-scale sequence-based surveys of integration sites have become possible (Schroder et al. 2002; Laufs et al. 2003; Wu et al. 2003). Schroder et al. (2002) investigated targeting of human immunodeficiency virus (HIV) and HIV-based vectors in a human lymphoid cell line (SupT1) and found that genes were favored integration targets. Global analysis of transcription in SupT1 cells showed that active genes were favored for integration, particularly those that were active after infection with the HIV-based vector. Wu et al. (2003) examined targeting of murine leukemia virus (MLV) in human HeLa cells and found that MLV does not strongly favor integration in transcription units, but rather favors integration near sequences encoding mRNA 5′ ends. Here we contrast integration targeting by three retroviruses, avian sarcoma-leukosis virus (ASLV), HIV, and MLV, taking advantage of 1,462 new integration site sequences and matched transcriptional profiling data. We find that ASLV does not favor integration near transcription start sites, nor does it strongly favor active genes. For HIV, we find that active genes are favored for integration in two primary cell types, extending findings from previous studies of transformed cell lines. Cell-type-specific transcription was found to result in cell-type-specific biases in integration site placement. We also reanalyzed the MLV data from Burgess and coworkers (Wu et al. 2003) in parallel, confirming that MLV integration is favored near transcription start sites. Thus it appears that each retrovirus studied to date has a unique pattern of integration site selection within the human genome, suggesting that there may be local recognition of chromosomal features unique to each virus. Results Integration Site Datasets Used in this Study The origins of the 3,127 integration sites studied are summarized in Table 1. All were generated by acute infection of cells with retroviruses or with viruses generated from retroviral vectors. To isolate integration sites, DNA from infected cells was isolated, cleaved with restriction enzymes, then ligated to DNA linkers. Integration sites were amplified using one primer that bound to the viral DNA end and another that bound the linker, then amplification products were cloned and sequenced (Schroder et al. 2002; Wu et al. 2003). Integration sites were mapped on the draft human genome sequence (Figure 1) and local features at integration sites quantified. Figure 1 Relationship between Integration Sites and Transcriptional Intensity in the Human Genome The human chromosomes are shown numbered. HIV integration sites from all datasets in Table 1 are shown as blue “lollipops”; MLV integration sites are shown in lavender; and ASLV integration sites are shown in green. Transcriptional activity is shown by the red shading on each of the chromosomes (derived from quantification of nonnormalized EST libraries, see text). Centromeres, which are mostly unsequenced, are shown as grey rectangles. Table 1 Integration Site Datasets Used in This Study DOI: 10.1371/journal.pbio.0020234.t001 Three integration site datasets were newly determined in this study. Integration by an ASLV vector was analyzed in 293T-TVA cells, which are human 293T cells engineered to express the subgroup A avian retrovirus receptor. Integration by an HIV-based vector was characterized in two types of primary human cells, peripheral blood mononuclear cells (PBMCs) and IMR90 lung fibroblasts. Several previously described datasets were also subjected to further analysis in parallel—HIV integration sites in three transformed cell lines (SupT1 [Schroder et al. 2002], H9, and HeLa [Wu et al. 2003]) and MLV integration sites in HeLa cells (Wu et al. 2003). The use of restriction enzymes to cleave cellular DNA during the cloning of integration sites could potentially introduce a bias in favor of isolating integration events closer to restriction sites. Previous work suggested that integration site surveys were not strongly biased. In one study, an experimental control based on integration in vitro indicated that the cloning and analytical methods used did not detectably bias the conclusions (Schroder et al. 2002). In addition, HIV integration sites cloned by different methods showed a similar preference for active genes (Carteau et al. 1998; Schroder et al. 2002; Wu et al. 2003), including sites isolated using several different restriction enzymes to cleave cellular DNA prior to linker ligation, and isolation using inverse PCR instead of ligation-mediated PCR. In this study we have added a computational method to address possible biased isolation. Each integration site was paired with ten sites in the human genome randomly selected in silico that were constrained to be the same distance from a restriction site of the type used for cloning as the experimentally determined integration site. Statistical tests were then carried out by comparing each experimentally determined integration site to the ten matched random control sites. In this way any bias due to the placement of restriction sites in the human genome was accounted for in the statistical analysis. All the collections of integration sites were analyzed in this manner, including data previously published in (Schroder et al. 2002; Wu et al. 2003). However, direct analysis of the distribution of integration sites without this correction yielded generally similar conclusions, suggesting that restriction site placement did not introduce a strong bias. A detailed description of the statistical analysis is presented in Protocol S1 (p. 2). Integration in Transcription Units For HIV the frequency of integration in transcription units ranged from 75% to 80%, while the frequency for MLV was 61% and for ASLV was 57%. For comparison, about 45% of the human genome is composed of transcription units (using the Acembly gene definition). Analysis using the different catalogs of human genes suggests that somewhat different fractions of the human genome are transcribed, and new information indicates that an unexpectedly large fraction of the human genome may be transcribed into noncoding RNAs (Cawley et al. 2004). However, for comparisons using any catalog of the human genes, the rate of integration in human transcription units determined experimentally was substantially higher than in the matched random control sites (Protocol S1, p. 3–11). We next assessed the placement of integration sites within genes and intergenic regions. A previous study revealed that integration by MLV is favored near transcription start sites, but no such bias was seen for HIV (Wu et al. 2003). We investigated this issue for ASLV and reanalyzed all of the available data by comparison to the matched random control dataset (Figure 2). For sites within genes, MLV showed a highly significant bias in favor of integration near transcription start sites (p = 1.4 × 10−14). No such bias was seen for ASLV (p > 0.05). For the HIV datasets, two of the four sets showed modest bias (HIV/PBMC, p = 0.0007; HIV/H9 and HeLa combined, p = 0.027). For HIV, the observed statistical significance was sensitive to the details of analytical approach used and is of questionable biological importance. Thus, ASLV and HIV do not strongly favor integration at transcription start sites as was seen with MLV. Figure 2 Integration Intensity in Genes and Intergenic Regions Genes or intergenic regions were normalized to a common length and then divided into ten intervals to allow comparison. The number of integration sites in each interval was divided by the number of matched random control sites and the value plotted. A value of one indicates no difference between the experimental sites and the random controls. Viruses and cell types studied are as marked above each graph. The direction of transcription within each gene is from left to right. Note that our normalization method de-emphasizes favored MLV integration events just upstream of gene 5′ ends (outside transcription units), as reported by Wu et al. (2003). We carried out an analysis specially designed to identify this effect and confirmed that the regions just upstream of gene 5′ ends are favored for MLV integration when reanalyzed with the matched random control data (unpublished data). Effects of Transcriptional Activity on Integration Transcriptional profiling analysis was carried out in some of the cell types studied, allowing the influence of transcriptional activity on integration site selection to be assessed. Transcriptional profiling was carried out on infected cells so that the data reflected the known influence of infection on cellular gene activity (Corbeil et al. 2001; Schroder et al. 2002; Mitchell et al. 2003; van 't Wout et al. 2003). Prior to isolating RNA for microarray analysis, the SupT1, PBMC, and IMR90 cells were each infected with the HIV-based vector used for HIV integration site isolation. The 293T-TVA cells were infected with the RCAS ASLV vector prior to RNA isolation. RNA samples were harvested 24–48 h after infection. For analysis of MLV and HIV integration sites in HeLa cells, published transcriptional profiling data from uninfected cells were used (Tian et al. 2002). The median expression level (average difference value) of genes hosting integration events was consistently higher than the median of all genes assayed on the microarrays. The ratios (targeted genes/all genes assayed) for HIV ranged from 1.6 to 3.0, indicating that integration targeting in human primary cells (PBMC and IMR90) favored active genes, as shown previously for transformed cell lines (Schroder et al. 2002; Wu et al. 2003). For MLV and ASLV the ratios were each 1.3, lower than for HIV but still greater than the chip average. The analysis shown in Figure 3 reveals that the association of integration sites with gene activity was statistically significant for all the HIV datasets. For MLV and ASLV, there was a weak tendency for integration to favor active genes, but the trend did not achieve statistical significance. Figure 3 Influence of Gene Activity on Integration Frequency Expression levels were assayed using Affymetrix HU-95Av2 or HU-133A microarrays and scored by the average difference value as defined in the Affymetrix Microarray Suite 4.1 software package. All the genes assayed by the chip were divided into eight “bins” according to their relative level of expression (the leftmost bin in each panel is lowest expression levels and the rightmost the highest). Genes that hosted integration events were then distributed into the same bins, summed, and expressed as a percent of the total. The y-axis indicates the percent of all genes in the indicated bin. P values were determined using the Chi-square test for trends by comparison to a null hypothesis of no bias due to expression level. All average difference values were ranked prior to analysis, and the analysis was carried out on the ranked data. This was done to avoid possible complications due to differential normalization or other data processing differences arising during work up of the microarrays. All three HIV datasets showed reduced integration in the most highly expressed category of genes analyzed, suggesting that although transcription favors integration, very high level transcription may actually be less favorable (Figure 3). A fourth dataset monitoring infection by an HIV-based vector in a T-cell line also showed this trend (M. Lewinski, P. S., J. R. E., and F. D. B., unpublished data). Possibly this finding is related to that of a previous study of integration by ALV in a model gene that also suggested that high level transcription may disfavor integration (Weidhaas et al. 2000). Tissue-Specific Transcription Results in Tissue-Specific Biases in HIV Integration Site Selection We next investigated the effects of cell-type-specific transcription on integration site selection. For this analysis we used only the three HIV integration site datasets for which we had transcriptional profiling data from infected cells (i. e., SupT1, PBMC, and IMR90), to allow us to control for the effects of infection on transcription. Pairwise comparisons of the microarray datasets for the three cell types showed that the correlation coefficients ranged only from 0.64 to 0.79, indicating that transcriptional activity indeed differed among cell types. We reasoned that since active transcription favors integration, then the genes targeted by integration should on average be more highly expressed in the cell type that hosted the integration event than in either of the other two. Statistical analysis (Figure 4) showed that transcription of targeted genes was higher on average in the cell type hosting the integration event than in either of the other two tested (all comparisons attain p < 0.05 using the Chi-square test for linear trend in proportions). We note, however, that the differences were quantitatively modest, perhaps because much of the cellular program of gene activity is shared among many cell types (Caron et al. 2001; Mungall et al. 2003; Versteeg et al. 2003). Figure 4 Effects of Tissue-Specific Transcription on Integration Site Selection in Different Cell Types Genes hosting integration events by the HIV vector were analyzed for their expression levels in transcriptional profiling data from IMR90, PBMC, and SupT1 cells. For each gene hosting an integration event, the expression values from the three cell types were then ranked lowest (red), medium (orange), and highest (yellow). The values were summed and displayed separately for each set of integration sites: (A) IMR90 sites, (B) PBMC sites, and (C) SupT1 sites. In each case there was a significant trend for the cell type hosting the integration events to show the highest expression values relative to the other two (p < 0.05 for all comparisons). Integration Site Selection and Transcriptional Domains We next analyzed factors influencing the placement of integration sites at the chromosomal level, taking into account both gene density and expression (see Figure 1). Transcriptional activity was quantified by counting the EST sequence copies for each gene present in a collection of nonnormalized EST libraries (Mungall et al. 2003). EST sequences from many tissues were used to build up the map of transcriptional activity, thus focusing the analysis on transcriptional patterns common to many cell types (Caron et al. 2001; Mungall et al. 2003; Versteeg et al. 2003). A detailed comparison of the relationship between EST frequency and integration frequency of HIV, MLV, and ASLV is shown for Chromosome 11 in Figure 5. Integration frequency for HIV closely parallels the transcriptional intensity deduced from EST counts. Fewer sites are available for analyzing MLV and ASLV, but MLV may show a related trend, while it is unclear whether ASLV does so or not. Similar analysis of the other human chromosomes yields similar conclusions (unpublished data). Figure 5 Comparison of Transcriptional Intensity to Integration Intensity on Human Chromosome 11 All data were quantified in 2-Mb intervals. The top line shows summed EST data documenting the “transcriptional intensity” for each chromosomal interval (data from Mungall and al. [2003]). The bottom three lines show the summed frequency of integration site sequences in each interval. The numbers of ESTs (top) or integration sites (bottom three) are shown on the y-axis. Statistical analysis was carried out comparing integration frequencies to (1) gene density or (2) transcriptional intensity, as measured by the EST counts. All analyses incorporated a comparison to the matched random control set of integration sites. Each type of vector showed a significant positive correlation with gene density (HIV, p = 1.8 × 10−12 to 3.2 × 10−38, depending on the dataset; MLV, p = 2.4 × 10−22; ASLV, p = 3.2 × 10−9) and a stronger association with transcriptional intensity (HIV, p = 3.8 × 10−19 to 9.7 × 10−46; MLV, p = 5.1 × 10−35; ASLV, p = 1.7 × 10−11). Overall, ASLV showed the weakest association with gene density and transcriptional intensity. Thus, the analysis of transcriptional activity in the context of chromosomal location revealed significant effects of transcription on MLV and ASLV integration. This is in contrast to the study based on transcriptional profiling alone, in which the effect was not statistically significant—however, a similar trend was evident and the general conclusions similar (see Figure 3). It appears that adding information on chromosomal position to the gene expression data allowed quantitatively modest effects to reach statistical significance. Substructures within Chromosomal Regions Favorable for Integration Two lines of evidence indicated that the chromosomal regions favorable for integration can be subdivided into favorable and unfavorable segments. In the first study, a computational analysis was carried out to determine the length of the chromosomal segments yielding the best fit between transcriptional intensity and integration intensity. The sizes of the chromosomal regions analyzed were varied systematically from 25 kb to 32,000 kb, and the statistical significance determined for the correlations. This analysis revealed that the segment length yielding the best correlation was comparatively short, around 100–250 kb, the length of one or a few human genes. These conclusions held for HIV, ASLV, and MLV (Protocol S1, p. 16–65). An analysis of integration frequency near CpG islands also indicated substructure within regions favorable for integration. CpG islands are chromosomal regions enriched in the rare CpG dinucleotide. These regions commonly correspond to gene regulatory regions containing clustered transcription factor binding sites—consequently, CpG islands are more frequent in gene-rich regions. Previously Wu et al. (2003) reported that CpG islands were positively associated with MLV integration sites but that for HIV integration sites there was no influence. An analysis of the effects of proximity to CpG islands on integration frequency incorporating the matched random control dataset is shown in Figure 6. The relative integration frequency near CpG islands was found to be much higher than expected by chance for MLV, as reported previously, and slightly higher than expected by chance for ASLV. For HIV, the region surrounding CpG islands was actually disfavored, and this was statistically significant in three out of four datasets. Thus for HIV, broadly favorable gene-dense chromosomal regions actually contain a mixture of favorable clusters of active genes and unfavorable CpG islands. For MLV, in contrast, CpG islands are quite favorable. Figure 6 The Effects of Proximity to CpG Islands Differs for HIV, MLV, and ASLV Integration The viral vectors and cell types studied are indicated by color. A value of one indicates no bias, less than one indicates disfavored integration, and more than one indicates favored integration. The x-axis (from plus or minus 1 kb to 50 kb) indicates distance from the edge of a CpG island in either direction along the genome. The statistical analysis specifically removed the favorable effects of being in a gene and being in a region containing expressed genes to highlight the effects of CpG islands alone. When effects of gene density and activity are left in, HIV integration goes from disfavored at short distances (less than 1 kb) to favored at longer distances (more than 10 kb). This is because at longer distances the association with genes is significant—many CpG islands are within 10 kb of a gene, and genes are favored targets for HIV integration. To carry out this analysis, the numbers of experimentally determined and matched control sites were fitted according to whether they were near a CpG island, whether they were in genes, and the level of the expression density variable. Each variable contributes a “multiplier” for the ratio of the number of experimental to control sites. The multiplier for “near CpG island” is shown (see Protocol S2, p. 9–12). High gene density in the human chromosomes is known to correlate with several other features, including high levels of gene expression, high densities of CpG islands, the occurrence of Giemsa-light chromosomal bands, and high G/C content (Caron et al. 2001; Lander et al. 2001; Venter et al. 2001; Mungall et al. 2003; Versteeg et al. 2003). The effects of chromosomal banding pattern and G/C content were analyzed statistically and found to favor integration, as expected from the correlation with other favorable features (Protocol S2). A Quantitative Model for Integration Intensity A statistical model was constructed to examine the relative contributions to integration intensity of (1) gene density, (2) gene activity, (3) proximity to CpG islands, (4) G/C content, and (5) location within genes (Protocol S2, p. 13–15). Inclusion of each of these parameters improved the fit of the model to the observed experimental datasets, but the quantitative contribution of each parameter varied among the different retrovirus types. The effects of being in a gene or a region with many expressed genes were most important for HIV and ASLV. For MLV, the distance from the transcription start site was the most important parameter. ASLV differed significantly from each of the other datasets (p < 0.0001), and the model based on the above parameters predicted the placement of ASLV integration sites least well. Thus ASLV is least responsive to the effects of the parameters so far known to affect integration site selection in human cells. Integration Frequency in the Individual Human Chromosomes Figure 7 presents the frequency of integration in each of the different human chromosomes for HIV, MLV, and ASLV. For HIV, each of the datasets is shown separately. A statistical analysis was carried out comparing the observed frequency of integration in each chromosome to that expected from the matched random control (Protocol S1, p. 3). As can be seen from the figure, the frequencies were quite different among the different chromosomes. For example, the gene-rich Chromosome 19 showed more integration than expected by chance, while the gene-poor Chromosome 18 showed less integration. The differences in integration frequencies among chromosomes are in part a function of gene density. However, for unknown reasons, the datasets also differed significantly from each other (p < 2.22 × 10−16). Evidently there are factors—so far unknown—affecting integration targeting that operate at the level of whole chromosomes(a conclusion also reached by Laufs et al. [2003]). Figure 7 Frequency of Integration in Human Chromosomes Human chromosome numbers are indicated at the bottom of the figure. The number of integration events detected in each chromosome was divided by the number expected from the matched random control. The line at one indicates the bar height expected if the observed number of integration events matched the expected number. Higher bars indicate favored integration, lower bars, disfavored integration. Most of the cell types studied were from human females; too little data were available for the Y chromosome for meaningful analysis. Discussion We report that ASLV, MLV, and HIV have quite different preferences for integration sites in the human chromosomes. HIV strongly favors active genes in primary cells as well as in transformed cell lines. MLV favors integration near transcription start regions and favors active genes only weakly. ASLV shows the weakest bias toward integration in active genes and no favoring of integration near transcription start sites. We expect that these same patterns will be seen for MLV and ASLV integration in different human cell types, because all four HIV datasets yielded similar results, though more data on additional cell and tissue types will be helpful to further evaluate the generality. One of the earliest models for chromosomal influences on integration targeting proposed that condensed chromatin in inactive regions disfavored integration, thereby concentrating integration in more open active chromatin (Panet and Cedar 1977; Vijaya et al. 1986; Rohdewohld et al. 1987). Integration by HIV, ASLV, and MLV all showed at least a weak bias in favor of integration in active genes, consistent with the idea that open chromatin at active genes favors integration. Also consistent with this idea, heterochromatic regions at human centromeres and telomeres were found to disfavor integration. However, it seems unlikely that relative accessibility is the only feature directing integration site selection, because HIV, ASLV, and MLV each show such distinctive target sequence preferences. Studies of the Ty retrotransposons of yeast, close relatives of retroviruses, have revealed that interactions with bound chromosomal proteins can tether the Ty integration machinery to chromosomes and thereby direct integration to nearby sites (Boeke and Devine 1998; Bushman 2003; Sandmeyer 2003; Zhu et al. 2003). Such a model may explain integration targeting by retroviruses as well (Bushman 2003). HIV integration complexes might bind to factors enriched at active genes, while MLV complexes could bind to factors bound near transcription start sites. In support of this idea, in vitro studies have established that retroviral integrase enzymes fused to sequence-specific DNA-binding domains can direct integration preferentially to local regions when tethered at specific DNA sites (Bushman 1994; Goulaouic and Chow 1996; Katz et al. 1996). The analysis of chromosomal regions favored for integration also suggested a role for locally bound proteins. Chromosomal regions enriched in active genes were generally favorable, but further analysis revealed interleaved favorable and unfavorable regions. Statistical tests indicated that favorable regions were typically short (100–250 kb), and for HIV these were interspersed with unfavorable regions near CpG islands. CpG islands are thought to be regulatory regions that bind distinctive sets of transcription factors. Thus, a simple model to explain targeting is that a distinctive set of sequence-specific DNA-binding proteins bound at or near CpG islands disfavor HIV integration, while proteins bound in active transcription units are favorable. For MLV, the proteins bound at CpG islands instead favor integration. For ASLV, it is possible that the viral integration machinery does not interact with factors bound in or near genes, explaining the more random distribution of integration sites in the genome. Such a pattern might have evolved to minimize disruption to the host cell chromosomes due to integration. Another possibility, however, is that ASLV does have stricter target site preferences during normal integration in chicken cells, but the targeting system does not function properly in the human cells studied here. According to this idea, putative chicken chromosomal proteins normally bind ASLV integration complexes and direct integration, but the homologous human proteins may be too different to interact properly. It should be possible to investigate this possibility by characterizing ASLV integration in chicken cells, now that the draft chicken genome sequence is completed (Ren et al. 2003). One consequence of the above findings is that integration will differ from tissue to tissue as a consequence of cell-type-specific transcription. To assess effects of tissue-specific transcription, we analyzed HIV integration in three different cell types (SupT1, PBMC, and IMR90). Transcriptional profiling data showed that transcription was significantly different among the three. This allowed an analysis of integration targeting, which showed that highly expressed genes particular to each tissue were favored for integration in that tissue. However, the magnitude of the tissue-specific biases on integration were modest, probably because most of the cellular transcriptional program appears to be common among cell types (Caron et al. 2001; Mungall et al. 2003; Versteeg et al. 2003). Additional mechanisms could also contribute to targeting. For example, we and others have detected statistically significant biases in integration frequency in whole chromosomes that do not appear to be fully explained by gene density or gene activity (Schroder et al. 2002; Laufs et al. 2003; data reported here). Perhaps the intranuclear position of chromosomes may have an influence, since this has been proposed to be relatively fixed for cells of specific types but may differ among cell types (Boyle et al. 2001; Chubb and Bickmore 2003). Our data indicate that ASLV has integration site preferences that may make it attractive as a vector for human gene therapy. MLV-based vectors have the unfavorable preference for integration near transcription start sites (Wu et al. 2003). The adverse events arising during X-linked severe combined immunodeficiency gene therapy involved integration of an MLV vector near the transcription start region of the LMO2 proto-oncogene. HIV-based vectors strongly favor integration in active genes, which is also likely to be disruptive to the host cell genome (Schroder et al. 2002; Wu et al. 2003). ASLV, in contrast, shows only weak favoring of integration in active genes, and no favoring of integration near transcription start sites. A quantitative model based on gene density, expression, and proximity to transcription start regions fit the ASLV data least well, indicating that ASLV has the weakest bias toward integration in these unfavorable locations. ASLV vectors are known to infect a variety of human cell types (e. g., Valsesia-Wittmann et al. 1994; Federspiel and Hughes 1997; Hatziioannou and Goff 2001; Katz et al. 2002) and can transduce nondividing cells (Hatziioannou and Goff 2001; Katz et al. 2002), adding to their possible utility. More generally, this study, together with previous work (Schroder et al. 2002; Wu et al. 2003), indicates that the selection of different retroviral integration systems can modulate the selection of integration target sites, and this may potentially be exploited for safer gene therapy. Materials and Methods Oligonucleotides used in this study Each oligonucleotide is described by its name, sequence (written 5′ to 3′), and use, in that order. HincII adaptor, GTAATACGACTCACTATAGGGCACGCGTGGTCGACGGCCCGGGCTGC, adapter for use with DNA cleaved by 6-cutter restriction enzymes, top strand; mNheIAvrIISpeII adaptor, P-CTAGGCAGCCCG-NH2, adapter for 6-cutter restriction enzymes, bottom strand; ASB-9, GACTCACTATAGGGCACGCGT, adapter primer for PCR for I/SupT1, PBMC, and IMR-90; SB-76, GAGGGATCTCTAGTTACCAGAGTCACA, HIV primer for PCR for I/SupT1; ASB-19, GAGATTTTCCACACTGACTAAAAGGGTC, HIV primer for PCR for I/PBMC and IMR-90; ASB-16, GTCGACGGCCCGGGCTGCCTA, adapter primer for nested PCR for I/SupT1, PBMC, and IMR-90; ASB-1, AGCCAGAGAGCTCCCAGGCTCAGATC, HIV primer for nested PCR for I/SupT1; ASB-20, CTGAGGGATCTCTAGTTACCAGAGTCA, HIV primer for nested PCR forPBMC and IMR-90; MseI linker +, GTAATACGACTCACTATAGGGCTCCGCTTAAGGGAC, MseI linker, top strand; MseI linker −, P-TAGTCCCTTAAGCGGAG-NH2, MseI linker, bottom strand; MseI linker primer, GTAATACGACTCACTATAGGGC, MseI linker primer for first round of PCR; MseI linker nested primer, AGGGCTCCGCTTAAGGGAC, MseI linker nested primer for second round of PCR; BB389, GATGGCCGGACCGTTGATTC, inner ASLV LTR primer for second round of “nested” PCR; BB390, CGATACAATAAACGCCATTTGACCATTC, outer ASLV LTR primer for first round of PCR. Preparation of the ASLV- and HIV-based vectors To produce HIV vector particles, 293T cells were cotransfected with three plasmids: one encoding the HIV vector segment (p156RRLsinPPTCMVGFPWPRE) (Follenzi et al. 2000), the second, the packaging construct (pCMVdeltaR9) (Naldini et al. 1996), and the third, the gene for VSV-G (pMD.G) (Naldini et al. 1996). Forty-eight hours after transfection, supernatants were collected, centrifuged to pellet cellular debris, then filtered through 0.45-μm filters. Viral particles were further purified by centrifugation at 23,000g and resuspended in 1/17 volume of fresh medium. ASLV particles were generated by transfecting the DF-1 chicken embryonic fibroblast cell line (ATCC CRL-12203) with the plasmid RCASBP(A)GFP (from Steve Hughes, National Cancer Institute, Frederick, Maryland). Supernatant was removed from the cells 4 d post transfection (when cells were nearly 100% GFP positive) and filtered though a 0.45-μm syringe filter. Infections. PBMCs were separated from human blood using a ficoll gradient (Amersham Biosciences, Little Chalfont, United Kingdom). 1 × 107 PHA, IL-2 prestimulated PBMCs, or IMR-90 cells (passage #36) at 30%–50% confluency (1–2 × 106 cells) were infected with the HIV-based vector at an moi of 10 (60 ng p24 per 5 × 10 5 cells). The vector was added to the cells with DEAE-dextran at a final concentration of 5 μg/ml. Forty-eight hours after infection, the cells were pelleted. For RNA isolation, cells were resuspended in 250 μl of PBS and 750 μl of TRIzol and frozen in liquid nitrogen. To determine the extent of infection, cells were analyzed by flow cytometry. For ASLV, supernatant containing RCASBP(A)GFP particles was added to 293T-TVA cells (293T 0.8 cells; a gift from John Young, Salk Institute) at 30%–50% confluency. Forty-eight hours post infection, green fluorescence was seen in approximately 30% of the cells, as determined by examination of the cultures with a fluorescence microscope. DNA was harvested at this point (DNeasy, Qiagen, Valencia, California, United States). RNA from infected cells was also isolated at 48 h post infection (TRIzol) and stored at −80 °C until used for transcriptional profiling analysis. RNA was isolated from infected cell cultures, and samples from each were used for hybridization on one Affymetrix (Santa Clara, California, United States) microarray. Integration site determination. HIV integration sites were cloned by ligation-mediated PCR essentially as described in Schroder et al. (2002). ASLV integration site determination using ligation-mediated PCR was carried out essentially as described in Wu et al. (2003). Oligonucleotides used are summarized above. All novel integration site sequences are deposited at the National Center for Biotechnology Information (NCBI) (accession numbers CL528318–CL529767). Integration sites from earlier studies were reanalyzed on the November 2002 freeze of the human genome sequence (using the University of California at Santa Cruz browser), and a few were excluded because they did not find matches of sufficiently high quality on the new draft sequence, accounting for slightly different numbers than in previous reports. This study used primarily the Acembly and Ensemble human gene catalogs; similar results were generally obtained when the Unigene, RefGene, or GeneScan catalogs of the human genes were used (Protocol S1, p. 3–10). Transcriptional profiling analysis Transcriptional profiling was carried out using Affymetrix microarrays as described in Schroder et al. (2002). Gene expression levels (average difference values) were analyzed using Affymetrix Microarray Suite 4.1 software. All novel transcriptional profiling datasets reported here are deposited at NCBI (GEO dataset numbers GSE1407, GSE1408, GSE1409, and GSE1410). For the analysis in Figure 3, a complication was introduced by the fact that the HU95A chips used have multiple probe sets for some genes but not others. In our analysis all probe sets were accepted and analyzed in these cases. Statistical analysis A detailed description of the statistical methods used is presented in Protocols S1 and S2. Supporting Information Protocol S1 Association of Genomic Features with Integration—Part 1 (322 KB PDF). Click here for additional data file. Protocol S2 Association of Genomic Features with Integration—Part 2 (128 KB PDF). Click here for additional data file. Accession Numbers The GenBank (http://www.ncbi.nlm.nih.gov/) accession numbers for the novel integration site sequences discussed in this paper are CL528318–CL529767. The GenBank GEO dataset numbers for the novel transcriptional profiling datasets reported here are GSE1407, GSE1408, GSE1409, and GSE1410. We thank members of the Bushman laboratory for helpful discussions, and Dr. John Young for the 293T-TVA cells. This work was supported by National Institutes of Health grants AI52845 and AI34786, the James B. Pendleton Charitable Trust, the Berger Foundation, Robin and Frederic Withington (grant to FDB), and the Fritz B. Burns Foundation (grant to JRE). ARWS was supported by a grant from the Deutsche Forschungsgemeinschaft. Conflicts of interest. The authors have declared that no conflicts of interest exist. Author contributions. RSM, BFB, ARWS, CCB, JRE, and FDB conceived and designed the experiments. RSM, BFB, ARWS, PS, HC, CCB, JRE, and FDB performed the experiments. RSM, BFB, ARWS, PS, HC, CCB, HCB, JRE, and FDB analyzed the data. RSM, BFB, CCB, JRE, and FDB wrote the paper. Academic Editor: Michael Emerman, Fred Hutchinson Cancer Research Center Citation: Mitchell RS, Beitzel BF, Schroder ARW, Shinn P, Chen H, et al. (2004) Retroviral DNA integration: ASLV, HIV, and MLV show distinct target site preferences. PLoS Biol 2(8): e234. Abbreviations ASLVavian sarcoma-leukosis virus HIVhuman immunodeficiency virus MLVmurine leukemia virus PBMCperipheral blood mononuclear cell ==== Refs References Boeke JD Devine SE Yeast retrotransposons: Finding a nice quiet neighborhood Cell 1998 93 1087 1089 9657139 Boyle S Gilchrist S Bridger JM Mahy NL Ellis JA The spatial organization of human chromosomes within the nuclei of normal and emerin-mutant cells Hum Mol Genet 2001 10 211 219 11159939 Bushman FD Tethering human immunodeficiency virus 1 integrase to a DNA site directs integration to nearby sequences Proc Natl Acad Sci U S A 1994 91 9233 9237 7937746 Bushman FD Lateral DNA transfer: Mechanisms and consequences 2001 New York Cold Spring Harbor Laboratory Press 448 Bushman FD Targeting survival: Integration site selection by retroviruses and LTR-retrotransposons Cell 2003 115 135 138 14567911 Caron H van Schaik B van der Mee M Bass B Riggins G The human transcriptome map: Clustering of highly expressed genes in chromosomal domains Science 2001 291 1289 1292 11181992 Carteau S Hoffmann C Bushman FD Chromosome structure and HIV-1 cDNA integration: Centromeric alphoid repeats are a disfavored target J Virol 1998 72 4005 4014 9557688 Cawley S Bekiranova S Ng HH Kapranov P Sekinger EA Unbiased mapping of transcription factor binding sites along human chromosomes 21 and 22 points to widespread regulation of noncoding RNAs Cell 2004 116 499 509 14980218 Check E A tragic setback Nature 2002 420 116 12432357 Chubb JR Bickmore WA Considering nuclear compartmentalization in light of nuclear dynamics Cell 2003 112 403 406 12600306 Coffin JM Hughes SH Varmus HE editors Retroviruses 1997 New York Cold Spring Harbor Laboratory Press 843 Corbeil J Sheeter D Genini D Rought S Leoni L Temporal gene regulation during HIV-1 infection of human CD4+ T cells Genome Res 2001 11 1198 1204 11435401 Federspiel MJ Hughes SH Retroviral gene delivery Methods Cell Biol 1997 52 179 214 9379950 Follenzi A Ailes LE Bakovic S Gueuna M Naldini L Gene transfer by lentiviral vectors is limited by nuclear translocation and rescued by HIV-1 pol sequences Nat Genetics 2000 25 217 222 10835641 Goulaouic H Chow SA Directed integration of viral DNA mediated by fusion proteins consisting of human immunodeficiency virus type 1 integrase and Eschericia coli LexA protein J Virol 1996 70 37 46 8523550 Hacein-Bey-Abina S von Kalle C Schmidt M Le Deist F Wulffraat N A serious adverse event after successful gene therapy for X-linked severe combined immunodeficiency N Engl J Med 2003 348 255 256 12529469 Hatziioannou T Goff SP Infection of nondividing cells by Rous sarcoma virus J Virol 2001 75 9526 9531 11533215 Katz RA Merkel G Skalka AM Targeting of retroviral integrase by fusion to a heterologous DNA binding domain: In vitro activities and incorporation of a fusion protein into viral particles Virology 1996 217 178 190 8599202 Katz RA Greger JG Darby K Biomel P Rall GF Transduction of interphase cells by avian sarcoma virus J Virol 2002 76 5422 5434 11991971 Lander ES Linton LM Birren B Nusbaum C Zody MC Initial sequencing and analysis of the human genome Nature 2001 409 860 921 11237011 Laufs S Gentner B Nagy Z Jauch A Benner A Retroviral vector integration occurs in preferred genomic targets in human bone marrow-repopulating cells Blood 2003 101 2191 2198 12424203 Li Z Dullmann J Schiedlmeier B Schmidt M von Kalle C Murine leukemia induced by retroviral gene marking Science 2002 296 497 11964471 Mitchell R Chiang C Berry C Bushman FD Global effects on cellular transcription following infection with an HIV-based vector Mol Ther 2003 8 674 687 14529841 Mungall AJ Palmer SA Sims SK Edwards CA Ashurst JL The DNA sequence and analysis of human chromosome 6 Nature 2003 425 805 811 14574404 Naldini L Blomer U Gallay P Ory D Mulligan R In vivo gene delivery and stable transduction of nondividing cells by a lentiviral vector Science 1996 272 263 267 8602510 Panet A Cedar H Selective degradation of integrated murine leukemia proviral DNA by deoxyribonucleases Cell 1977 11 933 940 560916 Ren C Lee MK Yan B Ding K Cox B A BAC-based physical map of the chicken genome Genome Res 2003 13 2754 2758 14656976 Rohdewohld H Weiher H Reik W Jaenisch R Breindl M Retrovirus integration and chromatin structure: Moloney murine leukemia proviral integration sites map near DNase I-hypersensitive sites J Virol 1987 61 336 343 3027365 Sandmeyer S Integration by design Proc Natl Acad Sci U S A 2003 100 5586 5588 12732725 Schroder A Shinn P Chen H Berry C Ecker JR HIV-1 integration in the human genome favors active genes and local hotspots Cell 2002 110 521 529 12202041 Tian B Zhang Y Luxon BA Garofalo RP Casola A Identification of NF-kappaB-dependent gene networks in respiratory syncytial virus-infected cells J Virol 2002 76 6800 6814 12050393 Valsesia-Wittmann S Drynda A Deleage G Aumailley M Heard JM Modifications in the binding domain of avian retrovirus envelope protein to redirect the host range of retroviral vectors J Virol 1994 68 4609 4619 8207835 van 't Wout AB Lehrman GK Mikheeva SA O'Keeffe GC Katze MG Cellular gene expression upon human immunodeficiency virus type 1 infection of CD4+-T-cell lines J Virol 2003 77 1392 1402 12502855 Venter JC Adams MD Myers EW Li PW Mural RJ et al The sequence of the human genome Science 2001 291 1304 1351 11181995 Versteeg R van Schaik BD van Batenberg MF Roos M Monajemi R The human transcriptome map reveals extremes in gene density, intron length, GC content, and repeat pattern for domains of highly and weakly expressed genes Genome Res 2003 13 1998 2004 12915492 Vijaya S Steffan DL Robinson HL Acceptor sites for retroviral integrations map near DNase I-hypersensitive sites in chromatin J Virol 1986 60 683 692 3490582 Weidhaas JB Angelichio EL Fenner S Coffin JM Relationship between retroviral DNA integration and gene expression J Virol 2000 74 8382 8389 10954538 Wu X Li Y Crise B Burgess SM Transcription start regions in the human genome are favored targets for MLV integration Science 2003 300 1749 1751 12805549 Zhu Y Dai J Fuerst PG Voytas DF Controlling integration specificity of yeast retrotransposon Proc Natl Acad Sci U S A 2003 100 5891 5895 12730380

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020235Research ArticleCell BiologySaccharomyces—4932) IRE1-Independent Gain Control of the Unfolded Protein Response Transcriptional Control of Hac1p ExpressionLeber Jess H 1 Bernales Sebastián 1 Walter Peter walter@cgl.ucsf.edu 1 2 1Department of Biochemistry and Biophysics, University of CaliforniaSan Francisco, California, United States of America2Howard Hughes Medical Institute, Chevy ChaseMarylandUnited States of America8 2004 17 8 2004 17 8 2004 2 8 e2354 2 2004 24 5 2004 Copyright: © 2004 Leber et al.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. Gcn4p and Novel Upstream Activating Sequences Regulate Targets of the Unfolded Protein Response Yeast Use Dual Gain Controls to Amplify Protein-Processing Nonconventional splicing of the gene encoding the Hac1p transcription activator regulates the unfolded protein response (UPR) in Saccharomyces cerevisiae. This simple on/off switch contrasts with a more complex circuitry in higher eukaryotes. Here we show that a heretofore unrecognized pathway operates in yeast to regulate the transcription of HAC1. The resulting increase in Hac1p production, combined with the production or activation of a putative UPR modulatory factor, is necessary to qualitatively modify the cellular response in order to survive the inducing conditions. This parallel endoplasmic reticulum–to–nucleus signaling pathway thereby serves to modify the UPR-driven transcriptional program. The results suggest a surprising conservation among all eukaryotes of the ways by which the elements of the UPR signaling circuit are connected. We show that by adding an additional signaling element to the basic UPR circuit, a simple switch is transformed into a complex response. The unfolded protein response in yeast was thought to be a simple on/off switch. Here, a second signaling element is revealed, transforming this simple switch into a complex response ==== Body Introduction In eukaryotes, the endoplasmic reticulum (ER) serves as the first station of the secretory pathway, through which all secreted and membrane proteins must pass. Within the ER, proteins are folded into their native structure and multisubunit protein complexes are assembled. The ER is a dynamic organelle, capable of sensing and adjusting its folding capacity in response to increased demand: when misfolded proteins accumulate in the ER, a signaling pathway, termed the unfolded protein response (UPR), is activated (reviewed in Ma and Hendershot 2001; Patil and Walter 2001; Kaufman 2002; Ron 2002). The UPR activates the expression of genes that enable the cell to adapt to and survive the stress, including those encoding ER-resident chaperones (Lee 1987; Kozutsumi et al. 1988), key enzymes in lipid biosynthesis (Cox et al. 1997), members of the ER-associated degradation (ERAD) machinery, and other components of the secretory system (Ng et al. 2000; Travers et al. 2000; Urano et al. 2000). In yeast, the UPR is controlled by a binary switch imposed by a nonconventional splicing reaction that governs the production of the Hac1p transcription factor responsible for the activation of UPR target genes (Cox et al. 1993; Kohno et al. 1993; Cox and Walter 1996; Mori et al. 1992, 1996). In uninduced cells, direct base pairing between the 5′ untranslated region (UTR) and an intron at the 3′ end of the mRNA prevents HAC1 mRNA translation (Chapman and Walter 1997; Ruegsegger et al. 2001). Accumulation of unfolded proteins activates the ER-resident transmembrane kinase/endoribonuclease Ire1p, which then cleaves the HAC1 mRNA at two precise splice junctions, excising the intron (Cox et al. 1993; Mori et al. 1993; Sidrauski and Walter 1997). The two HAC1 exons are then joined by tRNA ligase, allowing translation of Hac1p (Sidrauski et al. 1996). To date, Ire1-dependent HAC1 mRNA splicing is the only identified way by which signals from the ER lumen affect transcription in yeast. By contrast, in metazoan cells three mechanistically distinct pathways are known that operate in parallel, although their relative importance in different tissues remains to be determined (reviewed in Ma and Hendershot 2001). Hints that further complexity also exists in yeast comes from data presented in the accompanying paper (Patil et al. 2004): these data demonstrate that Hac1p activity is modulated by interaction with Gcn4p, a transcription factor central to regulation of amino acid biosynthesis. The UPR, therefore, may integrate signals from more than one source to compute a transcriptional output appropriate for the physiological conditions of the cell. In this paper, we show that HAC1 mRNA transcription is regulated, resulting in control of Hac1p abundance. Thus the on/off switch provided by IRE1-dependent splicing is not the only regulatory step of the UPR. This regulation responds to a bipartite signal that emanates from the ER and is communicated by an Ire1p-independent pathway. As a consequence, an alternate transcriptional program is triggered, with specific alterations to the normal UPR allowing the cell to survive. Thus, quantitative modulation of Hac1p imposes gain control on a binary switch in the UPR circuitry and, in collaboration with an additional signaling input, transforms a discrete transcriptional response into a more complex signaling function. Results Secretory Stress Boosts HAC1 mRNA Abundance To define the basic circuitry of signal transduction in the UPR, we evaluated the HAC1 mRNA processing step in a quantitative manner. To this end, we induced the UPR with either dithiothreitol (DTT) or tunicamycin (both agents that cause protein misfolding selectively in the ER) and monitored HAC1 mRNA by Northern blot analysis (Figure 1A). In agreement with previous results, we observed rapid and efficient splicing of HAC1 mRNA, as apparent from the conversion of unspliced HAC1u mRNA (u for UPR-uninduced) to spliced HAC1i mRNA (i for UPR-induced). Quantitation of the results shows that the relative abundance of HAC1 mRNA (the sum of HAC1u and HAC1i mRNAs) remained unchanged over at least 12 h (Figure 1A; unpublished data). These data demonstrate that acute induction of unfolded proteins triggers a simple on/off switch that controls HAC1 mRNA splicing. Figure 1 ER-Distal Secretory Stress Boosts HAC1 mRNA Abundance (A) Determination of HAC1 mRNA abundance during the UPR. The UPR was induced in WT cells by addition of either 6 mM DTT (lanes 1–4) or 1 μg/ml tunicamycin (lanes 5–8) for the times indicated. Total RNA was harvested at the indicated intervals, and the relative abundance of HAC1 and ACT1 mRNAs was analyzed by Northern blot analysis (see Materials and Methods). Splicing was calculated at the ratio of spliced (HAC1i) to total (HAC1i + HAC1u) mRNA. (B) Determination of HAC1 mRNA abundance during ER-distal secretory stress. WT, sec12–1, sec14–3, and sec1–1 strains were grown at 23 °C and shifted to 37 °C. (C) Determination of HAC1 mRNA abundance during ER-proximal secretory stress. WT, sec14–3, sec61–101, sec62–101, and sec63–201 strains were grown at 23 °C and shifted to 37 °C. In light of these observations, we were surprised to find that blocking the secretory pathway distal to the ER resulted in a pronounced increase in HAC1 mRNA abundance. As shown in Figure 1B, HAC1 mRNA levels increased 3- to 4-fold in mutant strains compromised at various steps in the secretory pathway when shifted to the nonpermissive temperature (sec12–1: ER → Golgi, lanes 5–8; sec14–1: intra-Golgi, lanes 9–12; and sec1–1: Golgi → plasma membrane, lanes 13–16) (Novick et al. 1980). Splicing was also induced, albeit to a lesser degree than was observed with DTT or tunicamycin treatment. The observed splicing suggests that blockages in ER-distal compartments of the secretory pathway lead to activation of Ire1p in the ER. Temperature shift alone only transiently induced HAC1 mRNA splicing and had no effect on HAC1 mRNA abundance (Figure 1B, lanes 1–4). To determine if any disruption of the secretory pathway had similar consequences, we blocked earlier stages of protein traffic. Mutations that blocked protein entry into the ER had no effect (Figure 1C: sec62–101, lanes 13–16; sec63–201, lanes 17–20) or only a mild effect (sec61–101, lanes 9–12) on HAC1 mRNA abundance. Thus, a surveillance pathway operates to adjust HAC1 mRNA levels in response to altered conditions in the secretory pathway. In the experiments described above, we observed HAC1 mRNA induction only in sec mutants that block transport distal to the ER, not in those that block protein entry into the ER. One common consequence of blocking the secretory pathway at later stages is that proteins in transit will eventually back up into the ER (Rose et al. 1989; Chang et al. 2002). This condition results in protein folding defects, thereby activating Ire1p, as indicated by the observed HAC1 mRNA splicing. From the data discussed above (Figure 1A), however, we know that an accumulation of unfolded proteins alone is insufficient to trigger an upregulation of HAC1 mRNA, suggesting that an additional inducing signal is required. HAC1 mRNA Induction Requires a Bipartite Signal To determine the nature of this second signal, we sought conditions that induce HAC1 mRNA when combined with ER protein misfolding drugs. Canvassing different conditions, we found two scenarios under which wild-type (WT) cells can be induced to upregulate HAC1 mRNA: (1) ER protein misfolding combined with a temperature shift from 23 °C to 37 °C (Figure 2A) and (2) ER protein misfolding combined with inositol starvation (Figure 2B). Intriguingly, while ER protein misfolding and inositol starvation each activated the UPR individually (as shown by the activation of HAC1 mRNA splicing; Figure 2A, lanes 5–8; Figure 2B, lanes 1–4 and 5–8), neither stress alone was sufficient to cause HAC1 mRNA upregulation. Similarly, the temperature shift reproducibly caused a transient UPR induction (see Figure 1B, lanes 1–4; Figure 2A, lanes 1–4) but by itself did not affect HAC1 mRNA levels. Only the combination of ER stress with either temperature shift (Figure 2A, lanes 9–12) or inositol starvation (Figure 2B, lanes 9–12) led to an increase in HAC1 mRNA abundance. Subjecting cells to both temperature shift and inositol deprivation had no additive effect, nor did treating cells with both DTT and tunicamycin (unpublished data). Thus, HAC1 mRNA induction requires a bipartite signal, consisting of one input provided by unfolded proteins in the ER (UP signal), and the other input provided by inositol starvation or temperature shift (I/T signal). Figure 2 HAC1 mRNA Induction Requires a Bipartite Signal and Is IRE1-Independent (A) Determination of HAC1 mRNA abundance during ER stress and temperature shift. WT cells were grown at 23 °C and shifted to 37 °C (lanes 1–4 and 9–12) or kept constant at 30 °C (lanes 5–8). DTT was added as indicated (lanes 5–8 and 9–12). (B) Determination of HAC1 mRNA abundance during ER stress and inositol deprivation. WT cells were grown at 30 °C in synthetic medium supplemented with inositol and shifted to synthetic medium lacking inositol (lanes 1–4 and 9–12), or continuously grown in medium supplemented with inositol (lanes 5–8). Tunicamycin was added to a final concentration of 1 μg/ml as indicated (lanes 5–8 and 9–12). (C) Distinction between heat shock response and HAC1-mRNA-inducing conditions. WT (lanes 1–4 and 9–12) and HSF1c (lanes 5–8) strains were grown at 23 °C and shifted to 37 °C (lanes 1–4 and 5–8) or continuously grown at 37 °C (lanes 9–12), and DTT added as indicated. (D) Analysis of IRE1 pathway for a role in HAC1 mRNA induction. Δire1 cells were grown at 23 °C and shifted to 37 °C (lanes 1–4 and 9–12) or continuously grown at 30 °C (lanes 5–8), and DTT was added as indicated (lanes 5–8 and 9–12). Note that in Δire1 cells, HAC1 mRNA is modestly induced in response to DTT alone (lanes 5–8). This observation is indicative of feedback regulation, whereby a block in the UPR induces the I/T signal. The heat shock response is transiently induced by shifting cells from 23 °C to 37 °C. To determine whether the heat shock response is an important component of the I/T signal, we tested whether continued growth at 37 °C or expression of a constitutively active allele of the heat shock factor Hsf1p (Sorger 1991; Bulman et al. 2001) would substitute for the temperature shift described above. Constitutive expression of active Hsf1p (Figure 2C, lanes 5–8) led to upregulation of SSA1, a known target of the heat shock response (Slater and Craig 1989), but did not substitute for the I/T signal for HAC1 upregulation. In contrast, continued growth at 37 °C (Figure 2C, lanes 9–12) allowed for modest induction of HAC1 mRNA. Thus, elevated temperature elicits effects other than heat shock, which are important for HAC1 mRNA upregulation. HAC1 Induction Is IRE1-Independent The UP signal was experimentally induced by DTT or tunicamycin treatment of the cells. As Ire1p is a sensor of folding conditions within the ER lumen, we tested next whether Ire1p was required to transmit this signal. Surprisingly, it was not. HAC1 mRNA abundance was induced 2.6-fold in Δire1 cells (Figure 2D, lanes 9–12), similar to the 3-fold induction observed in WT cells (Figure 2A, lanes 9–12). These results show that a previously unrecognized Ire1p-independent surveillance mechanism must exist that monitors protein folding in the ER. HAC1 mRNA Abundance Is Regulated Transcriptionally Increase of HAC1 mRNA abundance could result from increased transcription, reduced degradation, or both. To distinguish between these possibilities, we constructed a reporter gene consisting of the HAC1 promoter driving transcription of the open reading frame encoding the green fluorescent protein (GFP) flanked by ACT1 untranslated regions (HAC1pro-GFP). The resulting heterologous GFP mRNA therefore contained no HAC1 mRNA sequences. Under conditions providing both the UP and I/T signals, the change in abundance of the GFP mRNA (Figure 3A, lanes 5–8) mirrored that of the endogenous HAC1 mRNA (Figure 3A, lanes 1–4), both in the kinetics and magnitude of the response. These data demonstrate that the observed increase in HAC1 mRNA abundance was caused by increased transcriptional activity of the HAC1 promoter. Figure 3 Activation of the HAC1 Promoter Controls Increase in HAC1 mRNA Abundance (A) Analysis of HAC1 promoter activity during bipartite stress conditions. Δhac1 cells containing either a construct restoring HAC1 expression (lanes 1–4) or a construct expressing GFP driven by the HAC1 promoter (lanes 5–8) were grown at 23 °C and shifted to 37 °C concurrent with addition of DTT as indicated. (B) Determination of mRNA half-life during HAC1-mRNA-inducing conditions. polIIts cells were grown at 23 °C and were shifted to 37 °C either in the absence (open symbols) or presence (filled symbols) of DTT. HAC1 mRNA abundance (squares) and ACT1 mRNA abundance (circles) are normalized to the abundance of the PolIII transcript SCR1. To further test this notion, we compared the rate of decay of HAC1 mRNA under both HAC1mRNA-inducing and noninducing conditions. To this end, we employed a strain bearing a temperature-sensitive allele of RNA polymerase II, which was subjected to either elevated temperature alone, or to both elevated temperature and DTT treatment. In both cases, polymerase II transcription ceased upon temperature shift, and mRNA decay was measured. As shown in Figure 3B, the rate of decay of HAC1 mRNA was indistinguishable under the two conditions. Therefore, the increase in HAC1 mRNA abundance in response to the combination of UP and I/T signals is due solely to activation of the HAC1 promoter. HAC1 Promoter Regulation Is Required to Survive Certain Stress Conditions The results presented so far define a novel regulatory mechanism whereby cells adjust the amount of HAC1 mRNA. This mRNA is the substrate for the Ire1p-mediated splicing reaction, which in turn produces HAC1i mRNA that is translated to produce Hac1p transcription factor. We therefore asked whether elevated levels of HAC1 mRNA led to a proportional increase in the level of Hac1p. Quantitative Western blot analysis showed that this is indeed the case: when cells were treated with DTT and concomitantly shifted to 37 °C, the levels of Hac1p increased 3-fold (Figure 4A, lanes 5–8), relative to the Hac1p levels observed in cells subjected to DTT treatment alone (Figure 4A, lanes 1–4). Therefore, the transcriptional induction of HAC1 mRNA combined with Ire1p-mediated splicing results in elevated Hac1p levels, characterizing a new physiological state. Henceforth, we refer to this state as the “Super-UPR” (S-UPR). Figure 4 HAC1 Promoter Regulation Is Required to Survive Stress (A) Determination of Hac1p levels during either ER stress alone or during both ER stress and temperature shift. WT cells were either grown at 30 °C and treated with DTT (lanes 1–4) or grown at 23 °C and simultaneously shifted to 37 °C and treated with DTT (lanes 5–8). Protein lysates were prepared, and protein levels were analyzed by Western blot analysis. The relative Hac1p/Pgk1p ratio is normalized to the DTT-treated sample (lane 4). (B) Characterization of HAC1 expression in strain used to approximate basal HAC1 expression. Cells expressing HAC1 from the endogenous promoter (lanes 1–4) or the ADH1 promoter (lanes 5–8) were grown at 30 °C in synthetic medium supplemented with inositol and shifted to synthetic medium lacking inositol simultaneous with the addition of tunicamycin. (C) Reduced viability of strains unable to express HAC1 at elevated levels. The strains described in (B) were plated in serial dilutions (left to right) on synthetic medium lacking inositol (“−ino”) and synthetic medium lacking inositol and containing tunicamycin (“−ino +TM”). To assess the physiological role of the S-UPR, we sought conditions that would allow us to directly monitor the consequences of changes in HAC1 mRNA levels under otherwise identical growth conditions. To this end, we engineered a yeast strain unable to transcriptionally upregulate HAC1. In these cells, HAC1 mRNA expression was removed from the control of the HAC1 promoter and was instead driven by the heterologous ADH1 promoter (ADH1pro-HAC1), at levels closely approximating the uninduced HAC1 state (Figure 4B, compare ADH1pro-HAC1, lanes 5–8, to HAC1pro-HAC1, lanes 1–4). Expression from the ADH1 promoter was constitutive, and the levels of HAC1 mRNA did not change significantly under the various inducing conditions described above. As expected, induction of the UPR in these strains led to efficient HAC1 mRNA splicing and Hac1p production. This strain therefore allowed us to fix the cellular Hac1p concentration to a level closely approximating the basal HAC1 expression state observed during the UPR. We next assessed whether we could identify physiological conditions under which elevated HAC1 mRNA levels were required for cell growth. Therefore, we subjected WT cells and the engineered strain described above to the combinations of stresses described in Figure 2. Cells expressing HAC1 from the endogenous or from the ADH1 promoter grew equally well on plates lacking inositol (Figure 4C, left, first and third rows). This condition induces the UPR and requires the expression of at least a minimal amount of HAC1 mRNA, as Δhac1 cells fail to grow (Figure 4C, left, second row). In contrast, only WT cells, which are able to upregulate HAC1 mRNA production, grew on plates lacking inositol and also containing tunicamycin. Cells expressing HAC1 mRNA only at the basal levels from the ADH1 promoter were nonviable on these plates (Figure 4C, right, third row). As shown previously in Figure 2B, this combination of stresses induces the S-UPR. The data therefore reveal that regulation provided by the HAC1 promoter is necessary for cells to survive certain stress conditions that otherwise are lethal. Differential UPR Target Gene Induction by Elevated Hac1p Levels To begin to characterize the cause for increased viability, we next determined differences in UPR target gene expression resulting from either UPR or S-UPR induction. To this end, we used DNA microarray chip analysis to determine the complete mRNA profile of cells grown under UPR and S-UPR conditions. The results of this analysis are shown in Figure 5A. Each spot represents the fold induction of a UPR target under UPR conditions (x-axis) or S-UPR conditions (y-axis) (see Materials and Methods for definition of the UPR target set used in this analysis). UPR target genes for which the S-UPR has no additional effect should undergo equal induction under both conditions, and are expected to scatter around the diagonal, indicated by the dashed line. This was the case for many UPR targets. However, induction of a substantial number of genes was skewed to the top of the graph, indicating stronger induction under S-UPR conditions than under UPR conditions. These same data are displayed in Figure 5B to highlight and categorize these differences. In the histogram, the x-axis represents the ratio of the induction of a target gene during S-UPR and UPR conditions, and the y-axis shows the number of genes with a given ratio. We have operationally divided UPR target genes into three classes, based on their fold induction during the S-UPR compared to their fold induction during the UPR. (1) Class 1 targets (Figure 5, red bars) exhibit little if any difference in induction during the UPR and S-UPR (S-UPR induction / UPR induction < 2). Thus, the increased Hac1p during the S-UPR does not lead to enhanced transcription, indicating that for these genes the response is already saturated at UPR Hac1p levels. Class 1 targets include many of the known genes encoding ER lumenal chaperones (including KAR2, SCJ1, LHS1, and JEM1) and redox proteins (including PDI1, EUG1, and ERO1). (2) Class 2 targets (Figure 5, blue bars) are induced to a 2- to 4-fold greater extent during S-UPR than during the UPR. Transcription of these genes is therefore roughly proportional to the Hac1p levels in the cell. Class 2 targets include YIP3, involved in ER-to-Golgi transport, OPI3, encoding a phospholipid methyltransferase, and the hexose transporters HXT12, HXT15, HXT16, and HXT17. (3) Class 3 targets (Figure 5, green bars) are induced by the S-UPR greater than 4-fold more than by the UPR. Class 3 contains the UPR targets DER1, involved in ER-associated degradation (Knop et al. 1996; Ng et al. 2000; Travers et al. 2000), and INO1, critical for membrane biogenesis (Hirsch and Henry 1986). Figure 5 Differential UPR Target Gene Induction by Elevated Hac1p Levels (A) Comparison of UPR target gene induction under either UPR or S-UPR conditions. Whole-genome mRNA expression analysis was carried out on WT cells harvested after 60 min of treatment, either grown at 30 °C and treated with 6 mM DTT (x-axis), or grown at 23 °C and simultaneously shifted to 37 °C and treated with 6 mM DTT (y-axis). Fold changes in gene expression are in reference to the untreated (t = 0) samples. Shown are only those genes designated as targets of the UPR (see Materials and Methods). The dashed diagonal line represents equal induction under both conditions. (B) Comparison of UPR target gene induction under either UPR or S-UPR conditions (alternate display). The data from (A) were analyzed to generate a ratio (x-axis) for each gene, dividing the induction during S-UPR-inducing conditions by the induction during UPR-inducing conditions, with target genes of similar ratio grouped together (y-axis). (C) Characterization of HAC1 expression in a strain constitutively expressing HAC1 at high levels. Cells expressing HAC1 from the endogenous promoter (WT; lanes 1 and 2), or a modified promoter constitutively expressing HAC1 at high levels (HAC1proHI; lanes 3 and 4) were treated with 6 mM DTT for 60 min. Although the basal transcription of HAC1proHI is elevated, the promoter is still capable of further induction during the S-UPR (unpublished data). (D) Determination of Hac1p level in a strain constitutively expressing HAC1 at high levels. Protein lysates were prepared from the strains described in (C), and protein levels were analyzed by Western blot analysis. The relative Hac1p/Pgk1p ratio is normalized to the WT DTT-treated (t = 60) sample from Figure 4A. (E) Transcriptional response of different classes of UPR targets to high levels of Hac1p. Whole-genome mRNA expression analysis was carried on HAC1proHI and WT cells treated with 6 mM DTT and harvested after 60 min. For the genes in each of the three classes of UPR targets defined in (B), a ratio (x-axis) is calculated by dividing the fold induction in DTT-treated HAC1proHI cells by the fold induction in DTT-treated WT cells. This ratio is plotted against the number of genes with a similar ratio (y-axis). The Class 2 target YFR026C (asterisk), which is DTT-induced approximately 10-fold more in HAC1proHI than in WT cells, is of unknown function. a, DER1; b, INO1; c, YOR289W; d, YHR087W. (F) Transcriptional response of different classes of UPR targets to UMF. Whole-genome mRNA expression analysis was carried on ADH1pro-HAC1 cells grown at 23 °C and simultaneously shifted to 37 °C and treated with 6 mM DTT, and WT cells treated with 6 mM DTT, both harvested after 60 min. For the genes in each of the three classes of UPR targets defined in (B), a ratio (x-axis) is calculated by dividing the fold induction in ADH1pro-HAC1 cells under S-UPR-inducing conditions by the fold induction in WT cells under UPR-inducing conditions. This ratio is plotted against the number of genes with a similar ratio (y-axis). a, DER1; b, INO1; c, YOR289W; d, YHR087W. Role for a Putative UPR Modulatory Factor The increased transcriptional output under S-UPR conditions could occur for two reasons. It could be due to increased Hac1p concentrations in the cell, or it could result because an additional S-UPR-specific transcription factor is produced or activated (perhaps the same that regulates HAC1 transcription). It could also be due to a combination of these two scenarios. To distinguish among these possibilities, we determined the target gene induction profile in cells in which the HAC1 mRNA concentration was artificially elevated to a similar level as that found after S-UPR induction. We took advantage of a specific 15-bp deletion in the HAC1 promoter (HAC1proHI), which increases basal expression by about 3-fold, as compared to the endogenous promoter (Figure 5C). In cells bearing a HAC1proHI-HAC1 gene (“HAC1proHI cells”), splicing of HAC1 mRNA was somewhat reduced upon UPR induction (47%, compared to 67% for WT); however, even with this reduction, HAC1proHI cells produced approximately 2.5-fold more spliced HAC1i mRNA than WT cells (Figure 5C, compare lanes 3 and 4 to lanes 1 and 2). The increased levels of HAC1i mRNA led to a corresponding increase in Hac1p (Figure 5D, compare lanes 3 and 4 to lanes 1 and 2). The amount of Hac1p produced by DTT induction of HAC1proHI cells is approximately the same as the amount of Hac1p produced during the S-UPR (compare Figure 5D, lanes 2 and 4 with Figure 4A, lanes 4 and 8). The ability to set HAC1 mRNA levels to S-UPR levels allowed us to compare directly UPR target gene induction with the cellular Hac1p concentration being the only variable. We induced the UPR in both WT and HAC1proHI cells with DTT and determined the mRNA expression profiles. For each class of UPR target defined above, the expression analysis of UPR-induced WT and HAC1proHI cells is shown in Figure 5E. In the histograms, the x-axis shows the ratio of target gene induction during the UPR driven by a high level of Hac1p from HAC1proHI cells compared to induction during the UPR in WT cells. The y-axis shows the number of genes at any given ratio. As expected, Class 1 targets (Figure 5E, top panel) did not further respond to the higher levels of Hac1p produced in HAC1proHI cells. The majority of Class 2 and Class 3 targets (Figure 5E, middle and bottom panels) also did not respond to higher levels of Hac1p (ratio less than 2), indicating that only raising the Hac1p concentration in cells is not sufficient to account for their full increased induction during the S-UPR. By contrast, ten of the 32 Class 2 and Class 3 targets were significantly induced (ratio greater than 2) in cells expressing high levels of Hac1p. For the Class 3 target DER1, high levels of Hac1p were sufficient to elevate expression to S-UPR levels (compare 8-fold induction in DTT-treated HAC1proHI cells to 9-fold induction in WT cells during the S-UPR). Otherwise, however, high levels of Hac1p did not fully reconstitute the induction seen during the S-UPR. For example, while the Class 3 gene INO1 was induced 7.5-fold more in the S-UPR than in the UPR, it was induced only 3-fold more by high levels of Hac1p, compared to normal levels. We conclude that elevated Hac1p levels are sufficient to selectively increase the induction of a few UPR targets, but that the full transcriptional program of the S-UPR predicts the production or activation of an additional transcriptional activator, which we term UPR modulatory factor (UMF). To dissect further the UMF contribution during the S-UPR, we sought conditions under which UMF activity was the only variable. To this end, we induced the S-UPR in ADH1pro-HAC1 cells, which are prevented from achieving high level Hac1p expression, and compared the mRNA expression profile against the UPR in WT cells. In this analysis, Hac1p levels were approximately equivalent in the two conditions, so variations from the normal UPR transcriptional program reflect the activity of UMF. The results are shown in Figure 5F, with the data displayed similarly to Figure 5E: the x-axis shows the ratio of target gene induction during the S-UPR in ADH1pro-HAC1 cells, compared to induction during the UPR in WT cells, and the y-axis shows the number of genes at any given ratio. Not surprisingly, the induction of Class 1 targets (Figure 5F, top panel) was unaffected: these are targets that are fully induced by even low levels of Hac1p and are not more induced during the S-UPR. Two Class 3 targets, YOR289W and YHR087W (both of unknown function) reach near WT S-UPR induction levels, without elevated levels of Hac1p; for these targets, UMF likely plays a leading role in their induction, with Hac1p having less influence. Most Class 2 and Class 3 targets (Figure 5F, middle and bottom panels), however, do not reach full S-UPR induction levels in the absence of elevated Hac1p levels. For example, the Class 3 target INO1 is induced roughly 25-fold in ADH1pro-HAC1 cells during S-UPR conditions; while this is roughly twice the induction observed during the UPR, it falls far short of the 75-fold S-UPR induction in WT cells. These results reinforce the in vivo requirement for high levels of Hac1p to survive S-UPR stress, demonstrated in Figure 4C. Taken together with the data shown in Figure 5E, we conclude that the full S-UPR transcriptional program results from a collaboration between elevated Hac1p levels and UMF, with the relative contribution from each varying among different target genes. Discussion The Circuitry of the UPR In this paper, we describe a novel ER surveillance pathway in yeast that modulates the UPR, resulting in a new physiological state that we term the S-UPR. In response to a bipartite signal transmitted from the ER by an IRE1-independent pathway, the HAC1 promoter is activated, resulting in increased HAC1 mRNA levels that, upon splicing, yield more Hac1p. The increased Hac1p concentration, in conjunction with an additional postulated factor(s) produced or activated by the S-UPR (UMF), allows the cell to mount a modified transcriptional response to cope with the inducing stress conditions. Figure 6 shows the UPR as a circuit diagram utilizing multiple logical operations to integrate various signals. In the “classical UPR” (in red), basal transcription of HAC1 produces HAC1u mRNA, which is translationally inactive due to the presence of the inhibitory intron. In response to unfolded proteins, Ire1p performs an on/off operation, excising the intron from HAC1u mRNA to generate spliced HAC1i mRNA, which is translated to produce the Hac1p transcription activator. The S-UPR provides another layer of regulation superimposed on the UPR (in blue). If ER folding stress is combined with either a shift to elevated temperature or inositol starvation, an AND gate integrates this bipartite signal and boosts HAC1 mRNA levels. In turn, this regulation causes increased Hac1p production. Together with UMF, Hac1p induces UPR target genes, with particular genes responding differentially to differences in Hac1p and UMF concentration. Thus the S-UPR can be seen as an adaptation of the classical (or basal) UPR, fine-tuning the activation of select targets to produce a response suited to the challenge faced by the cell. Figure 6 A Schematic of the Circuitry of the UPR The model depicts the circuitry of the UPR (red) and the S-UPR (blue). Transcriptional control of HAC1 is indicated by an icon representing a rheostat affording gain control of the UPR; Ire1p-dependent HAC1u mRNA splicing is indicated by an icon representing an on/off switch. The I/T and UP signals in the S-UPR are integrated by an AND gate (semicircle, top right), i.e., both conditions must be met to propagate the S-UPR signal. The putative UMF may collaborate with Hac1p to control transcription of UPR target genes (shown) and also be involved in regulating HAC1 transcription (not shown); alternatively, different factors may be involved. The collaboration of Hac1p and UMF is indicated by the diamond-shaped icon, which integrates the information coming from both Hac1p and UMF concentration and activity. In the accompanying paper, Patil et al. (2004) describe a third signaling element, which additionally modifies the transcriptional program of the yeast UPR. The authors show that the transcriptional activator Gcn4p collaborates with Hac1p at the promoters of UPR targets, providing an additional opportunity for integration of information about the physiological state of the cell. Gcn4p is a highly regulated transcription regulator that responds to metabolic conditions, such as amino acid availability. Gcn4p is not UMF, as S-UPR induction of HAC1 proceeds normally in Δgcn4 cells (unpublished data). A recent report from Ogawa and coworkers (Ogawa and Mori 2004) demonstrates autoregulation of HAC1 expression under conditions of extreme and prolonged ER stress, mediated by Hac1p binding to its own promoter. Because the S-UPR can be triggered in Δire1 cells that do not produce Hac1p, autoregulation and the S-UPR are distinct pathways. The existence of multiple mechanisms of HAC1 regulation reinforces the notion that multiple cellular stimuli become integrated to fine-tune an appropriate response. Bipartite Signal Requirement for S-UPR Activation Presently, the molecular details of the pathway by which the S-UPR signal exerts transcriptional control are not known. In particular, it will be of interest to determine where in the cell the two branches of the S-UPR signal are integrated, i.e., how the AND gate is constructed and where it resides. One possibility is that this signal integration event occurs close to the source at the ER membrane. Both temperature shift and inositol starvation can equally induce the I/T signal pathway, and it is conceivable that both conditions affect ER membrane properties similarly. Inositol is an essential precursor for phosphatidylinositol, a major structural phospholipid in yeast that is required for proper functioning of the secretory system (White et al. 1991; Zinser and Daum 1995; Greenberg and Lopes 1996). Previous work has demonstrated an intimate link between inositol regulation and the UPR, presumably to coordinate the concentration of ER lumenal and membrane components (Cox et al. 1997). A similar sensing mechanism operates in cholesterol homeostasis, with sterol composition in ER membranes affecting the activity of SCAP, a membrane-bound regulator of SREBP intramembrane proteolysis (Espenshade et al. 2002). It is likely that elevated temperatures also affect ER membrane properties, such as fluidity (Laroche et al. 2001). If such a property were sensed, it would explain how the temperature effect contributing to the I/T signal is separate from the heat shock response. ER membranes distressed by either inositol deprivation or elevated temperature (the I/T signal) might then control the activity of a membrane-bound component of a signal transduction machine that also senses protein folding conditions (the UP signal) in the ER lumen. Alternatively, the AND gate might be well removed from the ER membrane, with I/T and UP signals traveling separately through the cell and meeting possibly as late as at the promoters of the affected target genes. Components that map onto either signaling pathway need to be identified and placed into the circuit to distinguish between these possibilities. The Transcriptional Output of the S-UPR The transcriptional response elicited by the S-UPR reveals different classes of UPR targets. During the S-UPR, the further activation of UPR targets is not simply proportional to the increase in Hac1p concentration; rather, we observe a multitude of complex responses. Some targets are already maximally transcribed during UPR conditions and are not induced further during the S-UPR, while other targets become significantly more induced. For some targets (a minority), elevated Hac1p concentrations are sufficient to increase transcriptional induction, while for others, S-UPR-derived UMF is also required. We find evidence for both kinds of regulation. The promoters of target genes, therefore, display differential responsiveness to Hac1p concentration and UMF activity. The production of different levels of Hac1p allowed us to isolate and directly assess the responsiveness of target genes to Hac1p concentration under otherwise identical conditions. Those target genes that undergo equivalent activation under both conditions likely have promoters that are saturated by the lower amount of Hac1p, and thus reach full activation more readily. For UPR targets at the other end of the spectrum, induction continues to increase as Hac1p levels increase; lower concentrations of Hac1p are inadequate for full stimulation of these genes, which may have lower affinity for Hac1p. Because genes respond differentially to Hac1p levels, regulation of HAC1 mRNA abundance can be used as a gene-specific gain control for target activation. This control is similar to that observed in regulation of phosphate metabolism, where the differential affinity of certain Pho4p phosphoforms for target promoters allows for the selective activation of a subset of phosphate-responsive genes (Springer et al. 2003). For most target genes, however, the S-UPR further enhances the transcriptional activity even in the presence of high concentrations of Hac1p. For example, INO1 is induced over 75-fold by the S-UPR in WT cells, compared to 33-fold during the UPR in HAC1proHI cells, while the amount of Hac1p produced in both cases is approximately the same. This added induction during the S-UPR is dependent on Hac1p, as ADH1pro-HAC1 cells treated with DTT and shifted to elevated temperature show significantly reduced induction of INO1. The simplest interpretation of these findings is that S-UPR-induced UMF, which may or may not be identical to the transcription factor regulating HAC1 mRNA, collaborates with Hac1p to further boost transcription of these genes. The cis determinants that instruct genes to behave as Class 1, 2, or 3 targets are unknown. One attractive possibility is that target gene promoters have differential affinity for Hac1p and/or UMF. Promoters with stronger affinity for Hac1p would be maximally occupied and fully activated during a normal UPR and would not further respond to increased Hac1p levels (i.e., Class 1 targets). Promoters with lesser affinity for Hac1p would increase in occupancy, and hence transcriptional activation, as Hac1p levels rose during the S-UPR, and would possibly achieve full transcriptional activity only with the additional binding of UMF (i.e., Class 2 and 3 targets). Such a mechanism of promoter-encoded differential responsiveness to transcription factor concentration would explain the selective regulation of subsets of UPR target genes. Links with the Metazoan UPR Higher eukaryotes possess three separate pathways to sense ER stress and direct overlapping but distinct transcriptional outputs (reviewed in Ma and Hendershot 2001). In the first branch, Ire1p senses unfolded proteins in the ER lumen and directs the cleavage of an intron from the mRNA encoding the XBP-1 transcription factor, analogous to the splicing of HAC1 in yeast (Yoshida et al. 2001; Calfon et al. 2002). In a second branch, the transmembrane kinase PERK phosphorylates and inactivates the eIF2-α translation initiation factor (Harding et al. 1999). This attenuates global protein synthesis, but selectively increases the translation of a small number of proteins including the ATF-4 transcriptional activator. Interestingly, ATF-4 is the metazoan ortholog of Gcn4p, the yeast transcription factor demonstrated by Patil et al. (2004) to collaborate with Hac1p. Finally, in a third branch, activation of the UPR in metazoans allows for the ER-to-Golgi transit of the membrane-tethered ATF-6 protein. In the Golgi apparatus, ATF-6 undergoes proteolytic cleavage within its membrane-spanning domain, and the soluble fragment subsequently travels to the nucleus as an active transcription factor (Haze et al. 1999; Ye et al. 2000). XBP-1, ATF-4, and ATF-6 all activate separate but overlapping transcriptional programs that enable the cell to respond to changing conditions in the ER. Notably, the XBP-1 promoter is a target of ATF-6 activation (Yoshida et al. 2001), reminiscent of the circuitry described here for yeast. Conceptually, therefore, HAC1 mRNA upregulation by the S-UPR pathway in yeast takes the place of XBP-1 upregulation by the ATF-6 fragment in metazoans. Moreover, ATF-6 and XBP-1 can heterodimerize (Lee et al. 2002), reminiscent of the proposed collaboration of UMF and Hac1p. Thus, intriguing parallels between yeast and metazoans in the wiring that connects the elements of the UPR signaling circuit are beginning to come to light. These findings suggest a common strategy among all eukaryotic cells for responding to challenges to the secretory system. Maintaining separate ER surveillance pathways creates the potential for cells to integrate multiple signals that, in principle, could convey precise information regarding the nature of the imbalance to afford finely tailored corrective measures. In this view, the UPR operates as a homeostatic control circuit, in which such regulation ensures that components of the secretory apparatus are produced according to need. The challenge now at hand is to decipher the logic between the UPR inducing conditions and the transcriptional output to add physiological explanations to the complex regulation of the response that we observe experimentally. Materials and Methods Yeast strains. The WT strain W303–1A, the Δire1 strain CS165, and the Δhac1 strain JC408 are as described previously (Cox et al. 1993; Cox and Walter 1996). All sec strains used in this study were provided by Robert Fuller (University of Michigan, Ann Arbor, Michigan, United States) and are otherwise genotypically identical to W303. The HSF1c strain was a kind gift of Hillary Nelson (University of Pennsylvania, Philadelphia, Pennsylvania, United States) and contains the R222A allele of HSF1 (Bulman et al. 2001) replacing the chromosomal locus in a W303 background. Strains used in the experiments described in Figure 3A were Δhac1 transformed with pPW598 (HAC1pro-HAC1, HA-tagged HAC1 [Cox and Walter 1996] under its own promoter and with native HAC1 flanking sequences, in a pRS304 background) or with pPW599 (HAC1pro-GFP, the GFP ORF, driven by the HAC1 promoter [defined as the region starting at the mapped start site of HAC1 transcription (Ruegsegger et al. 2001) and extending 500 bp upstream] and flanked by 5′ UTR and 3′ UTR sequences from ACT1). Strains used in experiments described in Figure 4 were HAC1pro-HAC1 and Δhac1 (described above) and Δhac1 transformed with pPW600 (ADH1pro-HAC1, HA-tagged HAC1 with 5′ and 3′ UTR HAC1 sequence subcloned into the p414 ADH expression vector [Mumberg et al. 1995] and transferred to a pRS304 backbone). In Figure 5, HAC1proHI (pPW601) was made by subjecting HAC1pro-HAC1 to QuikChange mutagenesis (Stratagene, La Jolla, California, United States) following the manufacturer's protocol, using oligonucleotides to remove the 15 bp at coordinates −338 to −323 (+1 representing the start site of transcription). Cell culture and plates Yeast cultures were grown in YPD medium (unless otherwise specified) at the indicated temperatures to midlog phase (OD600 ≈ 0.5). For temperature shift experiments, cultures were transferred to a preheated 37 °C water bath shaking incubator. DTT (Roche, Basel, Switzerland) was added to a final concentration of 6 mM, and tunicamycin (Boehringer Mannheim, Indianapolis, Indiana, United States) was added to a final concentration of 1 μg/ml. For experiments involving inositol deprivation in liquid medium, yeast cells were grown in liquid complete synthetic medium described by Sherman (1991), supplemented with myo-inositol (Sigma, St. Louis, Missouri, United States) to a final concentration of 100 μg/ml. Cells were then harvested by filtration, washed three times in prewarmed complete synthetic medium lacking inositol, and then filter-transferred to a flask containing prewarmed complete synthetic medium lacking inositol. For the experiment described in Figure 4C, yeast strains were grown in YPD to midlog phase (OD600 ≈ 0.5), transferred to a 96-well microtiter plate, and serially 5-fold diluted in fresh YPD. Using a liquid transfer prong (“frogging”) tool (Aladin Enterprises, San Francisco, California, United States), approximately 3 μl of all serial dilutions of all strains was simultaneously transferred to complete synthetic plates lacking inositol (described above), either in the absence or presence of 0.2 μg/ml tunicamycin. After approximately 2 d of incubation at 30 °C, plates were photographed using the Epi Chemi II Darkroom GelDoc system (UVP, Upland, California, United States). RNA analysis Isolation of total RNA from yeast cells was carried out with the modified hot-phenol extraction method described in Ruegsegger et al.(2001). For Northern blot analysis, 10 μg of total RNA was separated on a 1.5% w/v agarose gel and transferred to a Duralon-UV nylon membrane (Stratagene), which was incubated with a probe directed against the 5′ exon of HAC1. The mRNA abundance was quantitated using a PhosporImager (Molecular Dynamics, Sunnyvale, California, United States). The membranes were then stripped with two serial washes using 0.1% SDS at 65 °C for 60 min each and incubated with a probe directed against the 3′ exon of ACT1, and mRNA abundance was again quantitated. To control for the variable strength of Northern blot probes across multiple experiments, the relative HAC1/ACT1 mRNA abundance ratio is always normalized to the untreated (t = 0) sample. For the detection of other mRNAs, membranes were incubated with the additional relevant probes (GFP, SSA1) concurrent with the HAC1 probe. All data shown are an average of at least two independent experiments. PolyA+ mRNA was isolated from total RNA using the PolyATract system (Promega, Madison, Wisconsin, United States) according to the manufacturer's instructions. Microarray analysis, using yeast ORF arrays printed at the University of California, San Francisco, Core Center for Genomics and Proteomics (http://derisilab.ucsf.edu/core/, was performed as in Carroll et al. (2001) using protocols and reagents described at http://microarrays.org/. All array data are the average of two independent experiments. For this study, we were obliged to evaluate UPR targets differently than in Travers et al. (2000), as we considered HAC1-independent responses, whereas the former study specifically isolated genes induced by unfolded proteins via Hac1p (z-score ≥ 3.6 σ). Here, UPR targets were defined as those genes that met the following three criteria in a parallel set of microarray experiments using WT (W303) and Δhac1 (JC408) strains. First, induction (log2 of the fold change in gene expression) in WT cells treated with DTT must be at least one standard deviation greater than the mean ([induction WT,DTT − μ WT,DTT]/σ WT,DTT ≥ 1). Second, induction in WT cells treated with tunicamycin must be at least one standard deviation greater than the mean ([induction WT,tunicamycin − μ WT,tunicamycin]/σ WT,tunicamycin ≥ 1). Third, induction in Δhac1 cells treated with DTT must be at least one standard deviation less than the induction in WT cells treated with DTT (or, more awkwardly, [([(induction WT,DTT − μ WT,DTT)/σ WT,DTT] − [(induction Δhac1 ,DTT − μ Δhac1 ,DTT)/σ Δhac1,DTT]) − μ WT,DTT − Δhac1,DTT]/σ WT,DTT − Δhac1,DTT ≥ 1). Isolation and detection of protein from yeast cells Cells were collected by filtration, frozen in liquid nitrogen, and disrupted in 150 μl of 8 M urea/1% SDS by vortexing for 5 min at 4 °C in the presence of 150 μl of silica beads. The samples were then boiled for 5 min and the lysates cleared by centrifugation at 16,200g for 5 min at room temperature. SDS-PAGE was performed on 20 μg of protein separated on NuPAGE 10% w/v SDS-polyacrylamide gels (Invitrogen, Carlsbad, California, United States), and Western blots were visualized using SuperSignal West Dura Extended Duration ECL Substrate (Pierce Biotechnology, Rockford, Illinois, United States) according to the instructions of the manufacturer. Hac1p was detected using a polyclonal antibody raised against the carboxy terminus (see Figure 4) or a monoclonal antibody raised against the HA epitope and directly coupled to horseradish peroxidase (see Figure 5) (Molecular Probes, Eugene, Oregon, United States), and Pgk1p was detected using a commercially available polyclonal antibody (Molecular Probes). Protein abundance was quantified using the Epi Chemi II Darkroom GelDoc system (UVP). Parallel experiments using serial protein dilutions were performed to confirm that the detected protein levels were within the linear range of the system. Transcription shut-off The yeast strain JC218 (Sidrauski et al. 1996; rbp1–1) was grown in YPD at 23 °C to OD600 ≈ 0.5 and then shifted to a 37 °C water bath, shaking at 250 RPM. To induce the UPR, DTT was added to a final concentration of 6 mM. Cells were harvested and total RNA isolated, at 20 min intervals, as described above. Supporting Information Accession Numbers The GenBank accession numbers of the sequences discussed in this paper are Hac1p (NP_ 116622), Ire1p (NP_011946), and tRNA ligase (NP_012448). Microarray data can be accessed at the Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) database as platform number GPL999 and sample numbers GSM16978–GSM1984. We thank Jason Brickner and other members of the Walter lab for helpful discussions and comments on the manuscript, Adam Carroll and Manuel Llinas for assistance with microarrays, Chris Patil and Hao Li for help with bioinformatic analyses, and Robert Fuller and Hillary Nelson for yeast strains. Also, we acknowledge Vladimir Denic for initial observations regarding HAC1 mRNA transcriptional control. This work was supported by a University of California at San Francisco (UCSF) Chancellor's Fellowship to JL, by support from the UCSF Herbert H. Boyer Fund to SB, and by grants from the National Institutes of Health to PW. PW is an Investigator of the Howard Hughes Medical Institute. Conflicts of interest. The authors have declared that no conflicts of interest exist. Author contributions. JHL and PW conceived and designed the experiments. JHL and SB performed the experiments. JHL and PW analyzed the data and wrote the paper. Academic Editor: Steven McKnight, University of Texas Southwestern Citation: Leber JH, Bernales S, Walter P (2004) IRE1-independent gain control of the unfolded protein response. PLoS Biol 2(8): e235. Abbreviations DTTdithiothreitol ERendoplasmic reticulum GFPgreen fluorescent protein I/T signalsignal provided by inositol starvation or temperature shift S-UPRSuper-UPR UMFunfolded protein response modulatory factor UP signalsignal provided by unfolded proteins in the ER UPRunfolded protein response UTRuntranslated region WTwild-type ==== Refs References Bulman AL Hubl ST Nelson HC The DNA-binding domain of yeast heat shock transcription factor independently regulates both the N- and C-terminal activation domains J Biol Chem 2001 276 40254 40262 11509572 Calfon M Zeng H Urano F Till JH Hubbard SR IRE1 couples endoplasmic reticulum load to secretory capacity by processing the XBP-1 mRNA Nature 2002 415 92 96 11780124 Carroll AS Bishop AC DeRisi JL Shokat KM O'Shea EK Chemical inhibition of the Pho85 cyclin-dependent kinase reveals a role in the environmental stress response Proc Natl Acad Sci U S A 2001 98 12578 12583 11675494 Chang HJ Jones EW Henry SA Role of the unfolded protein response pathway in regulation of INO1 and in the sec14 bypass mechanism in Saccharomyces cerevisiae Genetics 2002 162 29 43 12242221 Chapman RE Walter P Translational attenuation mediated by an mRNA intron Curr Biol 1997 7 850 859 9382810 Cox JS Walter P A novel mechanism for regulating activity of a transcription factor that controls the unfolded protein response Cell 1996 87 391 404 8898193 Cox JS Shamu CE Walter P Transcriptional induction of genes encoding endoplasmic reticulum resident proteins requires a transmembrane protein kinase Cell 1993 73 1197 1206 8513503 Cox JS Chapman RE Walter P The unfolded protein response coordinates the production of endoplasmic reticulum protein and endoplasmic reticulum membrane Mol Biol Cell 1997 8 1805 1814 9307975 Espenshade PJ Li WP Yabe D Sterols block binding of COPII proteins to SCAP, thereby controlling SCAP sorting in ER Proc Natl Acad Sci U S A 2002 99 11694 11699 12193656 Greenberg ML Lopes JM Genetic regulation of phospholipid biosynthesis in Saccharomyces cerevisiae Microbiol Rev 1996 60 1 20 8852893 Harding HP Zhang Y Ron D Protein translation and folding are coupled by an endoplasmic-reticulum-resident kinase Nature 1999 397 271 274 9930704 Haze K Yoshida H Yanagi H Yura T Mori K Mammalian transcription factor ATF6 is synthesized as a transmembrane protein and activated by proteolysis in response to endoplasmic reticulum stress Mol Biol Cell 1999 10 3787 3799 10564271 Hirsch JP Henry SA Expression of the Saccharomyces cerevisiae inositol-1-phosphate synthase (INO1) gene is regulated by factors that affect phospholipid synthesis Mol Cell Biol 1986 6 3320 3328 3025587 Kaufman RJ Orchestrating the unfolded protein response in health and disease J Clin Invest 2002 110 1389 1398 12438434 Knop M Finger A Braun T Hellmuth K Wolf DH Der1, a novel protein specifically required for endoplasmic reticulum degradation in yeast EMBO J 1996 15 753 763 8631297 Kohno K Normington K Sambrook J Gething MJ Mori K The promoter region of the yeast KAR2 (BiP) gene contains a regulatory domain that responds to the presence of unfolded proteins in the endoplasmic reticulum Mol Cell Biol 1993 13 877 890 8423809 Kozutsumi Y Segal M Normington K Gething MJ Sambrook J The presence of malfolded proteins in the endoplasmic reticulum signals the induction of glucose-regulated proteins Nature 1988 332 462 464 3352747 Laroche C Beney L Marechal PA Gervais P The effect of osmotic pressure on the membrane fluidity of Saccharomyces cerevisiae at different physiological temperatures Appl Microbiol Biotechnol 2001 56 249 254 11499939 Lee AS Coordinated regulation of a set of genes by glucose and calcium ionophores in mammalian cells Trends Biochem Sci 1987 12 20 23 Lee K Tirasophon W Shen X Michalak M Prywes R IRE1-mediated unconventional mRNA splicing and S2P-mediated ATF6 cleavage merge to regulate XBP1 in signaling the unfolded protein response Genes Dev 2002 16 452 466 11850408 Ma Y Hendershot LM The unfolding tale of the unfolded protein response Cell 2001 107 827 830 11779459 Mori K Sant A Kohno K Normington K Gething MJ A 22 bp cis-acting element is necessary and sufficient for the induction of the yeast KAR2 (BiP) gene by unfolded proteins EMBO J 1992 11 2583 2593 1628622 Mori K Ma W Gething MJ Sambrook J A transmembrane protein with a cdc2+/CDC28-related kinase activity is required for signaling from the ER to the nucleus Cell 1993 74 743 756 8358794 Mori K Kawahara T Yoshida H Yanagi H Yura T Signalling from endoplasmic reticulum to nucleus: Transcription factor with a basic-leucine zipper motif is required for the unfolded protein-response pathway Genes Cells 1996 1 803 817 9077435 Mumberg D Muller R Funk M Yeast vectors for the controlled expression of heterologous proteins in different genetic backgrounds Gene 1995 156 119 122 7737504 Ng DT Spear ED Walter P The unfolded protein response regulates multiple aspects of secretory and membrane protein biogenesis and endoplasmic reticulum quality control J Cell Biol 2000 150 77 88 10893258 Novick P Field C Schekman R Identification of 23 complementation groups required for posttranslational events in the yeast secretory pathway Cell 1980 21 205 215 6996832 Ogawa N Mori K Autoregulation of the HAC1 gene is required for sustained activation of the yeast unfolded protein response Genes Cells 2004 9 95 104 15009095 Patil C Walter P Intracellular signaling from the endoplasmic reticulum to the nucleus: The unfolded protein response in yeast and mammals Curr Opin Cell Biol 2001 13 349 355 11343907 Patil C Li H Walter P Gcn4 and novel upstream activating sequences regulate targets of the unfolded protein response PLoS Biol 2004 2 e246 10.1371/journal.pbio.0020246 15314660 Ron D Translational control in the endoplasmic reticulum stress response J Clin Invest 2002 110 1383 1388 12438433 Rose MD Misra LM Vogel JP KAR2, a karyogamy gene, is the yeast homolog of the mammalian BiP/GRP78 gene Cell 1989 57 1211 1221 2661018 Ruegsegger U Leber JH Walter P Block of HAC1 mRNA translation by long-range base pairing is released by cytoplasmic splicing upon induction of the unfolded protein response Cell 2001 107 103 114 11595189 Sherman F Getting started with yeast Methods Enzymol 1991 194 3 21 2005794 Sidrauski C Walter P The transmembrane kinase Ire1p is a site-specific endonuclease that initiates mRNA splicing in the unfolded protein response Cell 1997 90 1031 1039 9323131 Sidrauski C Cox JS Walter P tRNA ligase is required for regulated mRNA splicing in the unfolded protein response Cell 1996 87 405 413 8898194 Slater MR Craig EA The SSA1 and SSA2 genes of the yeast Saccharomyces cerevisiae Nucleic Acids Res 1989 17 805 806 2644626 Sorger PK Heat shock factor and the heat shock response Cell 1991 65 363 366 2018972 Springer M Wykoff DD Miller N O'Shea EK Partially phosphorylated Pho4 activates transcription of a subset of phosphate-responsive genes PLoS Biol 2003 1 E28 10.1371/journal.pbio.0010028 14624238 Travers KJ Patil CK Wodicka L Lockhart DJ Weissman JS Functional and genomic analyses reveal an essential coordination between the unfolded protein response and ER-associated degradation Cell 2000 101 249 258 10847680 Urano F Wang X Bertolotti A Zhang Y Chung P Coupling of stress in the ER to activation of JNK protein kinases by transmembrane protein kinase IRE1 Science 2000 287 664 666 10650002 White MJ Lopes JM Henry SA Inositol metabolism in yeast Adv Microb Physiol 1991 32 1 51 1882726 Ye J Rawson RB Komuro R Chen X Davé UP ER stress induces cleavage of membrane-bound ATF6 by the same proteases that process SREBPs Molecular Cell 2000 6 1355 1364 11163209 Yoshida H Matsui T Yamamoto A Okada T Mori K XBP1 mRNA is induced by ATF6 and spliced by IRE1 in response to ER stress to produce a highly active transcription factor Cell 2001 107 881 891 11779464 Zinser E Daum G Isolation and biochemical characterization of organelles from the yeast, Saccharomyces cerevisiae Yeast 1995 11 493 536 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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020237Research ArticleCell BiologyDevelopmentGenetics/Genomics/Gene TherapyDanio (Zebrafish)The Zebrafish moonshine Gene Encodes Transcriptional Intermediary Factor 1γ, an Essential Regulator of Hematopoiesis moonshine/tif1γ in HematopoiesisRansom David G zon@enders.tch.harvard.edu 2 ¤Bahary Nathan 2 Niss Knut 2 Traver David 2 Burns Caroline 2 Trede Nikolaus S 2 Paffett-Lugassy Noelle 2 Saganic Walter J 2 Lim C. Anthoney 2 Hersey Candace 2 Zhou Yi 2 Barut Bruce A 1 2 Lin Shuo 3 Kingsley Paul D 4 Palis James 4 Orkin Stuart H 1 2 Zon Leonard I 1 2 1Howard Hughes Medical Institute, Chevy ChaseMaryland, United States of America2Division of Hematology/Oncology, Children's Hospital and Harvard Medical SchoolBoston, Massachusetts, United States of America3Department of Molecular, Cell and Developmental BiologyUniversity of California, Los Angeles, California, United States of America4Department of Pediatrics and Center for Human Genetics and Molecular Pediatric Disease, University of Rochester Medical CenterRochester, New YorkUnited States of America8 2004 17 8 2004 17 8 2004 2 8 e23720 1 2004 26 5 2004 Copyright: © 2004 Ransom et al.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. A Red-Blooded Transcription Factor Hematopoiesis is precisely orchestrated by lineage-specific DNA-binding proteins that regulate transcription in concert with coactivators and corepressors. Mutations in the zebrafish moonshine (mon) gene specifically disrupt both embryonic and adult hematopoiesis, resulting in severe red blood cell aplasia. We report that mon encodes the zebrafish ortholog of mammalian transcriptional intermediary factor 1γ (TIF1γ) (or TRIM33), a member of the TIF1 family of coactivators and corepressors. During development, hematopoietic progenitor cells in mon mutants fail to express normal levels of hematopoietic transcription factors, including gata1, and undergo apoptosis. Three different mon mutant alleles each encode premature stop codons, and enforced expression of wild-type tif1γ mRNA rescues embryonic hematopoiesis in homozygous mon mutants. Surprisingly, a high level of zygotic tif1γ mRNA expression delineates ventral mesoderm during hematopoietic stem cell and progenitor formation prior to gata1 expression. Transplantation studies reveal that tif1γ functions in a cell-autonomous manner during the differentiation of erythroid precursors. Studies in murine erythroid cell lines demonstrate that Tif1γ protein is localized within novel nuclear foci, and expression decreases during erythroid cell maturation. Our results establish a major role for this transcriptional intermediary factor in the differentiation of hematopoietic cells in vertebrates. A new gene acting early in red blood cell development is discovered by genetic analysis in zebrafish. The gene encodes a member of a well-known family of transcription factors ==== Body Introduction Hematopoiesis involves the coordinated processes of cell proliferation and differentiation of a relatively small number of progenitor cells into billions of circulating red and white blood cells (Thisse and Zon 2002). Hematopoiesis in vertebrates, from zebrafish to humans, is an evolutionarily conserved program that produces two waves of stem or progenitor cells that differ both in their embryonic origins and in the lineages of differentiated blood cells produced (Palis and Yoder 2001; Orkin and Zon 2002; Galloway and Zon 2003). The first, or primitive, wave of hematopoiesis originates from ventral mesoderm and gives rise to progenitor cells that differentiate in embryonic blood islands. The primitive wave of hematopoiesis produces a burst of embryonic erythrocytes and macrophages. The second, or definitive, wave of hematopoiesis arises from self-renewing stem cells that develop primarily in the intraembryonic aorta–gonad–mesonephros region. These definitive hematopoietic stem cells seed the later developing marrow spaces, to produce all lineages of adult blood cells, including definitive erythrocytes, myeloid cells, and lymphocytes. We have undertaken a genetic approach to characterize genes that control hematopoiesis using the zebrafish as a model system (Thisse and Zon 2002). As part of a large-scale forward genetic screen, we previously identified bloodless zebrafish mutants that failed to express the erythroid transcription factor gata1 normally in embryonic hematopoietic precursors (Ransom et al. 1996). We named one of these zebrafish genes moonshine (mon), and another group named a noncomplementing allele vampire (Weinstein et al. 1996). Here, we have determined that mutations in the mon gene cause a disruption in both primitive embryonic and definitive adult hematopoiesis, resulting in a severe loss of erythroid cells. Erythroid progenitor cells in mon mutants are initially present, but fail to express normal levels of hematopoietic transcription factors and undergo apoptosis. Positional cloning identifies the mon gene as the zebrafish ortholog of mammalian transcriptional intermediary factor 1γ (TIF1γ), a member of the TIF1 family of transcriptional coactivators and corepressors (Le Douarin et al. 1995; Friedman et al. 1996; Kim et al. 1996; Venturini et al. 1999; Peng et al. 2002). The three members of the vertebrate TIF1 family (α, β, and γ) are large nuclear proteins that each contain an N-terminal RBCC or TRIM domain (Reymond et al. 2001) composed of a RING finger, two B-boxes, and a coiled-coil domain. TIF1 family members also contain a C-terminal plant homeodomain finger and bromodomain that are characteristic of chromatin remodeling factors. TIF1α has been shown to associate with a variety of ligand-bound nuclear hormone receptors (Le Douarin et al. 1995) and function as a coactivator for retinoic acid receptors (Zhong et al.1999). TIF1β has been shown to act as a corepressor for the large family of Krüppel-associated box (KRAB) domain zinc-finger transcription factors (Friedman et al. 1996; Abrink et al. 2001). In contrast, TIF1γ does not associate directly with either nuclear receptors or KRAB domains that bind to the other TIF1 family members (Venturini et al. 1999; Abrink et al. 2001). Biochemical studies also demonstrate that TIF1γ forms both homo-oligomers and hetero-oligomers with TIF1α but not with TIF1β (Peng et al. 2002). The murine Tif1α and Tif1γ genes have not yet been subjected to gene targeting experiments, whereas analysis of mouse mutants demonstrates that Tif1β is required for postimplantation embryogenesis and mesoderm induction in particular (Cammas et al. 2000). Taken together, these studies suggest that a major function of TIF1 family members is to link DNA-binding proteins with other coactivators or corepressors during development. Our studies establish that tif1γ functions as an essential regulator of embryonic and adult hematopoiesis in vertebrates. Cell transplantation studies demonstrate that tif1γ acts in a cell-autonomous manner during embryonic hematopoiesis. The tif1γ gene is expressed specifically in ventral mesoderm and hematopoietic progenitors, then downregulated as erythroid maturation occurs. Tif1γ protein localizes to a novel class of nuclear bodies in both primary mouse embryo fibroblasts and erythroleukemia cell lines. Taken together, our studies demonstrate that Tif1γ is required for normal erythroid cell development and survival. Results The Zebrafish mon Gene Is Essential for Both Primitive and Definitive Erythropoiesis In order to determine when the mon gene is required in development, we first examined hematopoietic gene expression and apoptosis in zebrafish homozygous mon mutant embryos. During embryogenesis, homozygous zebrafish mon mutants have no red blood cells (RBCs) visible in circulation (Ransom et al. 1996; Weinstein et al. 1996). The mon mutants initiate expression of gata1 in hematopoietic cells around the five-somite stage, similar to wild-type embryos (data not shown); however, based on TUNEL staining, the differentiating erythroid cells undergo programmed cell death from the 12-somite stage to 22 h postfertilization (hpf) (Figure 1A and 1B, arrows). At 12 somites, gata1 expression is only slightly reduced. By 18–22 hpf, hematopoietic-specific markers such as gata1, scl, gata2, and ikaros are not detected in the embryonic blood island (Figure 1A and 1B; unpublished data). The hematopoietic cells are thus correctly specified early during the development of mon mutant embryos, but these precursors undergo cell death. Based on expression of c-myb and rag1 (Figure 1B, arrows), mon mutants have normal myeloid and lymphoid development, respectively. In addition to the deficit of RBCs in mon mutants, there is a prominent loss of fin-fold and tail mesenchyme (Ransom et al. 1996). TUNEL staining of mon mutants demonstrates extensive apoptosis of mesenchymal cells in the trunk and tail bud regions (Figure 1A and 1B, arrows). The mon gene is thus required for normal development and survival of both committed erythroid progenitor cells and posterior mesenchymal cells. Figure 1 Zebrafish mon Mutants Have Severe Defects in Primitive Hematopoiesis (A) Whole-mount TUNEL assays reveal that ventral-posterior mesodermal cells undergo apoptosis in homozygous montg234 mutant embryos. Whole-mount in situ hybridization of gata1 detected at the 12- and 18-somite stage in genotyped embryos. Posterior views, anterior to the left. (B) Extensive apoptosis is visible in the trunk and tail (arrowhead) and also in hematopoietic cells of the embryonic blood island at 22 h of development (arrow). Whole-mount in situ hybridization at 22 hpf including scl, gata2, gata1, ikaros, and myb in montg234 mutants. Expression of myb is greatly reduced in the blood islands because of a loss of erythroid cells, but embryonic macrophages are still present (arrows). The expression of rag1 in thymic T-cells appears normal in mon mutants at 5 d postfertilization (arrow heads). Lateral views of 22 hpf and 5-d-old embryos. We next examined definitive hematopoiesis in rare surviving homozygous adult zebrafish mon mutants. Mutations in mon are generally lethal by 10 to 14 d of development (Ransom et al. 1996), although rare mon homozygous mutants (approximately 1 in 500 bloodless embryos) of all tested alleles survive to adulthood. Adult mon mutants show cardiac hypertrophy, presumably due to the severe anemia leading to a high output state (Figure 2). In wild-type zebrafish, the adult site of hematopoiesis is the kidney (Al Adhami and Kunz 1977), which contains erythroid, lymphoid, and myeloid populations at various stages of differentiation (Bennett et al. 2001). In mon homozygous mutants, there is a severe block in maturation at the proerythroblast stage (Figure 2), whereas the differentiation of myeloid cells is normal (unpublished data). This demonstrates that the mon gene product acts during both primitive and definitive erythropoiesis. Figure 2 Zebrafish mon Mutants Also Have Severe Defects in Definitive Hematopoiesis Adult phenotype of wild-type and mon mutants. A rare surviving montb222 homozygous adult shows significant cardiomegaly in comparison to a wild-type age-matched control. Wright–Giemsa stained marrow of wild-type adult in comparison to a homozygous mutant. Note the dramatic reduction of terminally differentiated erythroid cells and the presence of abnormally large megaloblastic proerythroblasts in the montb222 mutant marrow. Positional Cloning Identifies mon as the Zebrafish Ortholog of Mammalian TIF1γ We identified the mon gene by positional cloning using a panel of 2,200 diploid mutants collected from Tübingen background (TU)/WIK strain hybrid parents carrying the montg234 allele. The mon mutant gene was positioned on Chromosome 8 between microsatellite markers z987 and z11001 (Figure 3A) (Knapik et al. 1998). For positional cloning purposes, over 12,000 polymorphic markers were screened using amplified fragment length polymorphism (AFLP) (Ransom and Zon 1999), and 36 markers within the interval were isolated. One of these, MA3, was found to be 0.3 cM from the gene (Figure 3A) and was utilized as the starting point of a chromosomal walk. A critical P1 bacterial artificial chromosome clone (PAC), 107N19, was obtained that spanned the genetic interval. Two simple sequence conformation polymorphism (SSCP) markers found on this PAC clone flank the critical genetic interval. The marker 80M12-T7 maps two recombinants out of 4,400 meioses telomeric of the mutation, and the marker 157J23-T7 maps one recombinant centromic of the mutation (Figure 3A). The end sequences and SSCP markers of PAC 107N19 are found in the zebrafish genomic sequence contig ctg23107 (http://www.ensembl.org/Danio_rerio/) containing a predicted zebrafish TIF1 family gene. This PAC was hybridized to a kidney cDNA library, resulting in the isolation of four clones that represented the same gene. Figure 3 Positional Cloning Identifies the mon Gene as Zebrafish tif1γ (A) Physical map of the mon locus on zebrafish Chromosome 8. Microsatellite markers z987 and z11001 were used to initially identify recombinants in a panel of 2,200 diploid montg234 homozygous mutants. The AFLP marker MA3 was used to initiate a chromosomal walk in PAC libraries. The critical PACS that were isolated to encompass the mon locus are indicated by numbers above bar. The PAC 107N19 defines the critical interval for the mon gene. This PAC was used as a probe to screen cDNA libraries and to identify zebrafish tif1γ cDNAs. Numbers below the bar indicate the number of recombinants identified by SSCP analysis. (B) Clustal-W–generated phylogentic tree of zebrafish (Danio rerio [Dr]) Tif1γ and Tif1α peptide sequences in comparison to TIF1 family members: human (Hs) TIF1α, TIF1β, and TIF1γ; mouse (Mm) Tif1α, Tif1β, and Tif1γ;; and fly (Dm) bonus. (C) Diagrams illustrating the structure of the Tif1γ-predicted peptide and the three identified point mutants. RING finger (RING), B-boxes (B1 and B2), plant homeodomain finger (PHD) and bromodomain (BROMO). Numbers below the first diagram indicate the percent identity shared between each of these domains in zebrafish and human TIF1γ. The predicted truncated proteins are indicated. (D) DNA sequence chromatograms showing the three ENU-induced point mutants in comparison to wild-type control sequences The mon gene encodes a member of the TIF1 family of transcriptional cofactors (Figure 3B and 3C). The coding sequence of mon is most similar to human TIFγ (Le Douarin et al. 1995; Friedman et al. 1996; Venturini et al. 1999), and the locations of exon boundaries are conserved between the zebrafish and human genes (unpublished data). The mon locus on zebrafish Chromosome 8 is also predicted to be syntenic to the region of human Chromosome 1p that contains the TIF1γ gene based on the conserved locations of 12 other orthologous gene pairs, including NRAS, mapped to these regions in human and zebrafish (Barbazuk et al. 2000). Therefore, based on sequence similarity and chromosomal location, the zebrafish mon gene is the likely ortholog of the human TIF1γ gene. We have identified ethyl-nitrosourea (ENU)-induced point mutations in three alleles of mon (Figure 3C and 3D), each of which generates a premature stop codon. The montb222b and montg234 alleles have a severe phenotype with no circulating blood cells. In contrast, the monm262 allele has 10–100 circulating blood cells by 48 hpf, in comparison to the approximately 3,000 RBCs in the circulation of wild-type or heterozygous embryos at the same time point. The monm262 allele was found to encode a premature stop codon at position E40, which would encode a putative protein of only 40 amino acids. Although this mutation would be expected to lead to a complete loss of mon gene product, another methionine is found downstream at amino acid position 104. In vitro translation experiments in reticulocyte lysates demonstrate reinitiation of translation from this methionine (unpublished data). Therefore, the hypomorphic larval phenotype of the monm262 allele is likely due to partial loss of mon function or expression. The presence of mutations in each of the mon alleles indicates that defective Tif1γ function is the cause of the mon phenotype. In order to determine whether tif1γ is expressed in hematopoietic mesoderm, we next examined zebrafish embryos by whole-mount in situ hybridization (Figure 4A). tif1γ mRNA is expressed maternally and is found throughout the embryo during blastula stages. During gastrulation and epiboly stages, zygotic expression of mon is highest in the mesendoderm of the germ ring. At tail bud and early somite stages a high level of tif1γ expression delineates a horseshoe-shaped population of ventral/lateral mesoderm that will give rise to blood and also expresses stem cell leukemiahematopoietic transcription factor (scl) (Liao et al. 1997). This group of cells continues to express tif1γ and scl while it converges and forms the embryonic blood island (Detrich et al. 1995). The tif1γ gene is also highly expressed in the central nervous system as well as the mesenchyme of the trunk and tail. Homozygous montg234 mutants have a greatly reduced amount of tif1γ mRNA in all tissues consistent with nonsense-mediated message decay. Thus, zebrafish tif1γ is specifically expressed in ventral mesoderm and putative hemangioblasts prior to and during the embryonic stages when hematopoietic progenitors are undergoing apoptosis in mon mutants. We also compared the expression of zebrafish mon to mouse Tif1γ (Figure 4A and 4B). Mouse Tif1γ is highly expressed in erythroid blood islands of the yolk sac, and it is subsequently expressed in the fetal liver at a high level, and in other tissues, including the central nervous system. Taken together these results strongly suggest that zebrafish mon and mouse Tif1γ are orthologs that function during hematopoiesis. Figure 4 The mon/tif1γ Gene Is Highly Expressed in Hematopoietic Mesoderm (A) In situ hybridization of zebrafish embryos demonstrating the embryonic expression of tif1γ. tif1γ is initially expressed as a maternal mRNA. Increased expression of tif1γ in ventral-lateral mesoderm begins between the one- to three-somite stages and increases through early development. By five somites, tif1γ is strongly expressed in lateral stripes of mesoderm that also express scl. At 22 hpf tif1γ is expressed broadly in the brain, spinal cord, trunk, and tail mesenchyme, but is at much higher levels in hematopoietic cells of the blood island. Zebrafish tif1α is also broadly expressed but relatively more uniform in most tissues, in comparison to tif1γ. Tif1α is weakly expressed at early somite stages in hematopoietic mesoderm and uniformly expressed at 22 hpf, including expression in the blood islands. Expression of scl at five somites and 22 hpf highlights the embryonic blood island in comparison to tif1γ expression. (B) In situ hybridization of mouse embryos detects broad expression of Tif1γ at embryonic day 8.5 including the yolk sac blood islands (arrow). AT embryonic day 12.5, there is high level expression in the fetal liver (arrow) and broad expression in the embryonic brain, spinal chord, gut, and muscle. Given that mammalian TIF1γ has been shown to form hetero-oligomers with Tif1α (Peng et al. 2002), we searched for additional TIF1 family members in zebrafish to compare with tif1γ. Using zebrafish expressed sequence tag (EST) sequences, we designed primers to RT-PCR amplify a TIF1-related cDNA from embryonic 10-hpf and 24-hpf RNA. This cDNA encodes a predicted zebrafish ortholog of human TIF1α based on predicted amino acid sequences (see Figure 3B). In addition, zebrafish tif1α ESTs map to LG4 in a region predicted to be syntenic to the region of human Chromosome 7 that contains the TIF1α gene based on the conserved locations of eight other orthologous gene pairs, including SEMA3A, mapped to these regions in human and zebrafish (Barbazuk et al. 2000). We next compared the embryonic expression pattern of tif1α mRNA to tif1γ by in situ hybridization. Like mammalian TIF1α (Le Douarin et al. 1995; Niederreither et al. 1999), the predicted zebrafish tif1γ gene is broadly expressed (see Figure 4A). At five somites, zebrafish tif1α does not display the relatively high expression in the horseshoe-shaped region of hematopoietic mesoderm seen with tif1γ. At later stages, tif1α is evenly expressed throughout most of the embryo, including the developing blood islands. Therefore, tif1α is coexpressed in the same cells with tif1γ and may therefore be available to form hetero-oligomers in vivo. Forced Expression of tif1γ Rescues Hematopoiesis in mon Mutants To further confirm that a mutation in the zebrafish tif1γ gene is responsible for the mon mutant phenotype we performed embryo rescue experiments (Figure 5A; Table 1). Microinjection of synthetic wild-type mon mRNA at the one-cell stage rescues the formation of embryonic erythrocytes in genotyped mutant embryos without causing obvious defects in embryonic patterning or organogenesis. At 4 d of development, 70% (n = 10) of montg234 mutants show significant (greater than 200 cells in comparison to a wild-type estimate of 3,000 cells) rescue of circulating hemoglobinized RBCs in comparison to control sibling mutants (n = 75). Based on the correction of the jagged fin-fold phenotype (Ransom et al. 1996), the mesenchymal cells are rescued to a similar extent as the anemia (unpublished data). Overexpression of mon did not result in expanded blood cell numbers in wild-type embryos and was not toxic at doses that rescue the phenotype of mon mutants (unpublished data). Since there were no expanded or ectopic blood populations in the embryos, these rescue experiments suggest that mon functions as a permissive factor required for hematopoiesis. Figure 5 Overexpression of Wild-Type tif1γ mRNA or Marrow Transplantation Rescues Embryonic Hematopoiesis in mon Mutants (A) montg234 mutants are rescued by injection of mRNA-encoding wild-type Tif1γ protein. At 4 d of development, large numbers of RBCs are visible in the circulation of wild-type zebrafish, shown here by o-dianisidine staining of hemoglobin. Uninjected monttg234 homozygous mutants are completely bloodless. Injection of 100 pg of wild-type tif1γ mRNA rescues erythropoiesis in mutant embryos. o-dianisidine-stained larvae are shown in ventral views to highlight blood in vessels. (B) Transplantation of wild-type zebrafish marrow cells carrying a gata1:GFP transgene into 2-d-old embryos reconstitutes erythropoiesis, but not viability, in montg234 homozygous mutants. Still frames from movies of live embryos at day 3 posttransplant highlight less than 100 GFP+ RBCs in circulation (top). Transplanted cells were observed to proliferate resulting in thousands of donor-derived erythrocytes 7 d later (bottom). Arrows indicate the hearts of control and transplanted zebrafish. See Videos S1–S4. Table 1 Overexpression of tif1γ mRNA Rescues mon Mutants: Hematopoietic Phenotypes Synthetic tif1γ mRNA (100 pg) was injected at the one-cell stage into embryos of the indicated genotypes. For the mon embryos, circulating cells where counted each day through 4 d, when the embryos were fixed and stained with o-dianisidine to detect hemoglobin in mature RBCs. Normal embryos contain approximately 3,000 circulating cells at these time points. Results are given as number of embryos with the indicated phenotype. Numbers in parentheses represent percentage of total embryos analyzed Marrow Transplantation Rescues Erythropoiesis in mon Mutants The high levels of tif1γ expression in erythroid cells suggest that it functions as a cell-autonomous regulator of gene expression in hematopoietic cells. In order to test this hypothesis, we transplanted wild-type adult zebrafish kidney marrow cells carrying a gata1:green fluorescent protein (GFP) transgene into 48-hpf mon mutant embryos (Figure 5B; Table 2). The gata1:GFP transgene makes use of the gata1 promoter to drive GFP expression and can thus be used to mark donor-derived erythroid cells (Long et al. 1997). Untransplanted mutant embryos have no embryonic blood cells in circulation. Following transplantation, mutant host embryos were observed daily for 2 wk. Of 191 mutant embryos injected, 129 (68%) showed GFP+ cells in circulation 2 d later. Many recipients showed robust increases in donor-derived cells over the observation period. Of 81 recipients initially scored as having less than ten GFP+ cells at day 2 posttransplant, 13 (16%) of these demonstrated a marked increase in erythroid cells with 100–1,000 GFP+ cells in circulation 6 d later. By day 10, these transplanted embryos showed approximately 3,000 cells in circulation, similar to the number of blood cells in normal embryos. Despite robust reconstitution of blood cells, mutant recipients did not inflate their swim bladders and thus failed to survive longer than nontransplanted sibling controls, all dying by 3 wk of age. In contrast, 13/35 (37%) heterozygous montg234 transplants survived to early adulthood. Similar transplants of wild-type cells can fully rescue vlad tepes (gata1) mutants (Traver et al. 2003). Therefore, the results of cell transplantations suggests that tif1γ plays a cell-autonomous role in erythroid cells, and its role in nonhematopoietic tissues, such as trunk mesenchyme or the nervous system, is also required for embryo survival. Table 2 Marrow Transplantation Rescues Hematopoiesis But Not Survival in mon Mutants: Embryos with Transplanted Erythroid Cells Between 100 and 1,000 kidney marrow cells from adult gata1:EGFP transgenic donors were injected per zebrafish embryo at 48 hpf. Individual transplanted embryos were anesthetized and visualized for GFP+ erythroid cells. By 10 d posttransplantation the indicated number of embryos had an estimated 100 to 3,000 GFP+ cells in circulation. At 3 mo the indicated number of fish were alive. The relative percentage of embryos is shown in parentheses Tif1γ in Punctate Nuclear Foci Is Developmentally Regulated In order to examine the subcellular distribution of Tif1γ protein, we generated an affinity-purified rabbit polyclonal antiserum directed against the C-terminal 15 amino acids conserved in human TIF1γ and mouse Tif1γ. Immunofluorescence of mouse embryo fibroblast nuclei with the anti-Tif1γ antiserum demonstrates that Tif1γ is localized in small nuclear foci (Figure 6A). The localization of Tif1γ protein appears different from the more diffuse nuclear patterns typically seen in studies of Tif1α (Remboutsika et al. 2002) or TIF1β (Cammas et al. 2002). A recent report demonstrates that TIF1β associates with heterochromatin-containing foci after retinoic acid treatment or serum starvation (Cammas et al. 2002). Thus, localization or expression of the TIF1 proteins may be regulated during distinct developmental processes or by environmental cues. The nuclear foci that contain Tif1γ do not colocalize with two markers of heterochromatin, HP1α protein and DAPI staining of DNA (Figure 6A). Furthermore, Tif1γ does not colocalize with promyelocytic leukemia gene product (PML) nuclear bodies, DNA repair complexes that contain Mre11, or transcriptional complexes containing TFII-B (unpublished data). We next examined the expression of Tif1γ protein during the differentiation of G1E cells, a murine erythroleukemia cell line that can terminally differentiate into erythrocytes when a Gata1:estrogen receptor fusion protein is stabilized in response to estrogen exposure (Weiss et al. 1997). Western blot analysis demonstrated that Tif1γ protein expression decreases with terminal erythroid differentiation (Figure 6B). Consistent with this finding, after 24 hpf, zebrafish mon mRNA expression falls during the terminal maturation of the primitive erythroid cells (unpublished data). In two different murine erythroleukemia cell lines (MEL and G1E), Tif1γ is also expressed in nuclear foci, and even though the overall Tif1γ protein level is reduced, this nuclear foci localization does not change with differentiation (unpublished data). This provides further support for the hypothesis that Tif1γ acts within novel nuclear foci, during erythroid differentiation. Figure 6 Mammalian Tif1γ Protein Localizes to Nuclear Bodies Distinct from Heterochromatin (A) Deconvolved immunofluorescence images of a mouse embryonic fibroblast cell nucleus stained with an anti-Tif1γ antibody and stained with a monoclonal antibody directed against HP1α. This is also compared to DAPI staining. The merged images of the nucleus show that Tif1γ does not colocalize with the HP1α or DAPI staining of heterochromatin while HP1α and DAPI staining overlap. (B) G1ER mouse erythroleukemia cells express high levels of Tif1γ protein as detected by Western blot analysis. Expression of Tif1γ decreases during Gata1-dependent erythroid maturation induced by β-estradiol treatment to induce a Gata1–ER fusion protein. Discussion The zebrafish is an excellent model system to elucidate the molecular machinery controlling gene expression during hematopoiesis (Thisse and Zon 2002; Galloway and Zon 2003). As part of a large-scale forward genetic screen, we originally identified a complementation group of independent mutant alleles in the zebrafish gene that we named moonshine (Ransom et al. 1996). Positional cloning was used to identify the mon gene, establishing a critical role for a transcriptional intermediary factor, Tif1γ, during hematopoietic development. The mon Gene Encodes the Zebrafish Ortholog of Mammalian TIF1γ Our results strongly support the conclusion that we have positionally cloned the zebrafish mon gene correctly, and it is the ortholog of mammalian Tif1γ. Tif1γ is present in the critical genetic interval encompassing a single approximately 50-kb PAC clone defined by linkage analysis (see Figure 3). Sequence analysis indicates that zebrafish tif1γ is most similar in predicted amino acid sequence and intron/exon structure compared to the predicted orthologous human and mouse genes. Zebrafish tif1γ is located in a region of zebrafish Chromosome 8 syntenic to the region of human Chromosome 1 containing TIF1γ. We identified point mutations in tif1γ from three different alleles of mon that each result in premature stop codons and mRNA decay. In addition, tif1γ/Tif1γ is highly expressed in hematopoietic cells throughout embryogenesis in both zebrafish and mouse (see Figure 4). And as predicted, forced expression of wild-type tif1γ mRNA efficiently rescues hematopoiesis in mon mutants and does not perturb hematopoiesis in wild-type embryos (see Figure 5). We have also cloned the predicted zebrafish ortholog of tif1α, which is more uniformly expressed in zebrafish embryos like mammalian TIF1α (Le Douarin et al. 1995; Niederreither et al. 1999) (see Figures 3A and 4A) and may therefore be available to form hetero-oligomers with Tif1γ protein in developing hematopoietic cells. Comparing available zebrafish and mammalian TIF1-predicted amino acid sequences, it appears that the Tif1γ orthologs are the most highly conserved family members while the Tif1α sequences are relatively more divergent. We have not found a Tif1β ortholog, thus far, in the zebrafish or fugu genome or EST sequences. It is possible that Tif1β, like the KRAB domain transcription factors it binds to, may be present only in tetrapods (Urrutia 2003). However, more complete genome sequences will be needed to confirm this hypothesis. Based on our analysis of zebrafish mon mutants, it is reasonable to predict that Tif1γ, the most evolutionarily conserved TIF1 family member, plays a similarly essential role in human and mouse hematopoiesis. Mutations in tif1γ Cause Apoptosis of Erythroid Progenitors Our examination of hematopoietic gene expression, apoptosis, and marrow histology in mon mutants demonstrates that early erythroid progenitors are formed in homozygous mutants, but they fail to properly differentiate and instead undergo programmed cell death (see Figure 1). The expression of gata1 appears to initiate normally in the committed erythroid cells of mon mutants. However, the cells are abnormal prior to the complete loss of gata1 expression. TUNEL-positive apoptotic cells are abundant by the 12-somite stage of development, and by 22 hpf all hematopoietic gene expression is extinguished. The expression of marker genes, including scl and gata2, characteristic of hematopoietic stem cells and primitive hematopoietic progenitors, are also not detected in the embryonic blood islands of mutants at 22 hpf. This indicates that the mutant hematopoietic cells are not blocked prior to commitment to the erythroid lineage, but instead develop as abnormal erythroid cells and undergo apoptosis, similar to gata1-deficient erythroid cells (Fujiwara et al. 1996; Lyons et al. 2002). Defective erythropoiesis and severe anemia were also observed in rare surviving homozygous mutant mon adults, demonstrating that tif1γ is also required in definitive hematopoiesis (see Figure 2). The zygotic phenotypes of mon mutants may not reveal the function of maternally inherited Tif1γ. Maternally expressed zebrafish Tif1γ may play roles in hematopoiesis or other aspects of organogenesis that are not detectable due to the presence of wild-type mRNA in eggs laid by heterozygous mothers. Analysis of the offspring of homozygous mon mutant female zebrafish will aid in defining the function of this maternal mRNA. The present analysis of zygotic mon mutants provides data that are consistent with the conclusion that tif1γ is essential for erythropoiesis but do not rule out essential functions in other hematopoietic lineages. The hematopoietic phenotype of mon mutants resembles the loss of erythroid cells seen in both mouse Gata1 knockout embryos and zebrafish vlad tepes (gata1) mutant embryos (Fujiwara et al. 1996; Lyons et al. 2002). In an effort to determine if there is a genetic relationship between mon and gata1, we tested their ability to rescue erythropoiesis. Both injection of gata1 mRNA into mon homozygous mutant embryos and injection of tif1γ mRNA into gata1 knock-down embryos failed to rescue hematopoiesis (unpublished data). We also tested for a direct interaction between Tif1γ and Gata1 proteins by coimmunoprecipitation and yeast two-hybrid assays and found no association (unpublished data). Although the mutations in each of these genes arrest cells at a similar stage of development, our results suggest that gata1 and tif1γ act independently. This does not rule out the possibility that parallel genetic pathways involving gata1 and tif1γ, operating together, regulate gene transcription within blood cells. The Role of Tif1γ in Primitive and Definitive Erythropoiesis Taken together, our data suggest that tif1γ is required as a permissive cofactor for the erythroid lineage-specific control of hematopoietic gene expression. We reasonably predict that Tif1γ protein functions as a transcriptional intermediary factor in hematopoietic progenitor cells given that both TIF1α (Zhong et al. 1999) and TIF1β (Friedman et al. 1996; Abrink et al. 2001) have been shown to act as intermediary factors that positively or negatively regulate gene transcription. These studies indicate that TIF1α and TIF1β act as scaffolds that link different classes of DNA-binding proteins and chromatin-associated proteins into larger regulatory complexes. Tif1γ is detected within nuclear foci (see Figure 6), which, based on our analysis, do not appear to correspond to several types of previously described nuclear bodies, including PML bodies. Localization of Tif1γ to these nuclear bodies may be regulated by posttranslational modification such as SUMO modification that is required for PML to form PML nuclear domains (Zhong et al. 2000a, 2000b; Best et al. 2002). These foci may serve as assembly points where Tif1γ forms multisubunit complexes with DNA-binding transcription factors and their other essential coactivators or corepressors, during the early stages of erythroid differentiation. It will be important to determine the identity of Tif1γ-interacting proteins in nuclear foci and establish how they function with Tif1γ to regulate blood cell development. Materials and Methods Zebrafish and mouse strains and studies Zebrafish were maintained and staged as described (Westerfield 1998). The alleles montb222b and montg234 were generated in a large-scale screen for ENU-induced mutations (Ransom et al. 1996) on the TU, whereas the monm262 allele was derived on the AB strain and was originally called vampire (Weinstein et al. 1996). Mapping strains were constructed by mating to WIK or SJD polymorphic strains. Linkage analysis was performed on haploid or diploid embryos obtained from TU/SJD or TU/WIK hybrids. In situ hybridization and stainings of embryos were done as described (Thompson et al. 1998; Liao et al. 2002). In situ hybridization of mouse embryos was performed as described (Kingsley et al. 2001). Genomic DNA isolation, genotyping, AFLP analysis, and chromosomal walking were each performed as previously described (Brownlie et al. 1998; Ransom and Zon 1999). A complete list of primers for genetic mapping, RT-PCR, and sequencing of mon are available on request. mRNA expression constructs, morpholinos, and microinjection The full-length mon cDNA was subcloned into EcoRI and XhoI sites in the pCS2+ vector. Synthetic mRNA was transcribed in vitro, and microinjection was performed essentially as described (Liao et al. 2002). Cell transplantation Whole kidney marrow cells were isolated from adult gata1:EGFP transgenic donors, resuspended in 0.9X phosphate-buffered saline + 5% fetal bovine serum, and injected into the sinus venosus of 2-d-old montg234 −/− and control embryos. Between 102 and 103 kidney marrow cells were injected per embryo. Individual transplanted embryos were anesthetized and visualized daily under an inverted fluorescent microscope (DM-IRE2; Leica, Wetzlar, Germany) for GFP+ cells over a span of 12 d. On day 13 posttransplant, all surviving larvae (12/129; 9%) were placed in tanks and monitored for survival. Antibodies, immunostaining, and immunoblots Antisera against the human C-terminal TIF1γ sequence RRKRLKSDERPVHIK was generated in rabbits (Genemed Synthesis, South San Francisco, California, United States) and affinity purified. Mouse embryonic fibroblasts grown on coverslips were immunostained with HP1α (Chemicon, Temecula, California, United States) and Tif1γ antisera simultaneously. In brief, cells were fixed in 4% paraformaldehyde for 5 min, washed with phosphate-buffered saline, and blocked with 5% serum (PBST) for 30 min. After incubation with the primary antibodies (PBST, 60 min) cells were washed three times with PBST and incubated with secondary antibodies (Jackson Laboratory, Bar Harbor, Maine, United States) followed by three washes in PBST. Cells were embedded with Vectashield/DAPI and analyzed using an Axioplan 2 microscope (Zeiss, Jena, Germany). Digital images were processed using the Volocity 1.0 software (Improvision, Lexington, Massachusetts, United States). G1E cell differentiation experiments were performed essentially as described (Weiss et al. 1997). Supporting Information Transplantation of wild-type zebrafish marrow cells carrying a gata1:GFP transgene into 2-d-old embryos reconstitutes erythropoiesis, but not viability, in montg234 homozygous mutants. Movies of live embryos at day 3 posttransplant highlight less than 100 GFP+ RBCs in circulation. Transplanted cells were observed to proliferate, resulting in thousands of donor-derived erythrocytes 7 d later. Movies present GFP-fluorescent images of live zebrafish larvae. Video S1 Untransplanted Control montg234 Homozygous Mutants Had No Fluorescent Cells in Circulation at 3 Days of Development (13.7 MB MOV). Click here for additional data file. Video S2 One Day after Transplantation, Less Than 100 GFP+ Erythrocytes Were Visible in the Circulation of Three montg234 Homozygous Mutants (11.3 MB MOV). Click here for additional data file. Video S3 Untransplanted Control montg234 Homozygous Mutants Had No Fluorescent Cells in Circulation at 9 Days of Development (7.9 MB MOV). Click here for additional data file. Video S4 Seven Days after Transplantation, Thousands of Donor-Derived Erythrocytes Were Visible in the Circulation of a Representative montg234 Homozygous Mutant (11.2 MB MOV) Click here for additional data file. Accession Numbers The GenBank (http://www.ncbi.nlm.nih.gov/Genbank) accession numbers for the genes and gene products discussed in this paper are fly bonus (AAF19646), human TIF1α (015164), human TIF1β (Q13263), human TIFγ (Q9UPN9), human TIF1γ (Q9UPN9), mon (AY59853), mouse Tif1α (Q64127), mouse Tif1β (AAH58391), and mouse Tif1γ (NP444400). The cDNA sequences of zebrafish mon/tif1γ and tif1α have been deposited in GenBank under the accession numbers AY598453 and AY598454, respectively. We thank A. Davidson, J. Amatruda, and J. Christian for critical review of this manuscript; J. Postlethwait and W. Talbot for helpful discussions and experimental advice; B. Weinstein for the gift of the m262 allele of mon; and D. Giarla for administrative assistance. DGR was funded by the American Cancer Society and an award to Oregon Health and Science University by the Howard Hughes Medical Institute (HHMI) Biomedical Research Support Program for Medical Schools. LIZ and SHO are investigators of the HHMI. This work was supported by grants from the National Institutes of Health. Conflicts of interest. The authors have declared that no conflicts of interest exist. Author contributions. DGR, NB, KN, DT, CB, NST, YZ, JP, SHO, and LIZ conceived and designed the experiments. DGR, NB, KN, DT, CB, NST, NPL, WJS, CAL, CH, BAB, and PDK performed the experiments. DGR, NB, KN, DT, CB, NST, NPL, YZ, JP, SHO, and LIZ analyzed the data. DGR, NB, KN, DT, NST, YZ, BAB, SL, and JP contributed reagents/materials/analysis tools. DGR, NB, KN, DT, and LIZ wrote the paper. Academic Editor: William Talbot, Stanford University ¤Current address: Department of Cell and Developmental Biology, Oregon Health and Science University, Portland, Oregon, United States of America Citation: Ransom DG, Bahary N, Niss K, Traver D, Burns C, et al. (2004) The zebrafish moonshine gene encodes transcriptional intermediary factor 1γ, an essential regulator of hematopoiesis. PLoS Biol 2(8): e237. Abbreviations AFLPamplified fragment length polymorphism ENUethyl-nitrosourea ESTexpressed sequence tag GFPgreen fluorescent protein hpfhours postfertilization KRABKrüppel-associated box mon moonshine; PAC PMLpromyelocytic leukemia gene product RBCsred blood cells scl stem cell leukemia; SSCP TIFtranscriptional intermediary factor TUTübingen background ==== Refs References Abrink M Ortiz JA Mark C Sanchez C Looman C Conserved interaction between distinct Kruppel-associated box domains and the transcriptional intermediary factor 1 beta Proc Natl Acad Sci U S A 2001 98 1422 1426 11171966 Al Adhami MA Kunz YW Ontogenesis of haematopoietic sites in Brachydanio rerio Dev Growth Differ 1977 19 171 179 Barbazuk WB Korf I Kadavi C Heyen J Tate S The syntenic relationship of the zebrafish and human genomes Genome Res 2000 10 1351 1358 10984453 Bennett CM Kanki JP Rhodes J Liu TX Paw BH Myelopoiesis in the zebrafish, Danio rerio Blood 2001 98 643 651 11468162 Best JL Ganiatsas S Agarwal S Changou A Salomoni P SUMO-1 protease-1 regulates gene transcription through PML Mol Cell 2002 10 843 855 12419228 Brownlie A Donovan A Pratt SJ Paw BH Oates AC Positional cloning of the zebrafish sauternes gene: A model for congenital sideroblastic anaemia Nat Genet 1998 20 244 250 9806542 Cammas F Mark M Dolle P Dierich A Chambon P Mice lacking the transcriptional corepressor TIF1beta are defective in early postimplantation development Development 2000 127 2955 2963 10851139 Cammas F Oulad-Abdelghani M Vonesch JL Huss-Garcia Y Chambon P Cell differentiation induces TIF1beta association with centromeric heterochromatin via an HP1 interaction J Cell Sci 2002 115 3439 3448 12154074 Detrich HW Kieran MW Chan FY Barone LM Yee K Intraembryonic hematopoietic cell migration during vertebrate development Proc Natl Acad Sci U S A 1995 92 10713 10717 7479870 Friedman JR Fredericks WJ Jensen DE Speicher DW Huang XP KAP-1, a novel corepressor for the highly conserved KRAB repression domain Genes Dev 1996 10 2067 2078 8769649 Fujiwara Y Browne CP Cunniff K Goff SC Orkin SH Arrested development of embryonic red cell precursors in mouse embryos lacking transcription factor GATA-1 Proc Natl Acad Sci U S A 1996 93 12355 12358 8901585 Galloway JL Zon LI Ontogeny of hematopoiesis: Examining the emergence of hematopoietic cells in the vertebrate embryo Curr Top Dev Biol 2003 53 139 158 12510667 Kim SS Chen YM O'Leary E Witzgall R Vidal M A novel member of the RING finger family, KRIP-1, associates with the KRAB-A transcriptional repressor domain of zinc finger proteins Proc Natl Acad Sci U S A 1996 93 15299 15304 8986806 Kingsley PD McGrath KE Maltby KM Koniski AD Ramchandran R Subtractive hybridization reveals tissue-specific expression of ahnak during embryonic development Dev Growth Differ 2001 43 133 143 11284963 Knapik EW Goodman A Ekker M Chevrette M Delgado J A microsatellite genetic linkage map for zebrafish (Danio rerio) Nat Genet 1998 18 338 343 9537415 Le Douarin B Zechel C Garnier JM Lutz Y Tora L The N-terminal part of TIF1, a putative mediator of the ligand-dependent activation function (AF-2) of nuclear receptors, is fused to B-raf in the oncogenic protein T18 EMBO J 1995 14 2020 2033 7744009 Liao EC Trede NS Ransom D Zapata A Kieran M Non-cell autonomous requirement for the bloodless gene in primitive hematopoiesis of zebrafish Development 2002 129 649 659 11830566 Liao W Bisgrove BW Sawyer H Hug B Bell B The zebrafish gene cloche acts upstream of a flk-1 homologue to regulate endothelial cell differentiation Development 1997 124 381 389 9053314 Long Q Meng A Wang H Jessen JR Farrell MJ GATA-1 expression pattern can be recapitulated in living transgenic zebrafish using GFP reporter gene Development 1997 124 4105 4111 9374406 Lyons SE Lawson ND Lei L Bennett PE Weinstein BM A nonsense mutation in zebrafish gata1 causes the bloodless phenotype in vlad tepes Proc Natl Acad Sci U S A 2002 99 5454 5459 11960002 Niederreither K Remboutsika E Gansmuller A Losson R Dolle P Expression of the transcriptional intermediary factor TIF1alpha during mouse development and in the reproductive organs Mech Dev 1999 88 111 117 10525195 Orkin SH Zon LI Hematopoiesis and stem cells: Plasticity versus developmental heterogeneity Nat Immunol 2002 3 323 328 11919568 Palis J Yoder MC Yolk-sac hematopoiesis: The first blood cells of mouse and man Exp Hematol 2001 29 927 936 11495698 Peng H Feldman I Rauscher FJ Hetero-oligomerization among the TIF family of RBCC/TRIM domain-containing nuclear cofactors: A potential mechanism for regulating the switch between coactivation and corepression J Mol Biol 2002 320 629 644 12096914 Ransom DG Zon LI Mapping zebrafish mutations by AFLP Methods Cell Biol 1999 60 195 211 9891339 Ransom DG Haffter P Odenthal J Brownlie A Vogelsang E Characterization of zebrafish mutants with defects in embryonic hematopoiesis Development 1996 123 311 319 9007251 Remboutsika E Yamamoto K Harbers M Schmutz M The bromodomain mediates transcriptional intermediary factor 1alpha-nucleosome interactions J Biol Chem 2002 277 50318 50325 12384511 Reymond A Meroni G Fantozzi A Merla G Cairo S The tripartite motif family identifies cell compartments EMBO J 2001 20 2140 2151 11331580 Thisse C Zon LI Organogenesis—heart and blood formation from the zebrafish point of view Science 2002 295 457 462 11799232 Thompson MA Ransom DG Pratt SJ MacLennan H Kieran MW The cloche and spadetail genes differentially affect hematopoiesis and vasculogenesis Dev Biol 1998 197 248 269 9630750 Traver D Paw BH Poss KD Penberthy WT Lin S Transplantation and in vivo imaging of multilineage engraftment in zebrafish bloodless mutants Nat Immunol 2003 4 1238 1246 14608381 Urrutia R KRAB-containing zinc-finger repressor proteins Genome Biol 2003 4 231 14519192 Venturini L You J Stadler M Galien R Lallemand V TIF1gamma, a novel member of the transcriptional intermediary factor 1 family Oncogene 1999 18 1209 1217 10022127 Weinstein BM Schier AF Abdelilah S Malicki J Solnica-Krezel L Hematopoietic mutations in the zebrafish Development 1996 123 303 309 9007250 Weiss MJ Yu C Orkin SH Erythroid-cell-specific properties of transcription factor GATA-1 revealed by phenotypic rescue of a gene-targeted cell line Mol Cell Biol 1997 17 1642 1651 9032291 Westerfield M The zebrafish book, 4th ed 1998 Eugene (Oregon) University of Oregon Press 50 Zhong S Delva L Rachez C Cenciarelli C Gandini D A RA-dependent, tumour-growth suppressive transcription complex is the target of the PML-RARalpha and T18 oncoproteins Nat Genet 1999 23 287 295 10610177 Zhong S Muller S Ronchetti S Freemont PS Dejean A Role of SUMO-1-modified PML in nuclear body formation Blood 2000a 95 2748 2752 10779416 Zhong S Salomoni P Pandolfi PP The transcriptional role of PML and the nuclear body Nat Cell Biol 2000b 2 E85 E90 10806494

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020240Research ArticleCancer BiologyCell BiologyDevelopmentMolecular Biology/Structural BiologyHomo (Human)The Telomeric Protein TRF2 Binds the ATM Kinase and Can Inhibit the ATM-Dependent DNA Damage Response TRF2 Inhibits ATMKarlseder Jan 1 ¤Hoke Kristina 1 Mirzoeva Olga K 3 Bakkenist Christopher 2 Kastan Michael B 2 Petrini John H. J 3 de Lange Titia delange@mail.rockefeller. edu 1 1Laboratory for Cell Biology and Genetics, Rockefeller University, New YorkUnited States of America2Department of Hematology and Oncology, St. Jude Children's Research HospitalMemphis, Tennessee, United States of America3Memorial Sloan–Kettering Cancer Center, New YorkNew YorkUnited States of America8 2004 17 8 2004 17 8 2004 2 8 e24029 3 2004 27 5 2004 Copyright: © 2004 Karlseder et al.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. Inhibition of the DNA Damage Pathway by a Telomere-Binding Protein The telomeric protein TRF2 is required to prevent mammalian telomeres from activating DNA damage checkpoints. Here we show that overexpression of TRF2 affects the response of the ATM kinase to DNA damage. Overexpression of TRF2 abrogated the cell cycle arrest after ionizing radiation and diminished several other readouts of the DNA damage response, including phosphorylation of Nbs1, induction of p53, and upregulation of p53 targets. TRF2 inhibited autophosphorylation of ATM on S1981, an early step in the activation of this kinase. A region of ATM containing S1981 was found to directly interact with TRF2 in vitro, and ATM immunoprecipitates contained TRF2. We propose that TRF2 has the ability to inhibit ATM activation at telomeres. Because TRF2 is abundant at chromosome ends but not elsewhere in the nucleus, this mechanism of checkpoint control could specifically block a DNA damage response at telomeres without affecting the surveillance of chromosome internal damage. The human telomere-associated protein TRF2 inhibits ATM kinase, suggesting a mechanism by which the telomeric protein complex prevents the activation of this DNA damage response transducer ==== Body Introduction Telomeres prevent the recognition of natural chromosome ends as double-stranded breaks (DSBs). When telomeres become dysfunctional due to shortening or loss of protective factors, chromosome ends activate a DNA damage response mediated (in part) by the ATM kinase (Karlseder et al. 1999; Takai et al. 2003). A major challenge in telomere biology is to define the mechanism by which functional telomeres prevent these events. Here we show that the human telomere-associated protein TRF2 is an inhibitor of the ATM kinase, suggesting a mechanism by which the telomeric protein complex prevents the activation of this DNA damage response transducer. TRF2 is a small multimeric protein that binds to duplex telomeric (TTAGGG) repeats and recruits hRap1, ERCC1/XPF, WRN, and the Mre11/Rad50/Nbs1 complex to chromosome ends (Li et al. 2000; Zhu et al. 2000, Zhu et al. 2000 2003; Opresko et al. 2002; Machwe et al. 2004). TRF2 can be inhibited with a dominant-negative allele, TRF2ΔBΔM, which removes the endogenous TRF2 complex from telomeres (van Steensel et al. 1998). Upon expression of TRF2ΔBΔM, telomeres become uncapped and experience a series of deleterious events, including association with DNA damage response factors such as 53BP1, cleavage of the telomeric 3′ overhang by ERCC1/XPF, and telomere–telomere ligation by DNA ligase IV (van Steensel et al. 1998; de Lange 2002; Smogorzewska et al. 2002; Takai et al. 2003; Zhu et al. 2003). The DNA damage response to uncapped telomeres induces phosphorylation of DNA damage response proteins, including H2AX, SMC1, Rad17, CHK1, and CHK2, and upregulation of p53, p21, and p16, resulting in a G1 arrest (Karlseder et al. 1999; Smogorzewska and de Lange 2002; d'Adda di Fagagna et al. 2003). Primary human cells with telomere damage undergo apoptosis or senescence (Karlseder et al. 1999; Smogorzewska and de Lange 2002). An important transducer of the DNA damage signal is the ATM kinase (reviewed in Shiloh 2003). ATM activation requires autophosphorylation on S1981 and concomitant dissociation into monomers, the presumed active form of the kinase (Bakkenist and Kastan 2003). DSBs and other genome stress lead to a rapid conversion of the ATM pool into active S1981–P monomers, which can phosphorylate regulators of the G1/S, intra-S, and G2/M cell cycle transitions (Bakkenist and Kastan 2003). Activation of ATM also takes place in response to telomere damage. When telomeres become uncapped due to inhibition of TRF2, S1981-phosphorylated ATM associates with telomeres (Takai et al. 2003). Furthermore, ATM targets become phosphorylated in aging cells with shortened telomeres (d'Adda di Fagagna et al. 2003). Genetic evidence for a role of ATM in the telomere damage pathway is provided by the diminished ability of ataxia telangiectasia (A-T) cells to mount a DNA damage response after telomere uncapping (Karlseder et al. 1999; Takai et al. 2003). However, several lines of evidence suggest that a second PIKK (phosphatidylinositol 3-kinase-like kinase), such as ATR or DNA-PKcs, can transduce the telomere damage signal in the absence of ATM (Takai et al. 2003; Wong et al. 2003). One proposed mechanism of telomere protection is based on the ciliate telomere proteins, which envelop the single-stranded telomere terminus (Horvath et al. 1998). Such a protein cap, if sufficiently stable, could simply hide chromosome ends from the DNA damage surveillance machinery. Both budding and fission yeast also contain protective single-stranded telomere-binding proteins, but it is not known whether these proteins function similarly by forming a physical cap over the telomere terminus (Garvik et al. 1995; Baumann and Cech 2001). TRF2 must represent a different mechanism for telomere protection since it only binds to the duplex part of the telomere. TRF2 has been proposed to promote the formation of t-loops (Griffith et al. 1999; Stansel et al. 2001). In the t-loop configuration, the 3′ overhang of TTAGGG repeats is strand-invaded into the duplex part of the telomere. Although this could be an effective way to protect chromosome ends from nucleases and ligases, t-loops have several structural features resembling DNA lesions, including single strand to double strand transitions, 3′ and 5′ ends, and single-stranded DNA. Therefore, human telomeres may need additional mechanisms to circumvent checkpoint activation. The results presented here argue for a model in which TRF2 directly blocks activation of the ATM kinase. Results TRF2 was overexpressed in IMR90 primary fibroblasts using a retroviral vector. Under these conditions, TRF2 saturates its telomeric binding sites and is present in the nucleoplasm. While control IMR90 cells showed the expected reduction in mitotic index after ionizing radiation (IR), TRF2 overexpression partially abrogated this checkpoint response, increasing the percentage of cells entering mitosis from 0.3% to 8% (Figure 1). The inappropriate entry into mitosis is indicative of a failure of the cell cycle checkpoints. Since cell cycle arrest after IR largely depends on ATM (reviewed in Shiloh 2003), we asked whether TRF2 was acting on this kinase. Caffeine, an inhibitor of ATM and the related kinase ATR, suppressed IR-induced arrest to a similar extent as TRF2 (Figure 1). Furthermore, caffeine had no additional effect on the ability of TRF2-overexpressing cells to bypass the DSB checkpoint, suggesting that TRF2 and caffeine target the same step in the response pathway. Figure 1 TRF2 Inhibits the IR-Induced Cell Cycle Arrest (A) Retrovirally infected IMR90 cells were treated with 4 Gy IR (left and right) or treated with 4 Gy IR and exposed to caffeine (10 mM) directly after irradiation (middle). After 16 h, during which the cells were incubated in 1 μg/ml colcemide, the DNA was stained with DAPI and mitotic cells were identified by immunofluorescence with an antibody to phosphorylated histone H3. (B) Quantification of bypass of IR-induced cell cycle arrest. The mean percentage of phosphorylated histone H3-positive cells and SDs from three experiments are given. The low maximal incidence of phosphorylated H3-positive nuclei (approximately 18%) is due to loss of mitotic cells during processing; loss of mitotic cells occurred at the same level in control and experimental samples. We then asked whether TRF2 overexpression inhibited other ATM-dependent readouts of the DNA damage response. ATM phosphorylates and stabilizes p53 in response to DNA damage (reviewed in Kastan and Lim 2000). Quantitative immunoblotting showed that cells overexpressing TRF2 had a diminished ability to induce p53 after irradiation (Figures 2A and 2B). Both the relative level of p53 protein and the induction of its downstream targets p21, Bax, and Hdm2 were dampened. By contrast, the p16/Rb pathway was not affected by TRF2 (Figure 2A). We also examined the phosphorylation of Nbs1 on S343, a target of ATM (Gatei et al. 2000; Lim et al. 2000; Wu et al. 2000; Zhao et al. 2000). Phosphorylation of this residue causes a change in electrophoretic mobility shift and can also be detected using an antibody specific for the phosphorylated form of Nbs1. Extracts from irradiated control cells showed the previously reported retardation of Nbs1 and its reactivity with the S343–P-specific Nbs1 antibody (Figure 2C). Both alterations could be reversed by phosphatase treatment of the Nbs1 immunoprecipitations (IPs). In contrast, irradiation did not appear to induce phosphorylation of Nbs1 in cells overexpressing TRF2, indicating that TRF2 diminished the ATM-dependent phosphorylation of Nbs1 (Figure 2C). Figure 2 Effect of TRF2 on Downstream Readouts of the IR-Induced ATM Response (A) Retrovirally infected IMR90 cells were exposed to 5 Gy IR and harvested after 0, 12, 24, and 36 h. Levels of p53, Bax, p21, Hdm2, p16, pRB, and γ-tubulin (loading control) were detected by immunoblotting of equal cell number equivalents. (B) Amount of p53 protein at the indicated timepoints (hours) was determined by densitometry of p53 immunoblots such as shown in (A). Amounts were normalized to the vector control at 0 h. Mean values from three experiments and standard deviations are shown. (C) Retrovirally infected IMR90 cells were exposed to 20 Gy IR and harvested after 45 min. Nbs1 was immunoprecipitated and subsequently detected by immunoblotting using a general Nbs1 antibody and a phosphospecific Nbs1 S343 antibody. IPs were treated with λ-phosphatase where indicated. Because TRF2 overexpression blunted several cellular responses that depend (in part) on the ATM kinase, we determined TRF2's effect on the activation of ATM itself. Phosphorylation of ATM on S1981, an early and essential step in the activation of this kinase, can be detected rapidly after IR, even when a low level of DNA damage is induced (Bakkenist and Kastan 2003). To test whether TRF2 affected the autophosphorylation of ATM, the two proteins were expressed in 293T cells and ATM was activated with low doses of IR. TRF2 inhibited the activation of ATM as monitored by immunoblotting with an antibody specific for ATM S1981–P (Figure 3A). The relative level of ATM S1981–P (normalized to total ATM protein) at 0.3 Gy was 49% of the vector control value (p = 0.002, Student's t test; n = 7). The TRF2 paralog TRF1, which also binds the duplex telomeric repeats, did not have a significant effect on ATM activation, demonstrating that the effect on ATM is specific to TRF2 (Figure 3A). Overexpression of TRF2 also diminished the IR-induced ATM autophosphorylation of endogenous ATM in IMR90 fibroblasts to 55% of vector control value at 0.3 Gy and 60% of vector control value at 0.6 Gy (Figure 3B). Figure 3 Effect of TRF2 on IR-Induced ATM Phosphorylation (A) Overexpression of TRF2 inhibits IR-induced phosphorylation of transfected ATM in 293T cells. 293T cells co-transfected with ATM and either TRF2, TRF1, or vector were treated with the indicated doses of IR. After a 30-min recovery, cells were harvested and immunoblot analysis was performed on whole-cell lysates. (B) Overexpression of TRF2 inhibits IR-induced phosphorylation of endogenous ATM in primary fibroblasts. IMR90 primary fibroblasts infected with a retroviral construct expressing TRF2 or an empty virus were treated with the indicated doses of IR. After a 1 h recovery, cells were harvested and ATM was immunoprecipitated from whole-cell lysates. Immunoblot analysis was performed on immunoprecipitated ATM. In order to understand the mechanism by which TRF2 inhibited ATM, we determined whether they interacted in vivo. IPs of the ATM kinase from primary human IMR90 fibroblasts resulted in recovery of a small fraction (approximately 1%) of endogenous TRF2 (Figure 4A). This association was accentuated when TRF2 was overexpressed from a retroviral vector. TRF2 was not recovered in anti-ATM immunoprecipitates from A-T cells even when TRF2 was overexpressed (Figure 4A), demonstrating that the recovery of TRF2 is dependent on the presence of functional ATM. The co-IP of TRF2 with ATM from IMR90 cells was resistant to the addition of ethidium bromide (data not shown), arguing that DNA tethering is not responsible for the association. A control IP with antibodies to the CycD1/Cdk4/Cdk6 kinase complex did not precipitate TRF2, and an irrelevant nuclear protein (Nova1), overexpressed in parallel in IMR90 cells, was not recovered in the ATM IP (Figure 4A). The association of TRF2 with ATM was not dependent on the presence of DNA damage, since neither IR nor UV treatment enhanced the recovery of TRF2 in ATM IPs (data not shown). Figure 4 TRF2 Interacts with the ATM Kinase In Vivo and In Vitro and TRF2 Does Not Localize to IRIF (A) Co-IP of TRF2 with ATM. Protein extracts from IMR90 cells and A-T cells (AG02496) infected with an empty virus or a TRF2-overexpressing virus were incubated with anti-ATM or anti-Cyclin D1 antibodies as indicated, and TRF2 was detected in the IP pellets by immunoblotting. The right panel represents IPs with anti-ATM antibodies from IMR90 cells infected with a retrovirus overexpressing Nova1 or the empty vector and detection of Nova1 by immunoblotting. For each extract 1% of the IP input (input) was processed for immunoblotting in parallel. (B) Bacterially expressed ATM–GST fusion proteins were purified on glutathione agarose beads and visualized by Western blotting with anti-GST antibody (Upstate Biotechnology [Lake Placid, New York, United States] #06–332) (top). Unfused GST was run on a separate gel because of its low molecular weight. Equal amounts of fusion proteins and GST alone were incubated with purified baculoviral TRF2 (middle) or TRF1 (bottom), bound to glutathione beads, spun down, washed, and bound proteins were processed for immunoblotting with an anti-TRF1 or anti-TRF2 serum. (C) TRF2 does not localize to IRIFS. IMR90 primary fibroblasts infected with a retroviral construct expressing TRF2 or an empty virus were treated with 5 Gy IR. After a 90 min recovery, cells were fixed and processed for immunofluorescence with or without Triton X-100 extraction before fixation. Arrowheads denote foci of TRF2 signal previously demonstrated to represent telomeres. When overexpressed, some TRF2 is localized to nucleolus. The nature of the association of TRF2 with ATM was explored further using in vitro pulldown experiments. GST-tagged fragments of ATM were tested for their ability to bind purified TRF2 protein expressed in a baculovirus system. In parallel, we used baculovirus-derived TRF1, which was previously shown to interact with ATM by co-IP (Kishi et al. 2001). TRF2 bound to two overlapping fragments of ATM spanning amino acids 1439 to 2138 (Figure 4B). This region contains the FAT domain and S1981, the critical target of autophosphorylation (Bakkenist and Kastan 2003). TRF1 bound a different region of ATM (Figure 4B), demonstrating the specificity of the observed interactions. Blunting of the DNA damage response was observed when TRF2 was overexpressed throughout the nucleus. Because TRF2 is chiefly present at telomeres, the simplest interpretation is that the observed activity reflected a telomeric function. However, we also considered the possibility that TRF2 may have a heretofore clandestine role in the general DNA damage response. If this were true, TRF2 might be expected to localize to IR-induced foci (IRIF), where it would be in a position to modulate ATM. Previous data had shown that the endogenous TRF2 does not relocate from telomeres to IRIF (Zhu et al. 2000). Similarly, immunofluorescence analysis showed that overexpressed TRF2 did not form IRIF (Figure 4C): the pattern of TRF2 localization was unchanged by IR, and there was no detectable colocalization with the known IRIF component 53BP1 (Schultz et al. 2000). This was also the case when TRF2 localization was examined in cells from which the nucleoplasmic proteins were extracted with a mild detergent (Figure 4C). Thus, the inhibitory effect of TRF2 on ATM signaling does not reflect association of TRF2 with sites of DNA damage. Instead, we propose that the inhibition of ATM by TRF2 is an innate property of the protein, important at its natural location: telomeres. However, we cannot exclude the transient presence of TRF2 at DNA lesions and/or a role for TRF2 in the general DNA damage response. Discussion Natural chromosome ends require mechanisms to prevent the activation of the DNA damage response. Inhibition of the ATM kinase at human telomeres is particularly important since the telomeric complex contains the Mre11 complex, one of the DNA damage sensors of the ATM pathway (Carson et al. 2003; Petrini and Stracker 2003; Uziel et al. 2003). The telomeric protein TRF2 appears to play a central role in preventing telomeres from activating ATM. Removal of TRF2 from telomeres results in the localization of the active, phosphorylated form of ATM to unprotected chromosome ends (Takai et al. 2003) and induces ATM-dependent apoptosis (Karlseder et al. 1999). The data reported here are consistent with the hypothesis that TRF2 protects telomeres through a direct interaction with ATM that blocks its activation. As a result, TRF2 abrogates the downstream outcomes of the ATM-dependent DNA damage response, including phosphorylation of various ATM targets and cell cycle arrest. We feel that the interaction of TRF2 with ATM is likely to be relevant to the mechanism by which TRF2 blocks ATM signaling. TRF2 binds ATM in a region surrounding S1981, which is functionally linked to the oligomerization state of ATM. Phosphorylation on S1981 occurs concomitant with the dissociation of ATM dimers (or oligomers), forming the monomeric, active form of the kinase (Bakkenist and Kastan 2003). TRF2 is also an oligomer of four to eight subunits, which are held together by the TRFH dimerization domain as well as other, yet to be defined, protein interactions (Broccoli et al. 1997; Fairall et al. 2001; Stansel et al. 2001). Owing to its oligomeric nature, TRF2 could potentially cross-link ATM monomers and thus hold the kinase in its inactive dimeric (or oligomeric) state. In this manner, TRF2 could abrogate the ATM pathway since it would block amplification of the ATM signal at an early step. In agreement with this idea, the in vitro GST pulldown experiments showed that TRF2 can interact with ATM when it is not phosphorylated on S1981. Because mutations in the TRF2 dimerization domain destabilize the protein, it has not been possible to test the contribution of TRF2 oligomerization on ATM repression directly. Alternatively, the interaction of TRF2 with the region surrounding S1981 may prevent ATM autophosphorylation or TRF2 binding could block a presumed interaction between ATM and a DNA damage sensor, such as the Mre11 complex. It is unlikely that TRF2 acts as an ATM target mimetic that titrates out genuine ATM targets since TRF2 is not a target of the ATM kinase (R. Drissi, M. B. Kastan, and J. Dome, unpublished data). Furthermore, TRF2 does not block ATM kinase activity in an in vitro assay (S. Kozlov, J. Karlseder, and M. F. Lavin, unpublished data). These findings are consistent with TRF2 acting at one of the earlier steps in the activation of the ATM kinase, including the interplay between ATM and DNA damage sensors, ATM autophosphorylation, or dissociation of ATM dimers. In this study we have expressed TRF2 at high levels throughout the nucleus, whereas endogenous TRF2 is localized primarily to telomeres (van Steensel et al. 1998). Our estimates suggest that TRF2 is extremely abundant at telomeres. Human cells contain on the order of 1 million copies of TRF2 (X.-D. Zhu and T. de Lange, unpublished data), sufficient to position thousands of TRF2 molecules at each chromosome end. This number is consistent with the presence of thousands of TRF2-binding sites per telomere and the oligomerization potential of the protein. Thus, for every ATM kinase that could be activated at a chromosome end, there is a vast molar excess of its potential inhibitor, TRF2. Since TRF2 is specifically lodged at telomeres and remains there when DNA damage is induced, it is unlikely to interfere with activation of the ATM kinase at sites of DNA damage elsewhere in the genome. Hence, TRF2 could act as a telomere-specific inhibitor of ATM. Previous studies have shown that overexpression of TRF2 can protect critically short telomeres generated by replicative aging (Karlseder et al. 2002). TRF2 reduced the incidence of end-to-end chromosome fusions in this setting and also delayed the onset of senescence. These findings suggested that senescence is induced by an altered telomere state, in which the telomere has become so short that the amount of TRF2 it can recruit is insufficient for the protection of the chromosome end. When TRF2 is overexpressed, this deficiency in TRF2 recruitment may be overcome. One possibility is that the altered state of critically short telomeres represents a situation in which telomeres have a diminished ability to form t-loops. The current findings raise the possibility that the altered state may also include a situation in which the telomere contains insufficient TRF2 to repress ATM. However, the ability of TRF2 to delay senescence was also observed in A-T cells (Karlseder et al. 2002), indicating that ATM repression is not the only pathway by which increased TRF2 loading can protect critically short telomeres. As TRF2 can bind ATM, it has the inherent ability to recruit this protein to telomeres. ATM has not been observed at undamaged telomeres, but its abundance may be too low for detection. The idea that ATM could be recruited to telomeres by TRF2 is interesting considering that ATM-like kinases are necessary for telomere maintenance in Saccharomyces cerevisiae (Craven et al. 2002) and Schizosaccharomyces pombe (Matsuura et al. 1999). It is not excluded that human telomere maintenance similarly requires ATM. TRF2 could function to recruit ATM in an inactive form, perhaps allowing for highly regulated activation of ATM at appropriate times. Such regulation of DNA damage signaling and repair pathways at telomeres has been proposed previously in the context of the nonhomologous end-joining pathway and the role of the nucleotide excision repair endonuclease ERCC1/XPF (Smogorzewska et al. 2002; Zhu et al. 2003). In both cases, proteins with the potential to have detrimental effects on telomeres appear to be regulated such that their activities can be employed for telomere function. Materials and Methods Cell culture and IR treatment IMR90 primary lung fibroblasts (ATCC, Manassas, Virginia, United States) and AG02496 and AG04405 primary A-T fibroblasts (Coriell Cell Repository, Camden, New Jersey, United States; PD 12 and PD 15) were grown and infected with retroviruses as described elsewhere (Karlseder et al. 2002). For γ-irradiation, 3 105 cells were seeded in 5-cm culture dishes and exposed to a Ce137 source. Where indicated, the medium was replaced with medium containing 10 mM caffeine (Sigma, St. Louis, Missouri, United States) and 1 μg/ml colcemide (Sigma). Indirect immunofluorescence was performed as described (Smogorzewska et al. 2000; Takai et al. 2003). Co-transfection assay for S1981–P inhibition One day prior to transfection, approximately 5 106 293T cells were plated in 10-cm dishes. Cells were transfected with 1 μg of FLAG–ATM DNA (Canman et al. 1998) and 9 μg of N-terminally Myc-tagged TRF2 (Karlseder et al. 2002) or TRF1 in a pLPC vector backbone (gift of S. Lowe, Cold Spring Harbor Laboratory) or vector alone using CaPO4 coprecipitation. Two days after transfection, cells were harvested in media and divided into three equal fractions, which were exposed to 0, 0.3, or 0.6 Gy IR. Cells were allowed to recover for 30 min, washed with PBS, and resuspended in 250 μl of lysis buffer (50 mM Tris [pH 7.4], 1% Triton X-100, 0.1% SDS, 150 mM NaCl, 1 mM EDTA, 1 mM DTT, 1 mM PMSF, with a complete mini-protease inhibitor tablet [Roche, Basel, Switzerland] per 10 ml). The NaCl concentration was raised to 400 mM, and the lysate was incubated on ice for 5 min. The NaCl concentration was reduced to 200 mM, cell debris was removed by centrifugation, and an equal volume of Laemmli buffer was added to the lysate. Immunoblotting For ATM immunoblots in the ATM S1981–P suppression assays: 40 μl of 293T cell lysate or ATM immunoprecipitated from approximately 5 106 IMR90 fibroblasts were run on 7.5% precast polyacrylamide Bio-Rad (Hercules, California, UnitedStates) Ready Gels. PVDF ImmobilonTM Transfer Membrane (Millipore, Billerica, Massachusetts, United States) was prepared for protein transfer according to the manufacturer's instructions and the gel was transferred for 2 h at 90 V. Membranes were preincubated in 10% milk, 0.1% Tween-20 in PBS for 30 min at room temperature and subsequently incubated with primary antibodies: polyclonal rabbit ATM S1981–P (Bakkenist and Kastan 2003) and mouse monoclonal ATM antibody MAT3 (gift from Y. Shiloh) diluted in 0.1% milk, 0.1% Tween-20 in PBS overnight at 4 °C followed by three 10 min washes. Membranes were incubated for 45 min with HRP-conjugated secondary antibodies, washed, and developed using the ECL system (Amersham, Little Chalfort, United Kingdom). Immunoblots of Myc-tagged proteins (using Ab-1; Oncogene Research, Cambridge, Massachusetts, United States) in the ATM S1981–P suppression assays were performed as above, except that nitrocellulose (Schleicher and Schuell, Keene, New Hampshire, United States) filters were used. For all other immunoblots, cells were trypsinized, washed once with PBS, and subsequently lysed in Laemmli buffer at 104 cells/μl. Lysates (10 μl) were separated on SDS-polyacrylamide gels (29:1 acrylamide: bisacrylamide, 8% for p53, TRF2, and γ-tubulin, 6% for pRB and Hdm2, 12% for Bax, p21, and p16) and transferred onto nitrocellulose membranes (Schleicher and Schuell) for 60 min at 90 V (Bio-Rad Mini-Protean II Cell). Membranes were preincubated in 10% nonfat dry milk, 0.1% Tween-20 in PBS for 30 min and subsequently incubated with primary antibodies: p53 D01 (Santa Cruz Biotechnology, Santa Cruz, California, United States); TRF2 serum 647 (Zhu et al. 2000); pRB #554136 (PharMingen, Uppsalla, Sweden); Hdm2 #3F3 (gift from, A. Levine); Bax #sc-7480 (Santa Cruz Biotechnology); p21 sc-7480 (Santa Cruz Biotechnology); p16 #15126E (PharMingen); γ-tubulin GTU88 (Sigma); Nova1 (Luque et al. 1991) in 5% dry milk, 0.1% Tween-20 in PBS overnight. Secondary antibody incubation and ECL were performed as described above. To quantify signals, band intensities were determined using an AlphaImagerTM 2200 using the SpotDenso function of AlphaEaseFCTM Software Version 3.1.2 (Witec, Littau, Switzerland). IP For co-IP of ATM and TRF2, proteins were extracted from subconfluent cells by incubating trypsinized cells (approximately 107 cells/0.1 ml buffer) in 20 mM HEPES (pH 7.9), 0.42 M KCl, 25% glycerol, 0.1 mM EDTA, 5 mM MgCl2, 0.2% NP40, 1 mM DTT, 0.5 mM PMSF, 1 μg/ml leupeptine, 1 μg/ml aprotinin, 10 μg/ml pepstatin on ice for 30 min. Debris was removed by centrifugation (14,000 rpm, 4 °C, 10 min). Protein concentration in the supernatant was determined using the Bradford assay and 400 μg of protein was diluted to 150 mM KCl and incubated for 20 min with 100 μl of protein G–Sepharose beads (Amersham), blocked with 1% fetal bovine serum in PBS. The beads were collected at 14,000 rpm for 1 min and the supernatant was incubated with 5 μg of anti-ATM antibody (AB3, Oncogene Research) or anti-Cyclin D1 antibody (#sc-6281, Santa Cruz Biotechnology) for 1 h at 4 °C on a nutator. Protein G–Sepharose beads (30 μl) were added, and the mixture was incubated 1 h at 4 °C on a nutator. The beads were collected at 4,000 rpm at 4 °C, washed three times with wash buffer (150 mM NaCl, 1% NP40, 50 mM Tris [pH 8.0] with protease inhibitors as described above) by vortexing the suspension for 10 s. The beads were resuspended in Laemmli buffer and boiled 5 min, and proteins were separated by polyacrylamide gel electrophoresis. For IP of endogenous ATM from IMR90 fibroblasts for the phosphorylation assay, cells were resuspended in lysis buffer (50 mM Hepes [pH 7.5], 150 mM NaCl, 50 mM NaF, 1% Tween-20, 0.2% NP40, 1mM PMSF, with 1 complete mini-protease inhibitor tablet [Roche, Basel, Switzerland] ) and centrifuged at 13,000 rpm for 10 min. 400 μl of lysate was incubated with 30 μl of blocked protein G beads and 100 μl of D16.11 monoclonal supernatant (Alligood et al. 2000) for 1.5 h. Beads were washed once in lysis buffer and twice in RIPA buffer and resuspended in 60 μl of Laemmli buffer. Pulldown assays GST–ATM fusion plasmids (Khanna et al. 1998) were transformed into BL-21 cells. A 10-ml overnight culture was used to inoculate 500 ml of LB-Amp (50 μg/ml) and at OD600, 0.5–0.7, 0.3 mM IPTG (final) was added. After 3 h at 30 °C, cells were harvested, resuspended in 8 ml of lysis buffer (50 mM Tris [pH 7.9], 100 mM KCl, 1% Triton X-100, 2 mM DTT, 0.1 mM PMSF, 1 complete protease inhibitor tablet [Roche]) and sonicated three times for 30 s on ice. The lysate was cleared by centrifugation at 50,000 g at 4 °C and incubated with 600 μl of equilibrated glutathione beads for 2 h at 4 °C. The beads were washed three times for 10 min each (washes 1 and 3: PBS, 1% Triton X-100, 2 mM DTT, 0.1 mM PMSF, 1 mM benzamidine, 1 complete protease inhibitor tablet [Roche]; wash 2: 300 mM NaCl, 50 mM Tris [pH 7.9], 2 mM DTT, 0.1 mM PMSF, 1 mM benzamidine, 1 complete protease inhibitor tablet [Roche]) and a fourth time in wash 4 (50 mM Tris [pH 7.9], 100 mM KCl, 10% glycerol, 2 mM DTT, 0.1 mM PMSF). Fusion proteins were eluted in 500 μl of wash 4 containing 15 mM glutathione (reduced form). Two subsequent elutions were collected. Five micrograms of GST fusion proteins or GST alone were incubated with 2 μg of baculoviral TRF1 or TRF2 in binding buffer (150 mM NaCl, 100 mM KCl, 50 mM Tris [pH 8.0], 1% NP40, 0.1% SDS, 100 g/ml BSA) at 4 °C for 1 h. Glutathione beads (20 μl) were added and incubated for 1 h at 4 °C. Beads were collected by centrifugation at 5,000 rpm at 4 °C and washed three times for 10 min each with binding buffer, and bound protein was eluted by boiling the samples in Laemmli buffer. GST fusion proteins, TRF1, and TRF2 were detected by immunoblotting. Cell cycle arrest assay Cells were seeded on microscope coverslips and irradiated with 4 Gy of γ-irradiation as described above. Cells were incubated in growth medium containing 1 μg/ml colcemid for 16 h. Cells were fixed, and phosphorylated histone H3 was detected by indirect immunofluorescence using a phosphospecific antibody (6G3 monoclonal; Cell Signaling Technology, Beverly, Massachusetts, United States). Cells in mitosis were counted and expressed as a percentage of total cell number. R. Darnell, Y. Shiloh, and M. Lavin are thanked for providing reagents. This work was funded by grants from the National Institutes of Health (NIH) to JHJP (GM59413 and GM56888), TdL (AG016642 and GM49046), and MK (CA71387 and CA21765) and by an Ellison Foundation Senior Scholar Award to TdL. JK was supported by fellowships from the Human Frontiers Science Program and the Charles H. Reversuson Foundation and by a grant from the L.Y. Mathers Charitable Foundation. KH was supported by NIH MSTP grant GM07739 to the Cornell/Rockefeller/Sloan–Kettering Tri-Institutional MD–PhD Program. Conflicts of interest. The authors have declared that no conflicts of interest exist. Author contributions. JK, KMH, and TdL conceived and designed the experiments. JK, KMH, and OM performed the experiments. JK, KMH, JHJP, and TdL analyzed the data. JK, KMH, CB, MBK, JHJP, and TdL contributed reagents/materials/analysis tools. JK, KMH, JHJP, and TdL wrote the paper. Academic Editor: Steve Elledge, Harvard Medical School ¤Current address: Regulatory Biology, The Salk Institute for Biological Studies, La Jolla, California, United States of America Citation: Karlseder J, Hoke K, Mirzoeva OK, Bakkenist C, Kastan MB, Petrini JHJ, de Lange T (2004) The telomeric protein TRF2 binds the ATM kinase and can inhibit the ATM-dependent DNA damage response. PLoS Biol 2(8): e240. Abbreviations A-Tataxia telangiectasia DSBdouble-stranded break IPimmunoprecipitation IRionizing radiation IRIFionizing radiation-induced foci ==== Refs References Alligood KJ Milla M Rhodes N Ellis B Kilpatrick KE Monoclonal antibodies generated against recombinant ATM support kinase activity Hybridoma 2000 19 317 321 11001404 Bakkenist CJ Kastan MB DNA damage activates ATM through intermolecular autophosphorylation and dimer dissociation Nature 2003 421 499 506 12556884 Baumann P Cech TR Pot1, the putative telomere end-binding protein in fission yeast and humans Science 2001 292 1171 1175 11349150 Broccoli D Smogorzewska A Chong L de Lange T Human telomeres contain two distinct Myb-related proteins, TRF1 and TRF2 Nat Genet 1997 17 231 235 9326950 Canman CE Lim DS Cimprich KA Taya Y Tamai K Activation of the ATM kinase by ionizing radiation and phosphorylation of p53 Science 1998 281 1677 1679 9733515 Carson CT Schwartz RA Stracker TH Lilley CE Lee DV The Mre11 complex is required for ATM activation and the G2/M checkpoint EMBO J 2003 22 6610 6620 14657032 Craven RJ Greenwell PW Dominska M Petes TD Regulation of genome stability by TEL1 and MEC1, yeast homologs of the mammalian ATM and ATR genes Genetics 2002 161 493 507 12072449 d'Adda di Fagagna F Reaper PM Clay-Farrace L Fiegler H Carr P A DNA damage checkpoint response in telomere-initiated senescence Nature 2003 426 194 198 14608368 de Lange T Protection of mammalian telomeres Oncogene 2002 21 532 540 11850778 Fairall L Chapman L Moss H de Lange T Rhodes D Structure of the TRFH dimerization domain of the human telomeric proteins TRF1 and TRF2 Mol Cell 2001 8 351 361 11545737 Garvik B Carson M Hartwell L Single-stranded DNA arising at telomeres in cdc13 mutants may constitute a specific signal for the RAD9 checkpoint Mol Cell Biol 1995 15 6128 6138 7565765 Gatei M Young D Cerosaletti KM Desai-Mehta A Spring K ATM-dependent phosphorylation of nibrin in response to radiation exposure Nat Genet 2000 25 115 119 10802669 Griffith JD Comeau L Rosenfield S Stansel RM Bianchi A Mammalian telomeres end in a large duplex loop Cell 1999 97 503 514 10338214 Horvath MP Schweiker VL Bevilacqua JM Ruggles JA Schultz SC Crystal structure of the Oxytricha nova telomere end binding protein complexed with single strand DNA Cell 1998 95 963 974 9875850 Karlseder J Broccoli D Dai Y Hardy S de Lange T p53- and ATM-dependent apoptosis induced by telomeres lacking TRF2 Science 1999 283 1321 1325 10037601 Karlseder J Smogorzewska A de Lange T Senescence induced by altered telomere state, not telomere loss Science 2002 295 2446 2449 11923537 Kastan MB Lim DS The many substrates and functions of ATM Nat Rev Mol Cell Biol 2000 1 179 186 11252893 Khanna KK Keating KE Kozlov S Scott S Gatei M ATM associates with and phosphorylates p53: Mapping the region of interaction Nat Genet 1998 20 398 400 9843217 Kishi S Zhou XZ Ziv Y Khoo C Hill DE Telomeric protein Pin2/TRF1 as an important ATM target in response to double strand DNA breaks J Biol Chem 2001 276 29282 29291 11375976 Li B Oestreich S de Lange T Identification of human Rap1: Implications for telomere evolution Cell 2000 101 471 483 10850490 Lim DS Kim ST Xu B Maser RS Lin J ATM phosphorylates p95/nbs1 in an S-phase checkpoint pathway Nature 2000 404 613 617 10766245 Luque FA Furneaux HM Ferziger R Rosenblum MK Wray SH Anti-Ri: An antibody associated with paraneoplastic opsoclonus and breast cancer Ann Neurol 1991 29 241 251 2042940 Machwe A Xiao L Orren DK TRF2 recruits the Werner syndrome (WRN) exonuclease for processing of telomeric DNA Oncogene 2004 23 149 156 14712220 Matsuura A Naito T Ishikawa F Genetic control of telomere integrity in Schizosaccharomyces pombe: Rad3(+) and tel1(+) are parts of two regulatory networks independent of the downstream protein kinases chk1(+) and cds1(+) Genetics 1999 152 1501 1512 10430579 Opresko PL Von Kobbe C Laine JP Harrigan J Hickson ID Telomere binding protein TRF2 binds to and stimulates the Werner and Bloom syndrome helicases J Biol Chem 2002 277 41110 41119 12181313 Petrini J Stracker T The cellular response to DNA double strand breaks: Defining the sensors and mediators Trends Cell Biol 2003 13 458 462 12946624 Schultz LB Chehab NH Malikzay A Halazonetis TD p53 binding protein 1 (53BP1) is an early participant in the cellular response to DNA double-strand breaks J Cell Biol 2000 151 1381 1390 11134068 Shiloh Y ATM and related protein kinases: Safeguarding genome integrity Nat Rev Cancer 2003 3 155 168 12612651 Smogorzewska A de Lange T Different telomere damage signaling pathways in human and mouse cells EMBO J 2002 21 4338 4348 12169636 Smogorzewska A van Steensel B Bianchi A Oelmann S Schaefer MR Control of human telomere length by TRF1 and TRF2 Mol Cell Biol 2000 20 1659 1668 10669743 Smogorzewska A Karlseder J Holtgreve-Grez H Jauch A de Lange T DNA ligase IV-dependent NHEJ of deprotected mammalian telomeres in G1 and G2 Curr Biol 2002 12 1635 1644 12361565 Stansel RM de Lange T Griffith JD T-loop assembly in vitro involves binding of TRF2 near the 3′ telomeric overhang EMBO J 2001 20 E5532 E5540 Takai H Smogorzewska A de Lange T DNA damage foci at dysfunctional telomeres Curr Biol 2003 13 1549 1556 12956959 Uziel T Lerenthal Y Moyal L Andegeko Y Mittelman L Requirement of the MRN complex for ATM activation by DNA damage EMBO J 2003 22 5612 5621 14532133 van Steensel B Smogorzewska A de Lange T TRF2 protects human telomeres from end-to-end fusions Cell 1998 92 401 413 9476899 Wong KK Maser RS Bachoo RM Menon J Carrasco DR Telomere dysfunction and Atm deficiency compromises organ homeostasis and accelerates ageing Nature 2003 421 643 648 12540856 Wu X Ranganathan V Weisman DS Heine WF Ciccone DN ATM phosphorylation of Nijmegen breakage syndrome protein is required in a DNA damage response Nature 2000 405 477 482 10839545 Zhao S Weng YC Yuan SS Lin YT Hsu HC Functional link between ataxia-telangiectasia and Nijmegen breakage syndrome gene products Nature 2000 405 473 477 10839544 Zhu XD Kuster B Mann M Petrini JH de Lange T Cell-cycle-regulated association of RAD50/MRE11/NBS1 with TRF2 and human telomeres Nat Genet 2000 25 347 352 10888888 Zhu XD Niedernhofer L Kuster B Mann M Hoeijmakers JH ERCC1/XPF removes the 3′ overhang from uncapped telomeres and represses formation of telomeric DNA-containing double minute chromosomes Mol Cell 2003 12 1489 1498 14690602

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020241PrimerGenetics/Genomics/Gene TherapyImmunologyMus (Mouse)Homo (Human)Mouse Models of Human Autoimmune Diseases: Essential Tools That Require the Proper Controls PrimerMorel Laurence 8 2004 17 8 2004 17 8 2004 2 8 e241Copyright: © 2004 Laurence Morel.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. Spontaneous Autoimmunity in 129 and C57BL/6 Mice-Implications for Autoimmunity Described in Gene-Targeted Mice What can we learn about human autoimmune disorders that have a genetic component -- such as systemic lupus erythematosus -- from mouse models? ==== Body Autoimmune diseases afflict a large segment of the population in Western countries. Many of them have been described, and rheumatoid arthritis, type I diabetes (also called insulin-dependent diabetes mellitus), multiple sclerosis, and systemic lupus erythematosus (SLE) are among the most common. Although tremendous progress has been made in disease management over the last decade, cures for these diseases have not yet been found. Consequently, a large research effort is sustained in this field. In addition, autoimmunity has intrigued basic immunologists since the early realization that the ability to discriminate self from non-self was at the core of the immune system's ability to protect an organism from pathogens while avoiding self-destruction. A failure of this mechanism results in autoimmune reactions that often lead to clinical disease. In spite of massive research efforts, the mechanisms by which autoimmune diseases develop are not clearly understood. Genetic predisposition as well as environmental triggers plays a role, but the identity of these factors has been largely elusive. The identification of the most common genetic and environmental factors that set off autoimmunity may lead to a better understanding of the ensuing pathogenesis, and offers the best hope for improved therapies, and ultimately, cures. So far, animal models have proved the best way to probe the mechanisms of disease in general, and autoimmune diseases in particular. In the past few decades, the mouse has become the model of choice for experimental medicine, and the rat is following close behind. Starting in the early twentieth century at the Jackson Laboratory (Bar Harbor, Maine, United States), the production of inbred strains of mice and the systematic collection and characterization of naturally occurring mutants have created the building blocks on which much of the research using animal models is now based. Inbred strains are collections of genetically identical animals obtained through selective breeding. These strains have provided homogenous experimental groups, with interindividual variability reduced to environmental (and stochastic) factors. In addition, inbred strains have an assortment of distinct phenotypes that have then been exploited as models of human diseases. Since the 1980s, techniques have been developed to manipulate the mouse genome. Specific genes now can be routinely over-expressed as transgenes, or eliminated by gene targeting, which creates a “knockout” (Smithies 1993; Wassarman and DePamphilis 1993). This approach, known as reverse genetics, has shown itself to be a powerful tool with which to evaluate the role of individual genes in various biological processes. The use of genetically engineered mouse models will likely play a major role in deciphering the function of a multitude of new genes revealed in the recently completed sequence of the mouse genome (Mouse Genome Sequencing Consortium 2002). Interestingly, the percentage of mouse genes without any homolog currently detectable in the human genome (and vice versa) has been estimated to be less than 1%, a fact that strengthens the validity of mouse models of human diseases. However, one has to be careful in directly applying data obtained from animal models to human diseases. Most human autoimmune diseases show an extremely heterogeneous clinical presentation, which animal models present as simplified versions. A mouse model, as in any reductionist approach, is both inconvenient, because it provides only a partial representation of the real biological complexity underlying the human disease, and advantageous, because it is a more tractable tool with which to probe mechanistic issues. In addition, a number of differences exist between the human and rodent immune systems (Mestas and Hughes 2004). Since immune dysfunctions are at the root of autoimmune diseases, such differences may limit extrapolations from animal models to autoimmune patients. Nonetheless, animal models are at the core of autoimmune research, and a large body of literature reflects the many advances brought by these models in terms of deciphering disease mechanisms. The relative lack of progress in certain human autoimmune diseases for which an animal model does not exist, such as neuropsychiatric lupus, corroborates the indispensable role played by animal models. Three basic types of animal models have been used in autoimmune research: spontaneous models, induced models, and genetically engineered models. The latter category has been further subdivided into transgenic and knockout strains (Table 1). Table 1 Examples of Common Mouse Models of Autoimmune Diseases Spontaneous models were produced through fortuitous observations of clinical symptoms reminiscent of a given human autoimmune disease developing in a given mouse strain, or in crosses between mouse strains. This happened, for example, with the nonobese diabetic (NOD) mouse, which developed type 1 diabetes, and the hybrid between the New Zealand Black (NZB) and the New Zealand White (NZW) mouse, (NZB × NZW)F1, which developed a lupus-like disease. Unfortunately, spontaneous models are not available for all human autoimmune diseases. Therefore, scientists have created induced models, often by exposing the animals to high doses of a suspected autoantigen at the same time as stimulating the immune system. Interestingly, marked differences exist between strains in their responses to these autoimmune inductions that reflect genetic variation associated with susceptibility to autoimmune diseases. For this reason, induced models have been limited to a small number of strains. For example, experimental autoimmune encephalomyelitis has been widely used as a model of multiple sclerosis. In this model, spinal cord homogenate or a protein derivative such as myelin basic protein is injected with a mixture of potent immunostimulants, most commonly in mice from the SJL strain. Another example of an induced model is collagen-induced arthritis, which has been used to study rheumatoid arthritis. In this model, type II collagen, a joint component, is injected also with immunostimulants, most commonly into mice from the DBA/1 strain. Finally, the ability to turn specific genes on or off, in specific cell types and/or at specific times, has created a plethora of mouse models limited only by the immunologist's imagination. Genes suspected to play a role in the pathogenesis of various autoimmune diseases have been evaluated this way, and those studies have been very informative in mapping out functional pathways that are targeted in these diseases. However, these models have intrinsic problems that have become more apparent in the past few years, and require careful controls to avoid possible misinterpretation. These problems are a result of the fundamental way in which transgenic and knockout strains are produced. When a piece of DNA carrying the gene of interest is injected as a “transgene” into fertilized eggs, it integrates randomly into the genome, and in doing so, potentially modifies the expression of the gene it integrates into. Since all genetic studies have recognized that a large number of genes are involved in autoimmune disease susceptibility, the potential for a transgene to hit one of those susceptibility genes is not negligible. This potentially confounding factor is usually controlled by producing and comparing several independent transgenic lines. More problematic is the interpretation of results obtained with knockout models. A gene is “knocked out” (KO) by homologous recombination of a disrupting piece of DNA within that gene. This genetic manipulation takes place in embryonic stem (ES) cells, which once mutated, are introduced into the inner cavity of a blastocyst (very early mouse embryo), creating chimeric embryos that are put back into female mice that carry the pregnancy to term. After multiple trials (and errors), ES cell lines from the 129 strain and blastocysts from the C57BL/6 (B6) strain have shown themselves to be superior in terms of efficiency and reliability. Consequently, this strain combination is at the origin of the overwhelming majority of knockout strains. Although the chimeric mice are usually backcrossed to B6 to dilute the contribution of the 129 genome, the knockout strains are always a mixture of the two genomes (Figure 1). Most importantly, a large region flanking the KO gene remains of 129 origin, unless extreme measures are taken to select for recombination between tightly linked markers. There have been sporadic reports of phenotypes initially attributed to deficiency in the expression of a given gene that disappeared with additional backcrosses to B6. The only possible interpretation was that these phenotypes were in fact due to 129 alleles that were replaced by B6 alleles with further backcrossing. Figure 1 Breeding Strategy Usually Performed to Transfer a KO Allele from the 129 Genome to the C57BL/6 (B6) Genome For clarity, only 4 of the 20 pairs of the mouse chromosomes are represented by black (B6) or red (129) bars. The KO allele is shown by a white box. Chimeric males are obtained from the integration of ES cells from the 129 strain that have been engineered to carry the KO allele to B6 blastocysts. These males are then bred to normal B6 females, resulting in an N1 progeny that is made up of 50% B6 and 50% 129 genome. N1 mice are subsequently “backcrossed” to B6, and their N2 progeny is selected for the presence of the KO allele. The contribution of 129 genome among the N2 progeny is normally distributed around a mean of 25%. This process can be repeated (shown here to N4), resulting in an average reduction of the 129 genome to one half of what it was in the previous generation. At any point in the process, homozygosity for the KO allele, which is necessary to prevent expression of that gene, can be obtained by intercrossing heterozygous mice, shown here at N4. The production of autoantibodies and mild antibody-related renal pathology, highly relevant to autoimmune diseases, especially SLE, has been reported independently in four mouse models using the (129 × B6) genetic background (Obara et al. 1979; Botto et al 1998; Bickerstaff et al. 1999; Santiago-Raber et al. 2001). It is generally accepted that genetic susceptibility to autoimmune diseases is conferred by multiple highly interactive genes that have small individual effects. In this context, the autoimmune phenotypes resulting from the combination of the 129 and B6 genomes may might therefore provide a primed background upon which the effects of deficiency in the target gene can be amplified. On the other hand, the autoimmune phenotype may be overwhelmingly contributed by the (129 × B6) genomic combination, with little if any effect of the deficiency of the KO gene. In this issue of PLoS Biology, Marina Botto and her colleagues have tested this hypothesis by taking one of their knockout models for SLE, the serum amyloid P component deficient mouse (Apcs −/−) (Bygrave et al. 2004). This group has published that Apcs −/− mice on a (129 × B6) genetic background develop a lupus-like disease, even after repeated backcrosses to B6 (Bickerstaff et al. 1999). Serum amyloid P component binds to debris generated from dying cells. Efficient removal of this debris has been shown to be critical to the prevention of the production of autoantibodies against intracellular material. Apcs was therefore an interesting candidate gene to evaluate. Apcs, however, is located in a region near the tip of mouse Chromosome 1 that is rich in SLE susceptibility loci and in genes that have been directly associated with SLE in humans (Wakeland et al. 1999). As mentioned above, the Apcs −/− mouse, although on a mostly B6 genomic background, has its entire Apcs flanking region replaced with 129 alleles. In a critical experiment, Botto and colleagues compared the autoimmune phenotypes of Apcs −/− mice to congenic mice (i.e., genetically identical, except for the gene of interest), carrying the same 129 region on Chromosome 1, but expressing Apcs. Amazingly, no difference was found between the two strains regarding the production of autoantibodies, clearly eliminating Apcs deficiency as a mechanism for this autoimmune process. Apcs deficiency was however associated with markedly increased renal damage, suggesting that this gene may be involved in preventing pathological consequences of autoantibody production. It has been reported anecdotally that the most common outcome of a genetic knockout is a lupus-like disease. Botto and her colleagues may have identified the reason behind this somewhat surprising observation as a spurious consequence of the gene-targeting process. Gene targeting has been an invaluable tool in understanding the mechanisms of immunological diseases, and has still a very important role to play with increasingly sophisticated techniques of selective targeting. The immediate consequence of this work should be an increased scrutiny for appropriate controls, which may include congenic mice carrying the same 129 flanking region, but expressing the targeted gene (Figure 2). Figure 2 Congenic Strains (Left and Right) of a Lupus-Prone Mouse (Middle). Image courtesy of Jessica Merritto The past few years have shown that genetic susceptibility to autoimmune diseases involves a large number of genes with small individual contributions. In spite of this great complexity, advances have been made, and a small but growing number of susceptibility genes have been identified (Morahan and Morel 2002). A common trait shared by successful studies has been the use of mouse models, either directly or indirectly. As the pace of genetic analysis increases in autoimmune diseases, and powerful tools have been created to navigate between the mouse and human genomes, the use of mouse models has been reaffirmed at multiple levels. Mouse models are used to discover new susceptibility genes that can then be assessed in patient populations, as well as to validate genes that have been directly identified in human genetic studies. Mouse models are also used to perform detailed functional and physiological analyses that cannot be conducted in humans. Finally, mouse models have been invaluable to screen disease-specific therapeutic agents. Using mouse models has its pitfalls; many differences, both obvious and subtle, exist between mice and humans. Those differences are, however, outweighed by the power of the experimental system offered by the mouse. What the new study of Botto and colleagues reminds us is that the appropriate control is still crucial to meaningful data interpretation. Keeping that in mind, one can predict that many of the keys to human autoimmune diseases are still in the mouse room. Laurence Morel is with the Department of Pathology, Immunology and Laboratory Medicine at the University of Florida College of Medicine, Gainesville, Florida, United States of America. E-mail: morel@pathology.ufl.edu Abbreviations ESembryonic stem KOknocked out NODnon-obese diabetic NZBNew Zealand black NZWNew Zealand white SLEsystemic lupus erythematosus ==== Refs References Bickerstaff MCM Botto M Hutchinson WL Herbert J Tennent GA Serum amyloid P component controls chromatin degradation and prevents antinuclear autoimmunity Nat Med 1999 5 694 697 10371509 Botto M Dell'Agnola C Bygrave AE Thompson EM Cook HT Homozygous C1q deficiency causes glomerulonephritis associated with multiple apoptotic bodies Nat Genet 1998 19 56 59 9590289 Bygrave A Rose K Warren J Cortes-Hernandez J Rigby R Spontaneous autoimmunity in 129 and C57BL/6 mice—Implications for autoimmunity described in gene-targeted mice PLoS Biol 2004 2 e243 10.1371/journal.pbio.0020243 15314659 Mestas J Hughes CCW Of mice and not men: Differences between mouse and human immunology J Immunol 2004 172 2731 2738 14978070 Morahan G Morel L Genetics of autoimmunity in patients and models Curr Opin Immunol 2002 14 803 811 12413533 Mouse Genome Sequencing Consortium Initial sequencing and comparative analysis of the mouse genome Nature 2002 420 520 562 12466850 Obara T Tanaka T Stockert E Good RA Autoimmune and lymphoproliferative disease in (B6-GIX+ × 129)F1: Relation to naturally occurring antibodies against murine leukemia virus-related surface antigens Proc Natl Acad Sci U S A 1979 76 5289 5293 228283 Santiago-Raber ML Lawson BR Dummer W Barnhouse M Koundouris S Role of cyclin kinase inhibitor p21 in systemic autoimmunity J Immunol 2001 167 4067 4074 11564828 Smithies O Animal models of human genetic diseases Trends Genet 1993 9 112 116 8516844 Wakeland EK Wandstrat AE Liu K Morel L Genetic dissection of systemic lupus erythematosus Curr Opin Immunol 1999 11 701 707 10631557 Wassarman PM DePamphilis ML Guide to techniques in mouse development 1993 San Diego Academic Press

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020242Research ArticleCancer BiologyCell BiologyDevelopmentMus (Mouse)p19 Arf Suppresses Growth, Progression, and Metastasis of Hras-Driven Carcinomas through p53-Dependent and -Independent Pathways p19Arf and Tumor ProgressionKelly-Spratt Karen S 1 Gurley Kay E 1 Yasui Yutaka 1 Kemp Christopher J cjkemp@fhcrc.org 1 1Fred Hutchinson Cancer Research CenterSeattle, WashingtonUnited States of America8 2004 17 8 2004 17 8 2004 2 8 e24216 1 2004 27 5 2004 Copyright: © 2004 Kelly-Spratt et al.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. Deterministic Tumor Evolution Ectopic expression of oncogenes such as Ras induces expression of p19Arf, which, in turn, activates p53 and growth arrest. Here, we used a multistage model of squamous cell carcinoma development to investigate the functional interactions between Ras, p19Arf, and p53 during tumor progression in the mouse. Skin tumors were induced in wild-type, p19Arf-deficient, and p53-deficient mice using the DMBA/TPA two-step protocol. Activating mutations in Hras were detected in all papillomas and carcinomas examined, regardless of genotype. Relative to wild-type mice, the growth rate of papillomas was greater in p19Arf-deficient mice, and reduced in p53-deficient mice. Malignant conversion of papillomas to squamous cell carcinomas, as well as metastasis to lymph nodes and lungs, was markedly accelerated in both p19 Arf- and p53-deficient mice. Thus, p19Arf inhibits the growth rate of tumors in a p53-independent manner. Through its regulation of p53, p19Arf also suppresses malignant conversion and metastasis. p53 expression was upregulated in papillomas from wild-type but not p19 Arf-null mice, and p53 mutations were more frequently seen in wild-type than in p19 Arf-null carcinomas. This indicates that selection for p53 mutations is a direct result of signaling from the initiating oncogenic lesion, Hras, acting through p19Arf. A squamous cell carcinoma model shows Ras mutation not only initiates tumor development but, through Arf and p53, directly influences the subsequent evolutionary trajectory of the tumors ==== Body Introduction Tumor development and metastasis is a multistep process of somatic cell evolution that includes uncontrolled proliferation, impaired apoptosis, loss of differentiation, immortalization, neovascularization, invasion, and metastatic spread (Hanahan and Weinberg 2000). This evolutionary transformation can be operationally divided into distinct stages, including initiation, promotion, progression, and metastasis (DiGiovanni 1992). Mutations in both oncogenes and tumor suppressor genes are found in end-stage tumors, implying their causal role in tumor development. However, the association of mutations in specific genes with specific phenotypic states during tumor progression is poorly characterized for most human solid tumors. It is also largely unknown whether each mutation is an independent event or whether there is a preferred sequence or combination of mutations that is favored. The purpose of this study is to investigate the functional interactions between the mutational activation of the oncogene Ras, and two tumor suppressors, p19 Arf, and p53, using a multistage epithelial tumor model. Ras is among the most frequently mutated oncogenes in human cancer, with approximately 30% of tumors carrying an activating mutation in one of three family members, Hras, Kras, or Nras (Bos 1989). Cancer-associated mutations in Ras result in constitutively active Ras protein. Ras is a nodal signaling molecule that regulates multiple signaling pathways, leading to profound changes in cellular proliferation, apoptosis, differentiation, senescence, cytoskeletal organization, adhesion, and migration (Campbell et al. 1998). Ras has also been shown to induce invasiveness and metastasis of cancer cells (Pozzatti et al. 1986; Webb et al. 1998; Varghese et al. 2002). These pleiotropic effects suggest Ras may influence multiple steps in tumor progression. p53 is the most frequently mutated tumor suppressor gene in human cancer, with more than 50% of tumors showing mutations (Hollstein et al. 1994). p53 is a nodal signaling protein that coordinates the cellular response to different types of stress, including oncogene activation, DNA damage, abnormal cell adhesion, altered ribonucleotide pools, hypoxia, and redox stress (Ko and Prives 1996; Giaccia and Kastan 1998). These stress stimuli are thought to activate p53 by inducing posttranslational modifications that stabilize p53 and enhance its ability to act as a transcription factor (Siognov and Haupt 1999; Vousden and Lu 2002). Loss of p53 function leads to loss of cell cycle checkpoints, impaired apoptosis, genomic instability, and tumor progression. However, a major unresolved issue is, of the many signals that have been shown to activate p53 using a variety of model systems, which one regulates p53 during autochthonous tumor progression. A mechanistic connection between Ras signaling and activation of p53 that involves the tumor suppressor p19Arf was recently established. p19Arf (p14Arf in humans; Stott et al. 1998) is encoded by the p16Ink4a/p19 Arf locus, but because it is transcribed in an alternative reading frame, the protein product is unrelated to the p16Ink4a protein (Quelle et al. 1995; Kamijo et al. 1997). Deletions or mutations at the p16Ink4a/p19 Arf locus are frequently (more than 50% of cases) seen in human tumors (Ruas and Peters 1998). p19Arf was established as a bona fide tumor suppressor in studies showing that mice lacking p19Arf are highly susceptible to spontaneous tumorigenesis (Kamijo et al. 1997). In vitro studies had shown that enforced expression of oncogenes such as Ras, c-Myc, and E1A activated p53 and induced growth arrest, senescence, or apoptosis depending on the cell type or oncogene used (Lowe and Ruley 1993; Hermeking and Eick 1994; Serrano et al. 1997). These cellular responses were impaired in cells lacking p53, indicating that functional p53 was required. The involvement of p19Arf was first suggested by experiments showing that enforced expression of Ras, Myc, and E1A in cells induced p19Arf, leading to G1 and G2 cell cycle arrest that was p53-dependent (Kamijo et al. 1997; Stott et al. 1998). Cells lacking p19Arf showed impaired p53 induction in response to these oncogenes, and, like p53-deficient cells, escaped growth arrest and were immortalized (Zindy et al. 1998; de Stanchina et al. 1998; Palmero et al. 1998; Lin and Lowe 2001; Ferbeyre et al. 2002). In vivo evidence linking oncogene signaling to p19Arf and p53 was obtained in a lymphoma model. B-cell lymphomas from transgenic Eμ-myc mice also show a dependence on p19Arf to activate p53, and Eμ-myc mice lacking either p19Arf or p53 developed lymphomas much faster (Eischen et al. 1999; Schmitt et al. 1999). p19Arf regulates p53 through mutual binding to the p53 regulator Mdm2. The levels of p53 in cells are normally kept low because of feedback regulation by the Mdm2 protein (Haupt et al. 1997; Kubbutat et al. 1997). Mdm2 binds to p53 and targets it for degradation by nuclear to cytoplasmic shuttling and through the E3 ubiquitin ligase activity of Mdm2 (Roth et al. 1998; Honda and Yasuda 1999). p19Arf sequesters Mdm2 from p53 and inhibits the ubiquitin ligase activity of Mdm2, resulting in increased stability and accumulation of p53 (Pomerantz et al. 1998; Tao and Levine 1999; Weber et al. 1999; Zhang and Xiong 1999). The importance of the Ras-p19Arf-p53 pathway in growth arrest was established in culture systems involving the ectopic overexpression of mutant Ras in both murine embryonic fibroblasts (Ferbeyre et al. 2002; Palmero et al. 1998) and primary epidermal keratinocytes (Lin and Lowe 2001). Both in vitro and in vivo models have established that the gene dosage of mutant Ras is critical for its oncogenic function. A single copy of mutant Ras is insufficient to transform cells; at least two mutant alleles are required (Finney and Bishop 1993). Duplication or even amplification of mutant Ras alleles is frequently observed in tumors (Quintanilla et al. 1986; Bremner and Balmain 1990). Ras activates multiple signaling pathways, and quantitative differences in Ras activity can lead to activation of different signals and qualitatively different cellular phenotypes (Shields et al. 2000). Cell culture conditions can add additional stress signals that are known to impinge on p19Arf and p53, leading to cell cycle arrest (Sherr and DePinho 2000; Lowe and Sherr 2003), and cannot recapitulate the complex cellular ecology of tumor progression. Thus, to understand the interactions between Ras, p19Arf, and p53 that drive tumor progression, an autochthonous tumor model is required. Since more than 90% of human cancers are epithelial in origin, a carcinoma model system is favored. Mouse skin carcinogenesis is perhaps the best-characterized in vivo model of epithelial neoplasia and was instrumental in establishing the concepts of initiation, promotion, and progression (DiGiovanni 1992). The two-stage chemical protocol involves treatment of mice with a carcinogen, DMBA, followed by multiple applications of TPA. This treatment induces benign squamous cell papillomas, nearly 100% of which have sustained an AT mutation in codon 61 of Hras (Quintanilla et al. 1986). As this mutation results in constitutively active Ras protein, this protocol is ideal to study the biological consequence of Ras activation during the entire natural history of tumor progression. Papillomas consist of a series of folded epidermal or follicular hyperplasias that protrude from the skin surface. Papillomas have dysplastic characteristics including disturbed cell polarity, basal cell hyperplasia, disturbed maturational sequence, increased mitotic activity, and increased nuclear to cytoplasmic ratio (Yuspa 1994). In most strains of mice, progression of these benign papillomas to malignant squamous cell carcinomas (SCCs) is a rare and late event. SCCs are usually endophytic tumors that present as plaques with an ulcerated surface. These tumors break through the basement membrane and progressively invade the underlying dermis and subcutaneous tissues, and rarely, can metastasize to regional and distant sites. SCCs are characterized by a disorderly proliferation of epithelial cells with increased cellular atypia and abnormal mitotic figures, and are classified into four grades: well-differentiated, moderately differentiated, poorly differentiated, and spindle cell carcinoma. The unique advantage of this skin tumor model is the ability to directly observe and quantify these evolutionary stages. Loss of p53 function is strongly associated with the benign to malignant transition of chemically induced SCCs. Mutations in p53 are seen more frequently in carcinomas than in papillomas (Burns et al. 1991; Ruggeri et al. 1991). p53 knockout mice show accelerated malignant progression of SCCs (Kemp et al. 1993). The strongest association of p53 with malignant progression was revealed in p53+/− mice, in which loss of the remaining wild-type allele of p53 was seen in carcinomas but not papillomas, indicating a strong selective pressure to completely inactivate p53 during this transition. Accelerated malignant progression seen in the absence of p53 was accompanied by extensive loss of differentiation and lymph node metastasis, indicating that p53 inhibits multiple steps involved in malignant tumor progression. Here, we used the mouse skin tumor model to examine the role of p19Arf in regulating the levels and tumor suppressor activity of p53. In addition, we addressed the biological and functional significance of alterations in p19Arf, p53, or both during tumor initiation, promotion, progression, and metastasis. Similar to p53-null mice, loss of p19 Arf resulted in increased malignant conversion, more aggressive tumors, and frequent and rapid metastasis. However, in contrast to p53-null mice, p19 Arf-null mice had greater tumor numbers and tumor growth rates, indicating additional, p53-independent tumor suppressor functions for p19Arf. Results Increased Papilloma Number and Size in p19Arf-Deficient Mice Both in vitro and in vivo studies have demonstrated that p19Arf is a tumor suppressor (Eischen et al. 1999; Kamijo et al. 1999; Schmitt et al. 1999; Lin and Lowe 2001). However, other than regulation of p53, little else is known about the role of p19Arf in tumor suppression. To address this, groups of p19 Arf+/+, p19 Arf +/−, and p19 Arf− /− littermates were treated with a single dose of DMBA followed by twice weekly application of TPA for 15 wk (see Materials and Methods). Papillomas began to appear in all three genotypes after 9 wk of promotion. By 20 wk, p19 Arf+/− and p19 Arf−/− mice showed a significant increase in papilloma number and size compared to wild-type mice (Figure 1A). Relative to wild-type littermates, p19 Arf−/− mice had an average of 2.97 more papillomas (95% CI (0.70, 5.24); p = 0.010) and p19 Arf+/− mice had an average of 2.60 more papillomas (95% CI (0.05, 5.14); p = 0.045) in weeks 18–30 after DMBA administration. Average papilloma size was also greater in both p19 Arf−/− and p19 Arf+/− mice compared to wild-type mice (Figure 1B). This effect was seen as early as 12 wk and increased through time so that by 28 wk, 33% (47/141) of papillomas from p19 Arf−/− mice were greater than 8 mm in diameter versus 14% (38/267) from wild-type mice (p < 0.0001). Papillomas from p19 Arf-deficient mice measured up to 16 mm in diameter while very few papillomas on wild-type mice measured more than 9 mm. Thus, p19 Arf deficiency resulted in faster growing papillomas, indicating a role for p19 Arf in regulating the early stages of benign tumor growth. Figure 1 Skin Tumor Multiplicity, Size, and Progression in p19 Arf-Deficient Mice (A) Average number of papillomas (more than 2 mm in diameter) per mouse is plotted versus the number of weeks postinitiation. Both p19 Arf (Arf)+/− and p19 Arf−/− mice show greater numbers of tumors than p19 Arf+/+ mice. (B) Comparison of papilloma size (in mm) between p19 Arf+/+, p19 Arf+/−, and p19 Arf−/− mice through 28 wk postinitiation. An increase in the largest size class of tumors is seen in p19 Arf+/− and p19 Arf−/− mice but not p19 Arf+/+ mice. (C) Percentage of mice bearing at least one carcinoma is plotted versus the number of weeks postinitiation. p19 Arf−/− mice show the shortest latency and greatest incidence of carcinoma conversion, with p19 Arf+/− mice showing an incidence between the p19 Arf−/− and p19 Arf+/+ mice. Time of appearance of lymph node metastasis is noted above the graph as a vertical line for each mouse analyzed. Metastasis to lymph node occurred frequently and sooner in p19 Arf-deficient mice than in wild-type mice. Mutations in Hras are found in more than 95% of DMBA/TPA-induced skin tumors (Quintanilla et al. 1986; Kemp et al. 1993). In vitro studies showed that mutant Ras induces p19Arf, which, in turn, inhibits Ras-induced proliferation (Sherr and Weber 2000). Thus, loss of p19Arf might reduce or eliminate the need to mutate Ras. All papillomas from p19 Arf+/+ (5/5), p19 Arf+/− (4/4), and p19 Arf−/− (5/5) mice contained the identical A→T transversion at codon 61 of Hras, resulting in an amino acid change from glutamine to leucine and a constitutively activated Ras protein (Quintanilla et al. 1986). Thus, mutation of Ras is very strongly selected for during epithelial carcinogenesis, with or without the presence of p19Arf, and loss of p19Arf cooperates with activated Ras to accelerate tumor growth. Increased Malignant Progression and Metastasis in p19Arf-Deficient Mice The rate of malignant conversion of papillomas to carcinomas is greatly increased in the absence of p53 function (Kemp et al. 1993). To determine if loss of p19Arf had a similar effect, progression was quantified by visual inspection and confirmed by histologic analysis. The rate of conversion from papillomas to carcinomas was dramatically accelerated in p19Arf-deficient mice. Carcinomas developed in p19 Arf−/− mice as early as 14 wk after initiation, whereas papillomas from p19 Arf+/+ mice began to convert much later, after 22 wk (Figure 1C). By 28 wk, 100% of the p19 Arf−/− mice had at least one carcinoma, compared to only 25% of the wild-type mice. The p19 Arf+/− mice showed an intermediate conversion rate, with 60% of the mice bearing at least one carcinoma, indicating an p19Arf gene dosage effect on malignant progression. In addition to reducing the latency, p19Arf deficiency increased the frequency of malignant conversion. The odds of developing a carcinoma within 30 wk after DMBA administration was 8.10 times higher for p19 Arf−/− mice (95% CI (1.90, 34.56); p = 0.005) and 3.11 times higher for p19 Arf+/− mice (95% CI (0.90, 10.77); p = 0.073) compared to wild-type mice. The reduced carcinoma latency and increased conversion frequency in the p19 Arf-null mice implicate loss of p19Arf as a critical rate-limiting step in malignant SCC progression. Histologic analysis revealed that the carcinomas from control mice ranged in grade from well-differentiated to poorly differentiated SCCs. Carcinomas from p19 Arf+/− and p19 Arf−/− mice also showed a range of grades but a significant number (9/12) were characterized as spindle cell carcinomas. These were characterized by packed and spindle-shaped cells with elongated pleiomorphic nuclei and abundant abnormal mitotic figures. These cells grew in a homogenous pattern with very little evidence of the cellular organization typical of low-grade tumors. These tumors showed focal areas of squamous differentiation, indicating that they were derived from squamous epithelium. p19 Arf deficiency also increased dissemination and establishment of metastatic SCCs. Carcinoma-bearing p19Arf-deficient mice frequently presented with enlarged lymph nodes, and in several cases tumors were noted on the lungs. (Table 1; Figure 2). Histologic analysis revealed that these lymph nodes and lung tumors contained cells with features similar to the primary SCCs, including squamous differentiation, keratin pearls, high mitotic index, nuclear pleomorphism, and disturbed cell polarity (Figure 2D and 2E). Immunostaining with a keratin-specific antibody showed that these cells were epithelial in origin, confirming that they were metastatic SCCs (Figure 2F and 2G). 60% of local enlarged lymph nodes from carcinoma-bearing p19 Arf−/− mice contained such squamous carcinoma deposits, compared to 10% of those from wild-type mice (Table 1). Metastatic lesions from p19 Arf-deficient mice were seen as early as 16 wk after initiation and must have occurred very soon after or simultaneously with papilloma to carcinoma conversion (see top of Figure 1C). In contrast, only one metastatic lesion was seen in one p19 Arf+/+ mice through 36 wk of observation. p19 Arf+ /− mice displayed an intermediate frequency of metastasis. Newly formed blood vessels, some measuring up to 2 mm in diameter, were seen on the underside of each tumor and appeared to lead directly to the inguinal or brachial lymph node (Figure 2A and 2B). Several primary p19 Arf-deficient carcinomas showed clear evidence of penetration of tumor cells through blood vessel walls, with intravascular rafts of tumor cells seen (Figure 2C), indicating a route by which tumor cells could migrate to distant organs through the circulation. Thus, in addition to increasing benign tumor growth, loss of p19Arf accelerated both benign to malignant conversion and metastatic spread of epithelial tumors. Tumors lacking p19Arf have a higher potential for metastatic spread. Figure 2 Metastasis of Primary SCC to Lymph Nodes and Lungs in p19 Arf-Deficient Mice (A) Underside of skin from tumor-bearing mouse shows newly formed blood vessels surrounding tumor site (arrow) and leading to inguinal lymph node (arrowhead). (B) Enlarged inquinal lymph node (left) containing metastatic SCC and blood vessel formation (arrow) compared to normal lymph node (right). (C) H&E stain of carcinoma section with prominent blood vessel (bv). Carcinoma cells (ca) have penetrated blood vessel wall (arrow). (D) H&E stain of lymph node bearing infiltrating SCC cells (arrow) among normal lymphocytes (arrowhead). (E) H&E stain of lymph node bearing metastatic differentiated SCC. (F) Immunostain with pan-keratin antibody of papilloma. (G) Immunostain with pan-keratin antibody of lymph node with metastatic SCC. (H and I) H&E stain of normal lung (arrowhead) with large metastatic SCC deposit (arrow). (J) H&E stain of lung metastasis with secondary site of infiltration (arrow). (D–G, J): 20× magnification. Inserts in (E–G): 40× magnification. Table 1 Metastatic Frequency of SCC Denominator indicates number of tissues examined. Numerator indicates number of tissues bearing SCC Reduced p53 Expression in Papillomas from p19Arf-Deficient Mice The p53 expression in DMBA/TPA-induced papillomas is increased relative to adjacent normal skin (Kemp et al. 2001). As multiple signals can lead to the accumulation of p53, including activated oncogenes, DNA damage, and hypoxia, it was not clear which was operative in this setting. As nearly all carcinogen-induced papillomas carry mutations in Hras, we questioned whether increased p53 expression was due to signaling from Ras through p19Arf. Western blot analysis of nuclear lysates showed increased levels of both p19Arf and p53 in wild-type papillomas compared to normal skin (Figures 3 and 4). In contrast, p53 expression was not detectable in papillomas from p19 Arf− /− mice and was intermediate and variable in papillomas from p19 Arf+/− mice. Immunostaining of paraffin-embedded sections confirmed the Western analysis, with nuclear staining of p53 detected in the epidermal cells of papillomas from wild-type mice, reduced numbers of p53-positive cells in the p19 Arf heterozygous papillomas, and undetectable p53 staining in p19 Arf-null papillomas (Figure 3B). To determine if p53 could still be induced in the absence of p19Arf by an alternative pathway, tumor-bearing mice were irradiated with 4Gy ionizing radiation and sacrificed 4 h later, and their tissues were examined for p53 expression. Both Western blot analysis and immunostaining revealed prominent induction of p53 in basal cells of normal skin and papillomas from both wild-type and p19 Arf-null mice (Figure 3A and 3B). Thus, the induction of p53 seen in mutant Ras-containing tumors is due to signaling through p19Arf. These results provide in vivo confirmation of the model, largely derived from in vitro studies, that posits that signaling from mutant Ras acts through p19Arf to induce p53. Other pathways to activate p53, such as those initiated by DNA damage, remain functional in the absence of p19Arf. Figure 3 Reduced p53 Expression in Skin Tumors from p19Arf-Deficient Mice (A) Western blot analysis of nuclear lysates from skin tumors from p19 Arf (Arf)+/+, p19 Arf+/−, and p19 Arf−/− mice using p53-specific antibody. PA, papilloma; skin IR, irradiated normal skin (B) p53 immunostain of paraffin-embedded skin tumor sections from p19 Arf+/+, p19 Arf+/−, and p19 Arf−/− mice (arrows indicate positive stained cells) (top). p53 immunostain of irradiated papillomas (IR) from p19 Arf+/+ and p19 Arf−/− mice (bottom). p53 is not detected in normal skin or tumors from p19 Arf−/− mice, but is induced by irradiation in both normal and tumor cells from p19 Arf−/− mice. Figure 4 LOH of Wild-Type p19Arf Allele in p19Arf+/− Tumors (A) LOH analysis by semiquantitative PCR of the wild-type p19Arf allele in p19Arf+/− papillomas and carcinomas. Gradient made from kidney DNA used for quantitation of wt/mu ratio (top row). wt, wild-type allele; mu, knockout allele; asterisk, loss or reduction of p19Arf wild-type band. (B) Western blot analysis of nuclear lysates from papillomas (PA) and carcinomas (CA) from p19Arf+/+, p19Arf+/−, and p19Arf−/− mice. Loss of the Wild-Type p19Arf Allele in Tumors from p19Arf+/− Mice Occurs During Benign to Malignant Conversion p19 Arf+/− mice displayed an intermediate rate of papilloma to carcinoma conversion (see Figure 1C). Two genetic models could explain this heterozygous phenotype. p19 Arf could be haploinsufficient, in which case no mutation or loss of heterozygosity (LOH) should be seen in the remaining wild-type p19 Arf allele in carcinomas. Alternatively, p19 Arf could be recessive, in which case LOH or reduction to a homozygous null state would be expected. The fate of the wild-type allele of p19 Arf in tumors from heterozygous mice was assessed by semiquantitative PCR analysis of genomic DNA. Three of 15 (20%) papillomas examined showed evidence of loss of the wild-type p19 Arf allele, compared to ten of 15 (67%) carcinomas (p = 0.0027) (Figure 4A), indicating LOH occurs primarily during malignant conversion. We next examined p19Arf expression in tumor lysates by Western blot analysis with a p19Arf-specific antibody. In wild-type mice, p19Arf protein was elevated in all papillomas and three of six carcinomas compared to normal skin (Figure 4B). Increased expression of p19Arf is consistent with activation of Ras in these tumors. p19Arf expression was also increased in papillomas from p19 Arf+/− mice but not to the levels seen in wild-type mice, indicating that p19Arf protein levels in tumors reflect p19 Arf gene dosage. p19Arf protein was reduced or undetectable in four of six carcinomas from p19 Arf+/− mice, consistent with the LOH data. Collectively, these data indicate that p19Arf expression is induced in tumors. Germline deletion of one p19 Arf allele provides a selective advantage during early tumor growth, and loss of the second allele confers an additional phenotype, destabilization of p53, and enhanced malignant progression. Independent Contributions of p19Arf and p53 to Tumorigenesis The observations that p19Arf and p53 were upregulated in papillomas, that p53 expression was reduced in p19 Ar f-null papillomas, and that loss of p19Arf had a similar effect on tumor progression as that of loss of p53, provide strong in vivo support of the model whereby p19Arf regulates p53 in response to mutational activation of Hras. However, enhanced tumor growth in p19 Arf-null mice, in contrast to reduced tumor growth in p53-null mice (Kemp et al. 1993), suggests additional tumor suppressor functions of p19Arf, independent of p53. To examine the effect of the combined loss of p53 and p19Arf tumor suppressors, skin tumors were induced in p19 Arf and p53 single and compound mutant littermates. Relative to wild-type mice, p53-null mice developed fewer tumors, averaging 4.05 fewer papillomas (95% CI (−6.10, −2.00); p = 0.0001) 10–16 wk after the DMBA administration, while p19 Arf-null mice averaged 2.68 more papillomas (95% CI (0.52, 4.84); p = 0.015) 18–40 wk after the DMBA administration (Figure 5A). The p19Arf /p53 double-null mice showed a papilloma multiplicity similar to wild-type mice. p53 −/− tumors were also smaller, while both p19Arf−/− and p19Arf−/−p53−/− tumors were larger compared to wild-type tumors. p19Arf and p53 also affected tumor size and morphology. Wild-type papillomas were highly exophytic, while tumors from both p19 Arf- and p53-deficient mice grew in a flatter, endophytic pattern (Figure 5B). Thus, loss of p19Arf increased the number and size of both wild-type p53 and p53-null tumors, demonstrating that p53 and p19Arf contribute independently to the early stages of tumor development. Figure 5 Tumor Multiplicity and Proliferative Index in p19 Arf /p53 Compound Mutant Mice (A) Average number of papillomas (more than 2 mm in diameter) per mouse is plotted against the number of weeks post-initiation. (B) Image of wild-type, p19 Arf (Arf)−/−, p53−/−, and p19Arf−/−p53−/− mice with skin tumors at time of sacrifice. Wild-type mice show large exophytic tumors, while both p19 Arf- and p53-deficient mice have endophytic tumors. Note larger tumors in p19Arf /p53 compound mutant mice relative to p53 single mutants. (C) BrdU-positive cells in papillomas from wild-type, p53−/−, p19 Arf−/−, and p19 Arf−/−p53−/− mice at 10 wk postinitiation. (Bars represent average counts ± standard deviation from ten fields and five mice). p53−/− tumors show significantly fewer BrdU-positive cells than either p19 Arf−/− or wild-type tumors (p < 0.05, Wilcoxon one-sided t-test). To determine whether tumor growth in mice lacking p19Arf or p53 is due to altered proliferation, additional cohorts of mice were treated with DMBA/TPA. Tumor-bearing mice 8–10 wk post DMBA treatment were injected with BrdU and sacrificed 1 h later. p53-null papillomas showed a reduced BrdU labeling index compared to wild-type mice, while the p19 Arf-null tumors showed a higher BrdU labeling index (Figure 5C). The p19 Arf /p53 double-null papillomas showed a proliferative index similar to that of wild-type tumors. Thus, decreased proliferation contributes to the reduced tumor growth seen in the p53-null mice. Apoptotic cells were very rare in papillomas regardless of p53 genotype or radiation exposure (apoptotic index over 40-fold less than proliferation index) (unpublished data). Thus, p53-regulated apoptosis does not appear to play a major role in SCC development, at least at the papilloma stage. Tumor Progression in p19Arf /p53 Compound Mutant Mice To determine if p19Arf and p53 cooperate during tumor progression, papilloma to carcinoma conversion was evaluated in p19Arf−/−, p53−/−, and p19Arf−/−p53−/− littermates. Tumor progression was accelerated in all p19 Arf- and p53-deficient genotypes compared to wild-type littermates (Figure 6A). Carcinoma latency and multiplicity was almost identical for p19 Arf−/− mice regardless of p53 genotype (p53+/+, p53+/−, or p53−/−) (Figure 6A), indicating no cooperation between p19Arf and p53 for malignant conversion per se. However, the size of carcinomas in both p19 Arf−/− and p19 Arf−/−p53−/− mice was considerably greater than that seen in p53−/− mice at comparable time points (see Figure 5B). This confirms a significant impact of p19Arf on suppressing tumor growth that does not require p53. Figure 6 Tumor Progression and p53 LOH in p19Arf /p53 Compound Mutant Mice (A) Average number of carcinomas per mouse is plotted against the number of weeks postinitiation. Tumor progression was accelerated in all p19 Arf (Arf)- and p53-deficient genotypes compared to wild-type littermates. Carcinoma latency and multiplicity was almost identical for p19 Arf−/− mice regardless of p53 genotype (p53+/+, p53+/−, or p53−/−). (B) LOH of the wild-type p53 allele by semiquantitative PCR in p19 Arf /p53 compound tumors. Gradient made from kidney DNA used for quantitation of wt/mu ratio (top row). wt, wild-type allele; mu, knockout allele; asterisk, tumors with reduction of wild-type p53. In p53+/− mice there is strong selective pressure to lose the wild-type allele during conversion to malignancy (Kemp et al. 1993). As p19Arf regulates p53, we next wished to determine if the selective pressure to lose p53 was reduced in the absence of p19Arf. Tumors from p53+/− mice of all three p19 Arf genotypes ( p19 Arf+/+, p19 Arf+/−, and p19 Arf−/−) were assessed for LOH of p53 by semiquantitative PCR analysis of genomic DNA. Two out of seven papillomas from p19 Arf+/+p53+/− mice show loss of the remaining p53 allele, while all papillomas examined from p19 Arf+/−p53+/− (n = 8) and p19 Arf−/−p53+/− (n = 8) mice show retention of wild-type p53 (Figure 6B). Seven of 14 (50%) carcinomas from p19 Arf+/+p53+/−, and three of 14 (21%) from p19 Arf+/−p53+/−, but only one of 12 (8%) from p19 Arf−/−p53+/− (p = 0.036) showed loss of p53. Thus, deletion of p19Arf disrupts the activation of p53 and thereby reduces selection for mutations in p53 during malignant progression. Discussion Using a multistage model of tumor progression, we have examined the functional interactions between the oncogene Hras and the tumor suppressors p19Arf and p53. Somatic mutation of Ras is an early and frequent event in this model of tumor development. Against this backdrop, p19Arf has at least two distinct tumor suppressor properties, which act at different stages of tumor development and which show a range of gene dosage effects. Loss of one or both p19 Arf alleles leads to accelerated growth of benign tumors, indicating p19 Arf is partially haploinsufficient for suppression of this early growth phenotype. Although p19Arf regulates p53 at this stage, suppression of tumor growth per se by p19Arf does not appear to be mediated through p53. p19Arf also inhibits the benign to malignant transition and subsequent tumor cell dissemination and metastasis, and this effect of p19Arf is, in contrast, mediated through p53. LOH of p19 Arf occurs preferentially in malignant tumors, indicating complete loss of p19Arf is favored during progression. Thus, p19Arf inhibits several stages in Ras-driven tumor progression. Furthermore, Ras is connected to both p19Arf and p53 through a signaling pathway, indicating that selection for mutations in the p19Arf / p53 pathway are a direct consequence of the initial Ras mutation. Ras, p19Arf, p53, and Early Tumor Growth The observation that Hras mutations are found at high frequency in papillomas from wild-type and both p19Arf- and p53-deficient mice indicates that squamous epithelial cells harboring Hras mutations have a strong selective advantage, with or without the presence of p19Arf or p53. This permits analysis of the effects of Ras on defined genetic backgrounds in the natural setting of tumor cell evolution. The expression levels of both p19Arf and p53 were increased in wild-type papillomas but not in p19 Arf−/− papillomas, indicating that p19Arf regulates p53 in response to activated Ras in vivo. However, other signals to induce p53, such as those stemming from DNA damage, remain intact in the absence of p19Arf, as shown by the rapid increase in p53 in irradiated p19 Arf-null tumors. Thus, of the many stimuli that have been shown to activate p53 using a variety of experimental systems (Ko and Prives 1996; Giaccia and Kastan 1998), the Ras-p19Arf pathway appears to be the major signal that operates during SCC development. This indicates that p53 activation is an intrinsic consequence of the oncogenic pathway that drives tumor growth, and is not due to other microenvironmental factors (e.g., those induced by hypoxia or due to lack of survival factors) or exogenous stimuli (e.g., DNA damage inducers). However, it remains possible that these other modes of p53 activation might predominate in other tumor types or in other circumstances. Despite the fact that both p19Arf and p53 were induced in papillomas, loss of p19Arf or p53 had opposite effects on early tumor growth. p19Arf deficiency resulted in increased tumor cell proliferation and tumor growth while p53-deficient mice had reduced tumor cell proliferation, tumor numbers, and tumor size. The observation that tumors harboring mutant Ras grew faster in the presence of p53 than in the absence of p53 differs from in vitro studies, in which ectopically expressed Ras induces p53-dependent growth arrest or senescence (Palmero et al. 1998; Zindy et al. 1998; Lin and Lowe 2001). These different outcomes are likely due to different experimental conditions. Ex vivo culture per se induces stress, which can further induce p53 and accelerate senescence (Lowe and Ruley 1993; Serrano et al. 1997; Sherr and DePinho 2000). Moreover, the levels of active Ras protein likely differ; our autochthonous tumor model begins with a single cell that has undergone a mutation at the endogenous Hras locus, and subsequent tumor growth occurs in the context of surrounding normal cells. Locally produced growth factors or TPA treatment may attenuate the effect of Ras on p53, effectively dampening the response. Thus, the absolute levels of both Ras and p53, as well as cell type involved and the local cellular ecology, may dictate the outcome. Greenhalgh al. (1996) also reported reduction in Ras-transgene-induced skin tumors in a p53-null background. We suggest that the acute effect of a constitutively active oncogene driving cellular proliferation, combined with lack of cell cycle checkpoints due to p53 deficiency, may generate excessive genetic instability, which may initially impair overall cellular fitness. This may be especially true at the early post-initiation stage where a small number of incipient tumor cells are competing with surrounding normal cells. This idea is consistent with the longstanding observation that p53-deficient mice (Donehower et al. 1992), and Li-Fraumeni patients who carry a germline p53 mutation (Vogelstein 1990), rarely develop multiple tumors, which would be expected if loss of p53 provided an early selective advantage. Also, in many human malignancies, mutations in p53 are infrequent in early premalignant lesions and much more common in late-stage disease, indicating a long latency between oncogene activation and loss of p53. Further genetic or epigenetic changes may be required for a cell to adapt to the combined effect of a dominant oncogene and loss of p53 to gain a fitness advantage. Loss of p19Arf appears to be one such change, as reduced tumor growth due to the absence of p53 was rescued by loss of p19Arf. Although p19Arf regulates p53, suppression of tumor growth per se by p19Arf does not appear to be mediated through p53. Other reports have suggested that p19Arf has tumor suppressor functions that are independent of p53. p19 Arf-null mice show a broader spectrum of spontaneous tumors compared to p53-null mice (Donehower et al. 1992; Kamijo et al. 1999). Mice lacking both p19 Arf and p53 showed a wider range of tumor types than animals lacking either gene alone, and many developed multiple primary tumors (Weber et al. 2000; Moore et al. 2003). Premalignant B-cells expressing oncogenic Eμ-myc and lacking both p19 Arf and p53 proliferated at a faster rate than cells lacking either p19 Arf or p53 alone (Weber et al. 2000). Indeed, both p19Arf and p53 are lost in a wide spectrum of human cancers, both familial and sporadic, at very high frequency (Ruas and Peters 1998; Vonlanthen et al. 1998). Microarray and GeneChip analysis of genes induced by a conditionally regulated p19Arf has identified members of the B-cell translocation gene family whose induction is independent of p53 (Kuo et al. 2003). Expression of these genes inhibits cell proliferation and induces cell cycle arrest. p19Arf can colocalize with the human replication protein A, suggesting a direct role for p19Arfin DNA synthesis (Yarbrough et al. 2002). p19Arf has also been shown to inhibit ribosomal RNA processing (Sugimoto et al. 2003) and to repress NF-κB transactivation (Rocha et al. 2003). Finally, p19Arf regulates vascular regression independent of p53, suggesting a role for p19Arf in angiogenesis. (McKeller et al. 2002). The functional relevance of these phenotypes for tumor suppression by p19Arf remains to be elucidated. Ras, p19Arf, p53, and Malignant Progression In the DMBA/TPA model, conversion of papillomas to carcinomas is a relatively rare event and can take up to 6–12 mo. Phenotypes associated with conversion include loss of basement membrane integrity, invasion of epithelial tumor cells into the dermis, loss of differentiation, and increased cellular atypia. Even more rarely, these carcinoma cells can metastasize, which involves additional phenotypic changes including, extravasation, migration, attachment, and establishment of tumor growth in an ectopic tissue. Although benign tumor growth differed between p19Arf- and p53-deficient mice, both mutant mice showed dramatically accelerated progression to malignancy and rapid metastasis. Thus, benign tumors lacking either p19Arf or p53 are at high risk for metastasis. In p19Arf-deficient mice, progression was similar with or without the presence of p53 and did not involve p53 LOH, indicating that loss of p19Arf decreased selection for p53 mutations during progression and that p19Arf acts through p53 at this stage. Schmitt et al. (1999) also reported increased lymphoma dissemination in Eμ-myc p53−/− mice relative to Eμ-myc mice alone. From a clinical perspective, then, the most relevant effect of the p19Arf-p53 pathway may be to inhibit malignant conversion and metastasis. Loss of p19Arf and/or p53 can increase progression and metastasis by several mechanisms. Deficiency in p19Arf or p53 could indirectly affect progression via increased genetic instability, increased generation of mutants, and accelerated tumor evolution. This view postulates the existence of a distinct class of genes whose dysfunction increases progression and metastasis. It also requires a series of clonal evolutionary steps to select for cells carrying mutations in these genes. Alternatively, loss of p19Arf or p53 can directly affect cellular phenotypes associated with progression through transcriptional regulation, or by relieving inhibition of Ras signaling. Both p19Arf- and p53-deficient papillomas displayed several characteristics consistent with early malignancy. Conversion of papillomas to carcinomas is first characterized by a flattening, endophytic transition. p19Arf- and p53-deficient papillomas had this morphology from the outset, suggesting an early propensity for malignant conversion. More detailed histological and immunochemical characterization showed that p53-deficient papillomas were more dysplastic and had aberrant expression of differentiation markers such as E-cadherin, P-cadherin, and Keratin-13 (Cano et al. 1996). E-cadherin is a critical component of cell–cell adhesion and its down regulation is strongly associated with malignant progression (Birchmeier et al. 1993; Perl et al. 1998). That these “high risk” p53-null papillomas exhibited these early malignant features argues for a more direct effect of p53 on cellular phenotypes associated with progression. In addition, there was a lack of correlation between papilloma size and propensity to progress. p53-null papillomas were fewer and smaller, yet these showed the most rapid progression. Finally, metastasis of skin tumors in both p19Arf- and p53-deficient mice was observed within a matter of days after papilloma to carcinoma conversion, again, irrespective of precursor tumor size. Collectively, these data are inconsistent with a model in which loss of p19Arf or p53 indirectly accelerates tumor progression by accelerating a series of independent genetic events, each followed by clonal selection, and instead favor a more direct model. We suggest that Ras may be a major driving force for multiple steps in tumor progression, with loss of p19Arf and p53 playing a facilitating role. In addition to the well-known effects of Ras on proliferation, consistent with an early role in neoplasia, Ras also contributes to a number of phenotypes that are involved in malignant progression, including metastasis. Ras induces cell motility, invasiveness (Lazarov et al. 2002; Dajee et al. 2003; Kim et al. 2003), epithelial to mesenchymal transition (Oft et al. 1996; Zondag et al. 2000), angiogenesis (Arbiser et al. 1997; Casanova et al. 2002), and metastasis (Pozzatti et al. 1986; Webb et al. 1998; Oft et al. 2002; Varghese et al. 2002). Ras activates a number of signaling cascades that drive these processes (Campbell et al. 1998). For example, Ras activation of the Raf-MAPK signaling cascade regulates the activities of nuclear transcription factors, including AP-1 (Campbell et al. 1998). In addition to regulating proliferation, AP-1 induces a motility/invasion program (Ozanne et al. 2000; Jochum et al. 2001; Young et al. 2003). Ras transgenic mice that lack Fos, a component of AP-1, develop benign skin tumors, but these fail to convert to carcinomas (Saez et al. 1995). MAPK activation also determines the ability of Ras-transformed fibroblasts to metastasize to the lung (Webb et al. 1998). Oncogenic Ras also works in concert with the Rho family of GTPases to regulate the intracellular actin cytoskeleton and promote cell motility and invasion leading to metastasis (Zohn et al. 1998). Sustained signaling by oncogenic Ras can permanently downregulate Rac activity and lead to an epithelial to mesenchymal transition. This transition is associated with changes in gene expression, loss of E-cadherin-mediated cell–cell adhesions, and increased invasiveness of tumor cells (Oft et al. 1996, 2002; Zondag et al. 2000). This allows the cell to become mobile, invade surrounding tissue, and establish metastatic sites. An additional link between Ras and tumor progression was demonstrated in a genome-wide survey of Ras transformation targets that identified a significant increase in expression of genes triggering invasion and metastasis, such as the laminin receptor, collagenase (Mmp-1), stromolysin (Mmp-3), and the Cd44 glycoprotein (Zuber et al. 2000). Ras also repressed genes involved in anti-invasive or anti-angiogenic activity, such as syndecan-2, tissue inhibitor of metalloproteases-2 (Timp-2), and thrombospondin-1. Further support for a continual involvement of Ras in tumor progression is indicated by the increase in copy number of mutant Ras alleles that is observed during tumor progression. In the DMBA/TPA skin tumor model, the mutant Ras allele is frequently duplicated in papillomas and amplified to multiple copies in carcinomas, especially in the most aggressive spindle cell tumors (Bremner and Balmain 1990; Buchmann et al. 1991). Increased expression of mutant Ras genes by gene amplification or other mechanisms is found in other tumor types (Schwab et al. 1983; Tanaka et al. 1986; Winter and Perucho 1986; Yokota et al. 1986) and has been shown to promote the growth of head and neck SCC and carcinoma of the cervix (Hoa et al. 2002; Soh et al. 2002). This indicates that there is a selective advantage to progressively increasing levels of Ras throughout tumor progression. Quantitative differences in Ras activity are known to differentially activate signaling pathways leading to different cellular outcomes (Shields et al. 2000). Loss of p53 may facilitate the increase in Ras levels, in that cells with inactivated p53 show greatly increased frequency of gene amplification (Yin et al. 1992). Thus, mutation in Ras is much more than the initiating event: it directly contributes to many of the phenotypes associated with malignant progression (Figure 7). As Ras induces both p19Arf and p53, and both are antagonistic to Ras, we suggest that an important consequence of p19Arf and p53 loss is that it permits increased Ras levels and signaling, fueling further tumor progression. In addition to counteracting Ras, p19Arf and p53 likely contribute to tumor suppression through additional pathways. For example, loss of p19Arf increases tumor growth, and loss of p53 confers resistance to apoptosis and loss of cell cycle checkpoints, leading to genetic instability. The observation that oncogene mutations are linked to tumor suppressor gene activation through mechanistic signaling pathways indicates that selective pressure in favor of tumor suppressor gene mutations originates from the initial oncogenic lesion and is thus intrinsic to the tumor. Figure 7 An Integrated Model of SCC Progression At the genetic level, treatment of mouse skin with DMBA induces mutations in Hras resulting in initiated cells that express constitutively active Ras protein (grey rectangles). TPA treatment is required for clonal expansion of these Hras mutant cells to form papillomas. Frequent duplication of the mutant Ras allele in papillomas indicates increased Ras signaling is favored. Mutation of p53, as well as additional Ras gene amplification, is seen in carcinomas, particularly in the most aggressive tumors (black rectangles). At the signaling level, mutant Ras upregulates p19Arf (Arf), which in turn activates p53. p19Arf, in turn, inhibits growth of Hras-driven tumors in a p53-independent manner. p19Arf, acting through p53, also inhibits malignant progression and metastasis. As Ras signals through p19Arf and p53, selection for subsequent mutations in p19 Arf or p53 is a direct consequence of the initial Ras mutation. In this model, Ras drives tumor progression through direct signaling effects and by dictating the evolution pathway of the tumor. Materials and Methods Mice p19Arf-deficient mice (C57BL/6 × 129SvJ) were provided by Martine Roussel and Charles Sherr (Kamijo et al. 1997). To increase their susceptibility to skin tumor development, p19 Arf−/− mice were backcrossed to the susceptible NIH/Ola strain (Harlan Olac, Oxfordshire, United Kingdom), and carcinogenesis studies were performed on the F3 littermates of this cross. 20 mice of each genotype, p19 Arf−/−, p19 Arf+/−, and p19 Arf+/+ were treated. The backs of 8-wk-old male and female mice were shaved and treated with a single application of DMBA (25 μg in 200 μl of acetone; Sigma, St. Louis, Missouri, United States) followed a week later by twice weekly applications of TPA (200 μl of 10−4 M solution in acetone) for 15 wk. The number and size of papillomas on each mouse were recorded every 2 wk. Mice were sacrificed if moribund or following detection of carcinomas. Tumors were frozen for DNA extraction and/or fixed in formalin to be processed and stained with hematoxylin/eosin (H&E) for histological examination. Mice deficient for p53 (Donehower et al. 1992) (F7 backcross to NIH) were crossed to p19 Arf-deficient (F4 backcross to NIH) mice to generate p19  Arf+/− p53+/− mice. These mice were intercrossed to generate all nine possible p19 Arf /p53 genotypes. Some 20–30 mice of each genotype were subjected to the same DMBA/TPA protocol and monitored as described above. Immunoblotting In order to remove abundant keratin present in papillomas and carcinomas, nuclear extracts were prepared as described (Schreiber et al. 1989) with modifications. Pieces of skin or tumor were ground in liquid nitrogen with a mortar and pestle, and the resulting powder was dissolved in buffer A and further homogenized for 1 min on ice (PowerGen 125, Fischer Scientific, Pittsburgh, Pennsylvania, United States). Buffers A and C both contained 1 mM DTT, 0.4 mg/ml Pefablock, 25 mg/ml Aprotinin, 10 mg/ml Pepstatin, and 10 mg/ml leupeptin (Roche, Alameda, California, Unites States) to inhibit proteases. Protein concentrations were standardized using the Bradford assay (Bio-Rad, Hercules, California, United States) and equal loading (50 μg/lane) was confirmed by Ponceau S staining of the nylon membrane after blotting. Western blot analysis was performed using specific antibodies against p19Arf (Novus Biologicals, Littleton, Colorado, United States) and p53 (Novocastra Laboratories, Newcastle-upon-Tyne, United Kingdom). Hras sequencing Genomic DNA was prepared from tumor and normal tissue by QIAamp DNA Mini Kit (Qiagen, Valencia, California, United States). A 400-bp PCR fragment containing exon 2 of Hras was amplified with standard PCR (3.0 mM MgCl2 andannealing for 2 min at 37 °C with 40 cycles), with 5′-GACTCCTACCGGAAACAGGT-3′ and 5′-CTGTACTGATGGATGTCCTC-3′ primers. We used the internal primer 5′-TGGTCATTGATGGGGAGACA-3′ to sequence exon 2, using PE Biosystems (Applied Biosystems, Foster City, Calfornia, United States) Dye-Terminator and Big-Dye cycle sequencing. Histological analysis Sections of normal skin, papillomas, carcinomas, and other organs were removed and fixed in 10% normal buffered formalin for 4 h. After fixation, tissues were processed and then embedded in paraffin. From the tissues, 4-μm sections were cut and stained for either p53 (CM5, Novocastra) or pan-keratin (AE1/AE3, Novocastra) using high-temperature antigen retrieval in 10 mM citrate buffer (pH 6), or for BrdU (Dako, Glostrup, Denmark) after treating with 2N HCl followed by 0.1% trypsin. After staining with the primary antibody, the sections were stained with a biotin-conjugated secondary (Vector Laboratories, Burlingame, California, United States) followed by StreptABComplex/HRP (Dako). Slides were developed with DAB/NiCl and counterstained with methyl green. Control sections with no primary antibody were run concurrently. Other sections were cut and stained using a standard H&E method. Proliferation index was determined by counting the number of BrdU-stained cells per 40× field. The apoptotic index was determined by counting the H&E slides for the number of apoptotic figures per 40× field. All counts were done on a Nikon (Tokyo, Japan) Labophot-2 microscope. Semiquantitative PCR analysis Genomic DNA was prepared from tumor tissue or normal kidney by QIAamp DNA Mini Kit (Qiagen). To measure LOH of the p19Arf wild-type allele in p19Arf+ /− tumors, wild-type and knockout alleles were amplified by PCR separately then combined for electrophoresis. Primers 5′-AGTACAGCAGCGGGAGCATGG-3′ (Arf1), 5′-TTGAGGAGGACCGTGAAGCCG-3′ (Arf2), and 5′-ACCACACTGCTCGACATTGGG-3′ (ArfN) were used to amplify wild-type (Arf1 and Arf2) and knockout alleles (Arf2 and ArfN) from 100 ng of genomic DNA using 68 °C for annealing and extension at 90 s for 30 cycles. Equal amounts of each PCR product were then combined for electrophoresis on a 2% TAE agarose gel. Wild-type and knockout alleles of p53 +/− tumors were amplified in a separate reaction as described (Timme and Thompson 1994) for 30 cycles. PCR products were electrophoresed on a 2% TAE agarose gel. Comparison gradients for p19Arf and p53 were established by combining wild-type and knockout genomic DNA in quantified ratios, then amplifying as described above. Statistical methods In order to assess the impact of p19Arf (or p19Arf /p53) genotypes on the development of papillomas, longitudinal profiles of papilloma counts were analyzed using the generalized estimating equation (GEE) approach (Zeger and Liang 1986). GEE is an established statistical approach to the regression analysis of longitudinal data. Our analysis used papilloma counts of each mouse measured every 2 wk as the outcome variable and incorporated within-mouse correlations of papilloma counts over time in making statistical inference. Using GEE, we estimated average differences of papilloma counts across genotypes after DMBA administration. Since the development of papillomas depends on the time since the DMBA administration and may differ by the sex of the mice, the effects of the weeks since the DMBA administration and sex were controlled for in the GEE analysis as covariates. A working correlation structure of the GEE analysis was specified as the first-order autoregressive structure over the time since the DMBA administration; however, GEE is robust against the misspecification of the correlation structure. In contrast to papillomas, the overall number of carcinomas developed during the experiment was relatively small. Thus, we analyzed differences by genotype in the probability of developing a carcinoma after DMBA administration. A logistic regression model (Clayton and Hills 2003) was used to assess the odds of developing a carcinoma during the experimental period and to compare it across p19Arf (or p19Arf /p53) genotypes. Estimates of relative odds were adjusted for sex effects. Fisher's exact test was used for comparing two proportions such as comparing LOH proportions between papillomas and carcinomas. All statistical tests were two-sided. We thank S. Lawrence Bailey for excellent technical assistance, Martine Roussel and Charles Sherr for generously providing p19Arf knockout mice, and Denny Liggett for assistance with histopathological evaluation of tumor samples. We also thank numerous colleagues at the Fred Hutchinson Cancer Research Center for critical reading of the manuscript. This work was supported by a National Institutes of Health T32 CA8046 Interdisciplinary Training Grant in Cancer Research to KSK-S and NCI R01 (CA099517) and NIEHS U01 (ES11045) grants to CJK. Conflicts of interest. The authors have declared that no conflicts of interest exist. Author contributions. KSK-S and CJK conceived and designed the experiments. KSK-S and KEG performed the experiments. KSK-S, YY, and CJK analyzed the data. KSK-S and KEG contributed reagents/materials/analysis tools. KSK-S and CJK wrote the paper. Academic Editor: Nicholas Hastie, Western General Hospital Citation: Kelly-Spratt KS, Gurley KE, Yasui Y, Kemp CJ (2004) p19Arf suppresses growth, progression, and metastasis of Hras-driven carcinomas through p53-dependent and -independent pathways. PLoS Biol 2(8): e242. 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H. A. Clowes Memorial Award Lecture Cancer Res 1994 54 1178 1189 8118803 Zeger SL Liang KY Longitudinal data analysis for discrete and continuous outcomes Biometrics 1986 42 121 130 3719049 Zhang Y Xiong Y Mutations in human ARF exon 2 disrupt its nucleolar localization and impair its ability to block nuclear export of MDM2 and p53 Mol Cell 1999 3 579 591 10360174 Zindy F Eischen CM Randle DH Kamijo T Cleveland JL Myc signaling via the ARF tumor suppressor regulates p53-dependent apoptosis and immortalization Genes Dev 1998 12 2424 2433 9694806 Zohn IM Campbell SL Khosravi-Far R Rossman KL Der CJ Rho family proteins and Ras transformation: The RHOad less traveled gets congested Oncogene 1998 17 1415 1438 9779988 Zondag GC Evers EE ten Klooster JP Janssen L van der Kammen RA Oncogenic Ras downregulates Rac activity, which leads to increased Rho activity and epithelial-mesenchymal transition J Cell Biol 2000 149 775 782 10811819 Zuber J Tchernitsa OI Hinzmann B Schmitz AC Grips M A genome-wide survey of RAS transformation targets Nature Genet 2000 24 144 152 10655059

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020243Research ArticleGenetics/Genomics/Gene TherapyImmunologyMus (Mouse)Spontaneous Autoimmunity in 129 and C57BL/6 Mice—Implications for Autoimmunity Described in Gene-Targeted Mice Gene-Targeted Mice and AutoimmunityBygrave Anne E 1 Rose Kirsten L 1 Cortes-Hernandez Josefina 1 Warren Joanna 1 Rigby Robert J 1 Cook H. Terence 2 Walport Mark J 1 ¤Vyse Timothy J 1 Botto Marina m.botto@imperial.ac.uk 1 1Rheumatology Section, Eric Bywaters CentreImperial College, London, United Kingdom2Department of Histopathology, Faculty of MedicineImperial College, LondonUnited Kingdom8 2004 17 8 2004 17 8 2004 2 8 e2431 1 2004 27 5 2004 Copyright: © 2004 Bygrave et al.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. Mouse Models of Human Autoimmune Diseases: Essential Tools That Require the Proper Controls Deconstructing Genetic Contributions to Autoimmunity in Mouse Models Systemic lupus erythematosus (SLE) is a multisystem autoimmune disorder in which complex genetic factors play an important role. Several strains of gene-targeted mice have been reported to develop SLE, implicating the null genes in the causation of disease. However, hybrid strains between 129 and C57BL/6 mice, widely used in the generation of gene-targeted mice, develop spontaneous autoimmunity. Furthermore, the genetic background markedly influences the autoimmune phenotype of SLE in gene-targeted mice. This suggests an important role in the expression of autoimmunity of as-yet-uncharacterised background genes originating from these parental mouse strains. Using genome-wide linkage analysis, we identified several susceptibility loci, derived from 129 and C57BL/6 mice, mapped in the lupus-prone hybrid (129 × C57BL/6) model. By creating a C57BL/6 congenic strain carrying a 129-derived Chromosome 1 segment, we found that this 129 interval was sufficient to mediate the loss of tolerance to nuclear antigens, which had previously been attributed to a disrupted gene. These results demonstrate important epistatic modifiers of autoimmunity in 129 and C57BL/6 mouse strains, widely used in gene targeting. These background gene influences may account for some, or even all, of the autoimmune traits described in some gene-targeted models of SLE. Several strains of gene-targeted mice develop systemic lupus erythematosus (SLE). Analysis of these strains demonstrates that the genetic background profoundly influences the development of autoimmunity ==== Body Introduction Systemic lupus erythematosus (SLE) is a chronic autoimmune disease characterised by the production of autoantibodies (auto-Abs) against a wide spectrum of self-antigens, mainly from subcellular compartments, especially the cell nucleus. Genetic predisposition is an important contributor to susceptibility to SLE in both humans and animals (Vyse and Todd 1996; Harley et al. 1998; Theofilopoulos and Kono 1999; Wakeland et al. 2001). Genes in multiple pathways participate in mediating disease pathogenesis, and epistatic interactions amongst these genes influence the expression of disease. In this context, both genetic linkage studies in spontaneous lupus-prone models and synthetic murine models of autoimmunity generated by targeted disruption of specific genes modulating the immune system have widely been used to investigate the complexity of SLE. The best-studied strains of mice that spontaneously develop a lupus-like pathology are the New Zealand Black/New Zealand White hybrid strain (NZB/WF1); the MRL/Mp lpr/lpr strain, which carries the lpr mutation of the FAS receptor gene; and the BXSB strain, which carries the Y chromosome autoimmune accelerator (Yaa) gene (Theofilopoulos and Dixon 1985). Extensive genetic mapping studies in all three strains have identified multiple intervals associated with disease susceptibility. Interestingly, the majority of the intervals detected are strain-specific, confirming the genetic complexity of the disease and indicating the presence of extensive heterogeneity in the genes contributing to the pathogenesis of the disease. However, some susceptibility loci have been mapped to similar chromosome locations in different strains, suggesting that at least some susceptibility may be shared amongst lupus-prone strains. Amongst these shared susceptibility loci, the most striking are loci on distal Chromosome 1, for which important contributing genes have been found in New Zealand and BXSB models (Theofilopoulos and Kono 1999; Wakeland et al. 2001). Although considerable efforts have been made to identify the genes responsible for the development of the disease, with the exception of the lpr mutation, none of the genetic contributions to disease in the three well-documented murine SLE strains have yet been fully resolved at the molecular or protein level. Thus, targeted genetic disruption of candidate genes encoding proteins of the immune system has been extensively used to examine their role in immune regulation. However, the most surprising result of this powerful approach has been the high frequency with which such mutations have been associated with an autoimmune phenotype. In this regard, it is of note that hybrid strains between 129 and C57BL/6 mice, widely used in the generation of gene-targeted mice, are spontaneously predisposed to development of humoral autoimmunity with low levels of glomerulonephritis (Obata et al. 1979; Botto et al. 1998; Bickerstaff et al. 1999; Santiago-Raber et al. 2001). Furthermore, the genetic background markedly influences the autoimmune phenotype in gene-targeted mice (Bolland and Ravetch 2000; Santiago-Raber et al. 2001; Mitchell et al. 2002). These observations led to the hypothesis that the autoimmune phenotype described in some gene-targeted mice might be due primarily to combinations of as-yet-uncharacterised background genes, originating from 129 and C57BL/6 mice strains, interacting or not with the mutated allele. To test this, we conducted a genome-wide scan analysis of two large cohorts of (129 × C57BL/6)F2 mice, one of which carried a mutation in the serum amyloid P component gene (Apcs). The Apcs-deficient mice (Apcs −/−) were chosen as an example of a gene-targeted strain previously reported to develop a lupus-like disease on the hybrid genetic background (129 × C57BL/6); autoimmunity in Apcs −/− mice persists even after backcrossing the mutated gene onto C57BL/6 (Bickerstaff et al. 1999). We chose this targeted gene in particular to study since the Apcs gene is located on Chromosome 1, approximately 94 cM from the centromere, within a region where several lupus-susceptibility loci, designated Sle1 (Morel et al. 2001), Nba2 (Drake et al. 1995; Vyse et al. 1997), and Bxs3 (Hogarth et al. 1998; Haywood et al. 2000), have been mapped in NZW, NZB, and BXSB lupus-prone strains, respectively. This region contains several genes, including those encoding FcγRII, the complement receptor CR1/2 (CD35/CD21), and the decay-accelerating factor CD55 (Prodeus et al. 1998; Bolland and Ravetch 2000; Miwa et al. 2002; Wu et al. 2002), which have each been implicated in the causation of SLE when inactivated by gene-targeting in 129 embryonic stem cells. Here we show that there are multiple genetic loci, derived from both 129 and C57BL/6 mice, contributing to autoimmunity. Furthermore, a 129-derived interval on distal Chromosome 1, when transferred onto the C57BL/6 genome, a combination commonly created by backcrossing onto C57BL/6 a gene that has been inactivated in 129 embryonic stem cells, was sufficient to cause humoral autoimmunity in its own right, irrespective of the presence of the mutated Apcs gene. These results demonstrate important epistatic interactions between genes from 129 and C57BL/6 genomes on the development of autoimmunity and illustrate the important effects of background genes in the analysis and interpretation of autoimmune phenotypes associated with targeted genetic disruptions. Results Disease Traits in (129 × C57BL/6)F2 and (129 × C57BL/6)F2.Apcs −/− Mice To investigate the genetic basis of the lupus-like disease observed in the (129 × C57BL/6) hybrid mice, we generated two large cohorts of (129 × C57BL/6)F2 animals, one carrying a mutation in the Apcs gene, and monitored them for 1 y under identical environmental conditions. Since female mice in the original reports showed a higher penetrance of disease, the present study was conducted only on female mice. The results of the phenotypic analysis at 1 y of age are summarised in Tables 1 and 2. As previously reported (Botto et al. 1998), the wild-type (129 × C57BL/6)F2 mice developed lupus traits with elevated levels of auto-Abs, starting from 6 mo of age (data not shown), and histological evidence of proliferative glomerulonephritis. In agreement with our previous observations (Bickerstaff et al. 1999), the titres of anti-nuclear Abs (ANAs) and anti-chromatin Ab were considerably greater in the (129 × C57BL/6)F2.Apcs −/− mice compared with the strain-matched controls. However, in contrast to our original findings, the levels of the other two disease serological markers analysed (anti-single-stranded DNA [ssDNA] and anti-double-stranded DNA [dsDNA] Abs) and the severity of the renal pathology were not different between the two experimental groups. In view of the possibility of an association between the fixed 129-derived segment flanking the mutated Apcs gene and the autoimmune traits observed, the genome-wide linkage analysis of the two experimental cohorts was carried out separately. Table 1 Spontaneous Auto-Abs in Apcs −/− and Wild-Type (129 × C57BL/6)F2 Female Mice Significant differences between Apcs −/− and wild-type controls by Mann–Whitney U test. The numbers tested for different phenotypes are not equal due to the limited amount of serum or death of the mice before the end of the experiment. NS, not significant Table 2 Histological Assessment of Kidney Sections in Apcs −/− and Wild-Type (129 × C57BL/6)F2 Female Mice The renal sections were scored on a 0–3 scale on the intensity and extent of the histopathological changes as described in Materials and Methods. The difference between the two experimental groups was not significant Mapping of Loci Predisposing to Lupus in the Hybrid Strain (129 × C57BL/6) Mice were genotyped with 143 microsatellite markers distributed throughout the autosomes such that 98% of the genes were within 20 cM of an informative marker. A summary of the genome-wide linkage analysis for each of the disease traits measured is shown in Table 3. The areas of linkage were defined according to the parental origin, 129 or C57BL/6. Only linkages identified in both experimental groups are reported in Table 3, with the exception of the Chromosome 1 distal segment, where the linkage analysis could not be applied to the (129 × C57BL/6)F2.Apcs −/− mice as this region was of fixed 129 origin. Chromosomes where linkages were present only in one of the two cohorts are shown in Figures 1–3. Figure 1 Linkage of Chromosome 2 with ANA and Anti-Chromatin Abs in (129 × C57BL/6)F2.Apcs−/− Mice These associations were not detected in (129 × C57BL/6)F2 animals. Centimorgan positions were deduced by interval mapping, anchoring marker locations to data from http://www.informatics.jax.org. Dotted lines and the dashed line indicate the threshold over which linkages were considered suggestive or significant, respectively, as defined in Materials and Methods. Figure 3 Linkage of Chromosome 4 with Anti-dsDNA Abs The estimated peak in (129 × C57BL/6)F2 mice was at position 51.3 cM, whilst in the (129 × C57BL/6)F2.Apcs−/−animals it was was at position 71 cM, indicating that most likely these were two independent loci. Centimorgan positions were deduced by interval mapping, anchoring marker locations to data from http://www.informatics.jax.org. Dotted lines the indicate threshold over which linkage was considered suggestive, as defined in Materials and Methods. Table 3 Summary of Genome-Wide Linkage Analysis in Apcs −/− and Wild-Type (129 × C57BL/6)F2 Female Mice a Suggestive linkage b Significant linkage c Highly significant linkage as defined in the material and method section Chr, Chromosome; Est. Peak, Estimated Peak; LOD, logarithm of odds; N/A, not applicable Chromosomes where linkages were not present in both experimental groups are not illustrated. See Materials and Methods for details. The oligonucleotide sequences and approximate positions of the microsatellite markers used were taken from the Mouse Genome Database, Mouse Genome Informatics, Jackson Laboratory, Bar Harbor, Maine, United States (http://www.informatics.jax.org) The quantitative trait linkage (QTL) analysis identified several intervals on Chromosome 1 with linkage to disease serological markers, and these regions were all derived from the 129 mouse strain (see Table 3; Figures 4 and 5). Interestingly, whilst ANA and anti-chromatin Ab levels showed suggestive or significant linkages only to the telomeric region of Chromosome 1, with an estimated peak occurring at a position approximately 90 cM near the Apcs gene, anti-dsDNA or anti-ssDNA Ab production was also linked to other segments on Chromosome 1, indicating a more complex genetic contribution from the 129 mouse strain. Figure 4 Interval Mapping Scans Showing QTL on Chromosome 1 with Anti-dsDNA and Anti-ssDNA Abs Centimorgan positions were deduced by interval mapping, anchoring marker locations to data from http://www.informatics.jax.org. Dotted lines indicate the threshold over which linkage was considered suggestive, dashed lines indicate the threshold over which linkage was considered significant, and dotted/dashed lines indicate highly significant linkage, as defined in Materials and Methods. See Table 3 for additional details. Figure 5 Interval Mapping Scans Showing QTL on Chromosome 1 with ANA and Anti-Chromatin Abs Centimorgan positions were deduced by interval mapping, anchoring marker locations to data from http://www.informatics.jax.org. Dotted lines indicate the threshold over which linkage was considered suggestive, and dashed lines indicate the threshold over which linkage was considered significant, as defined in Materials and Methods. See Table 3 for additional details. Guided by these observations, we investigated whether the increased levels of ANA and anti-chromatin Ab observed in the Apcs −/− mice were caused by a gene(s) within the fixed 129 region surrounding the mutated Apcs gene, rather than caused by the mutated Apcs gene itself. We compared the levels of these auto-Abs between all (129 × C57BL/6)F2.Apcs −/− mice and a group of 33 wild-type mice that were selected for being homozygous 129 in the region of Chromosome 1 between microsatellites D1Mit105 and D1Mit 223 (80–106 cM) (Figure 6A–6D). In contrast to the results reported in Table 1, this comparison showed no significant differences between the two experimental groups. This result demonstrates that, most likely, the 129-derived region and not the lack of Apcs was mediating the production of ANA and anti-chromatin Ab. Consistent with this explanation, we found that the 129 mice have significantly higher levels of Apcs in circulation compared with the C57BL/6 mice (median, 83 mg/l; range, 25–208; n = 16 versus median, 5 mg/l; range, 4–9; n = 10, respectively; p < 0.0001). The C57BL/6 strain has previously been reported to be one of the murine strains defined as low Apcs producers (Pepys et al. 1979; Baltz et al. 1980). In addition, sequence analysis of the entire Apcs coding region in both strains failed to identify any coding sequence polymorphisms in the Apcs gene (data not shown), indicating that a structural variant of the protein is unlikely to be the explanation for our findings. This is consistent with a previous report by Drake et al. (1996) that showed no Apcs coding sequence differences amongst several autoimmune and nonautoimmune murine strains. Figure 6 Auto-Ab Profiles (A) ANA titres in the (129 × C57BL/6)F2.Apcs −/− mice and (129 × C57BL/6)F2 at 1 y of age. A small circle represents one mouse; a large circle, a variable number of animals, as indicated in parentheses. Serum samples were titrated to endpoint. (B) ANA titres in the (129 × C57BL/6)F2.Apcs −/− mice and a selected number of wild-type (129 × C57BL/6)F2 animals carrying the Chromosome 1 region between D1Mit105 and D1Mit223 (80–106 cM) of 129 origin. The symbols are as in (A). (C and D) Anti-chromatin Ab levels expressed in AEUs related to a standard positive sample, which was assigned a value of 100 AEU. The comparison is between the same groups of mice as in (A) and (B), respectively. The symbols are as in (A). In addition to the 129-derived segments, in both cohorts the C57BL/6 strain contributed to the autoimmune traits with one major susceptibility locus on Chromosome 3. A genomic region between D3Mit40 and D3Mit13, with an estimated peak at position approximately 51 cM, showed a significant linkage to ANA production and weaker linkages to anti-ssDNA and anti-chromatin production (see Table 3; Figure 7). The high frequency of autoimmune phenotype in the (129 × C57BL/6) hybrid genetic background and its absence in either of the inbred parental strains imply that there are essential interactions between 129- and C57BL/6-derived alleles for the expression of autoimmunity. We investigated further the effects of genes from the C57BL/6 background by repeating the linkage analysis in (129 × C57BL/6)F2 mice, whilst controlling for the very strong 129 effect on distal Chromosome 1, as previously described (Zeng 1994). The results of this analysis showed that the statistical support for the linkage of the C57BL/6 locus on Chromosome 3 for ANA increased from logarithm of odds (LOD) 5.4 to LOD 6.4. Figure 7 Interval Mapping Scans Showing QTL on Chromosome 3 with ANA, Anti-Chromatin, and Anti-ssDNA Abs See Table 3 for additional details. Centimorgan positions were deduced by interval mapping, anchoring marker locations to data from http://www.informatics.jax.org. Dotted lines indicate the threshold over which linkage was considered suggestive, the dashed line indicate the threshold over which linkage was considered significant, and dotted/dashed lines indicate highly significant linkage, as defined in Materials and Methods. In contrast to these strong associations with disease serological markers, the QTL analysis identified only two potential linkages to glomerulonephritis: one in the wild-type mice on Chromosome 7 across a 10 cM region between D7Mit246 (15 cM) and D7Mit145 (26.5 cM) of 129 origin (LOD 2.86, p = 0.0013), and one on Chromosome 17 between D17Mit100 (11.7 cM) and D17Mit216 (29.4 cM) from the C57BL/6 strain (LOD 1.3, p = 0.049 and LOD 1.67, p = 0.021 in the wild-type and Apcs −/− mice, respectively). Histological evidence of glomerulonephritis was only found in approximately 20% of the mice in each cohort, which reduces the power of the QTL analysis for this disease trait. Production of a C57BL/6.129 Chromosome 1 Congenic Line and Its Phenotypic Analysis We generated a C57BL/6 congenic line carrying the telomeric region of Chromosome 1 from the 129 mouse strain, in order to dissect the complex polygenic disease phenotype of the (C57BL/6 × 129/Sv)F2 hybrid strain into its individual genetic components. The 129 interval was backcrossed seven times onto C57BL/6, and at each generation the presence or absence of the Chromosome 1 interval was determined with several microsatellite markers. Each backcrossed generation was screened with more than three markers per chromosome to facilitate the removal of unselected 129 genomic regions. At the end of the backcrossing, the 129-derived Chromosome 1 interval in the congenic mice extended from microsatellite marker D1Mit105 to D1Mit223 (80–106 cM), which encompasses the most important 129 interval identified by the linkage studies in the (C57BL/6 × 129/Sv)F2 mice. Female Chromosome 1 congenic mice (C57BL/6.129[D1Mit105–223]), together with sex-matched Apcs −/− mice backcrossed onto C57BL/6 for ten generations (C57BL/6.Apcs −/−) and C57BL/6 controls, were monitored for the presence of lupus. In the C57BL/6.Apcs −/− mice, the 129 genome around the Apcs locus was mapped as a stretch of approximately 17 cM, positioned from 87.9 cM (D1Mit15) to 105 cM (D1Mit17). Thus, the congenic line carried a similar 129 region (80–106 cM) to the one present in the C57BL/6.Apcs −/− mice (87.9–105 cM). At 1 y of age, all animals were sacrificed, the auto-Abs assessed, and the renal histology examined. The results of this analysis are shown in Figure 8. As previously reported (Bickerstaff et al. 1999), the levels of auto-Abs were markedly increased in the C57BL/6.Apcs −/− compared to the wild-type C57BL/6 controls. However, the C57BL/6.129(D1Mit105–223) animals also expressed high levels of auto-Abs, and these titres were not different from those detected in the matched congenic mice containing a null mutation of the Apcs gene. These results clearly demonstrated that epistatic interactions between 129 loci on Chromosome 1 and C57BL/6 genes were sufficient to mediate the loss of tolerance to nuclear autoantigens. However, in contrast to the serological data, the histological assessment of the kidneys showed evidence of markedly increased glomerulonephritis in the C57BL/6.Apcs −/− compared to both control groups (Figure 9), suggesting that the lack of Apcs, when combined with other C57BL/6 susceptibility alleles, can induce the development of severe renal damage. Figure 8 Auto-Ab Profiles (A) ANA titres in C57BL/6 mice, C57BL/6.Apcs −/− mice, and C57BL/6.129(D1Mit105–223) congenic mice at 1 y of age. Small symbols represent one mouse; large symbols, a variable number of animals as indicated in parentheses. Serum sample were titrated to endpoint. (B and C) Anti-ssDNA (B) and anti-chromatin (C) Ab levels in the same cohorts of mice as in (A). The Ab levels are expressed in AEUs related to a standard positive sample, which was assigned a value of 100 AEU. (D) Anti-dsDNA Ab levels. Serum samples were screened at 1:20. Samples that were positive were titrated to endpoint. The symbols are as in (A). Figure 9 Renal Histological Assessment C57BL/6 mice, C57BL/6.Apcs −/− mice, and C57BL/6.129(D1Mit105–223) congenic mice were sacrificed at 1 y of age to obtain age-matched autopsy specimens. Bouin's fixed kidney sections were scored blinded for glomerulonephritis. Glomerulonephritis was graded on a 0–3 scale (see Materials and Methods for details). Discussion There is accumulating evidence that background genes may influence the expression of autoimmunity in gene-targeted mice. Here we report what is to our knowledge the first systematic study that has examined this in the 129 and C57BL/6 mouse strains, widely used for gene targeting. Our results demonstrate interacting loci between 129 and C57BL/6 mice that can cause the expression of a powerful autoimmune phenotype in these animals, in the absence of any gene-targeted mutations. We also developed a congenic mouse strain bearing a portion of 129 Chromosome 1 on a C57BL/6 background and showed that this wild-type congenic line expressed striking anti-nuclear autoimmunity. By comparing this Chromosome 1 congenic strain with matched congenic mice lacking the Apcs gene, we demonstrated that serum amyloid P component deficiency influences the severity of glomerulonephritis, but is not the prime mover in the induction of anti-nuclear autoimmunity, contrary to our own original interpretation of our data (Bickerstaff et al. 1999). The same consideration applies to other genes located in the same Chromosome 1 region that have been implicated in the development of SLE when inactivated by gene-targeting in 129 embryonic stem cells and then backcrossed onto a pure genetic background (Bolland and Ravetch 2000; Miwa et al. 2002; Wu et al. 2002). For each, there has to be a question as to whether the anti-nuclear autoimmunity is due to the gene-targeted mutant gene or to the normal 129 genes expressed in the same region as the targeted gene. The influence of background genes on the development of spontaneous autoimmune disease is well known, especially with respect to the lpr and Yaa disease-susceptibility genes. In MRL/Mp mice, the presence of the lpr gene accelerates the development of high level and broad-spectrum auto-Ab production and lethal glomerulonephritis, in addition to marked lymphoproliferative disease. In contrast, homozygosity of the lpr gene in other strains such as C57BL/6, AKR, LG/J, and C3H leads only to auto-Ab production (Izui et al. 1984). Similarly, the Y-chromosome-linked Yaa gene in BXSB and MRL/Mp males enhances the rapid development of auto-Abs and glomerulonephritis (Izui et al. 1988; Merino et al. 1989). However, in the C57BL/6 background, the Yaa gene does not lead to an autoimmune phenotype (Izui et al. 1988). Not surprisingly, important effects of the genetic background on the expression of autoimmunity have also been reported in gene-targeted mice (Bolland and Ravetch 2000; Santiago-Raber et al. 2001; Mitchell et al. 2002). Thus, SLE exists as a complex-trait disorder in which specific combinations of susceptibility alleles are required for the expression of the full phenotype. Through the use of microsatellite marker maps, the identification of murine SLE susceptibility intervals in experimental crosses has been made possible. These mapping studies have shown that the disease expression in relation to the inheritance of the different alleles followed a threshold liability pattern in which a positive phenotype depended upon the presence of multiple discrete susceptibility loci with no single locus being a prerequisite factor. We have employed the same approach to analyse the genetic basis of disease inheritance in the (129 × C57BL/6) hybrid strain, the most common genetic background in gene-targeted mice. Although spontaneous autoimmunity has not been documented in either of the pure 129 or C57BL/6 strains, a spontaneous lupus-like phenotype has been described in (129 × C57BL/6) hybrid strains (Obata et al. 1979; Botto et al. 1998; Bickerstaff et al. 1999; Santiago-Raber et al. 2001), suggesting that the predisposition in these hybrid mice may arise as a result of the interaction between specific combinations of alleles inherited from both the 129 and C57BL/6 parental strains. This was confirmed by the mapping study reported here. We showed that there are multiple genetic loci contributing to the disease and these are derived from both 129 and C57BL/6 mice. We demonstrated that a 129-derived segment of Chromosome 1 was strongly linked to the expression of auto-Abs. This region is probably capable of causing the initiation of a humoral autoimmune response to nuclear antigens; however, this response does not occur in the absence of C57BL/6 genes. In support of this, we identified a C57BL/6 segment on Chromosome 3, which may interact with the 129 genes on Chromosome 1 to mediate the loss of tolerance. Interestingly, although the C57BL/6 SLE-susceptibility region on Chromosome 3 is novel, disease-modifying alleles derived from C57BL/10 and C57BL/6 strains have been mapped to a portion of Chromosome 3 close to the region identified in this study (Morel et al. 1999; Haywood et al. 2000). Furthermore, the region on Chromosome 7 associated with the development of lupus nephritis has been linked to the same trait in other murine models of SLE (Santiago et al. 1998; Morel et al. 1999; Xie et al. 2002), suggesting the possibility of shared susceptibility loci. Taken together our results suggest a complex genetic contribution from the (129 × C57BL/6) hybrid background genome, with both enhancing as well as inhibitory loci from the 129 mouse, in addition to genes promoting autoimmunity from the C57BL/6 mice. The impact that these interacting loci may have on the lupus-like disease present in several gene-targeted animals was further assessed by comparing Apcs −/− mice with Chromosome 1 genetically matched controls. In the context of SLE susceptibility, one of the most consistently mapped non-MHC regions of the mouse genome is the telomeric Chromosome 1 segment, where several disease loci, designated Sle1 (Morel et al. 2001), Nba2 (Drake et al. 1995; Rozzo et al. 1996; Vyse et al. 1997), and Bxs3 (Hogarth et al. 1998), have been mapped in lupus-prone strains. Moreover, this region of mouse Chromosome 1 is orthologous to a region on human Chromosome 1q22–1q25, which has also been linked with human SLE (Moser et al. 1998). The Apcs gene is one of the candidate genes known to lie within this region. The human serum amyloid P component binds avidly to DNA, chromatin, and apoptotic cells in physiological conditions in vitro (Pepys 1974; Pepys and Butler 1987; Butler et al. 1990) and also to exposed chromatin and apoptotic cells in vivo (Hintner et al. 1988; Breathnach et al. 1989; Familian et al. 2001). We have previously reported that (129 × C57BL/6).Apcs −/− mice spontaneously produce a wide range of ANAs and develop significant immune complex glomerulonephritis (Bickerstaff et al. 1999). On the basis of these observations, it was postulated that Apcs, by altering the clearance of chromatin, contributes to the pathogenesis of SLE. However, in this study we found that only ANA and anti-chromatin Ab levels were significantly increased in the (129 × C57BL/6)F2.Apcs −/− mice. A possible explanation for this discrepancy may lie in the fact that the Apcs −/− mice analysed in the original study were generated from a limited number of founders and that this may have caused a nonrandom inheritance of the loci from the parental strains. Furthermore, the whole-genome analysis identified the 129 region surrounding the Apcs gene as the main locus contributing to the development of ANA and anti-chromatin Ab. In agreement with this, when we carried out a selective comparison between the (129 × C57BL/6)F2.Apcs −/− mice and Chromosome 1 genetically matched controls, we failed to detect any significant difference in the levels of these two auto-Abs. These findings, taken together, indicated that the phenotype associated with Apcs deficiency was caused by the presence of unaltered 129 genes from the telomeric region of Chromosome 1 operating in the C57BL/6 genomic background. Strong supportive evidence for this was provided by the analysis of the C57BL/6 mice congenic for this 129 region. The generation and analysis of congenic strains have successfully been used to dissect the contribution of individual susceptibility alleles to a multigenic trait such as SLE. We adopted the same strategy to investigate the relative contribution of the 129 Chromosome 1 segment and the Apcs gene to each disease trait. Using this approach, we demonstrated that the 129 interval on distal Chromosome 1, when transferred onto the C57BL/6 genome, a combination commonly created by backcrossing onto C57BL/6 a mutated gene located in that chromosomal region, was sufficient to mediate the production of auto-Abs. In this context, it is of note that several strains of mice with targeted mutations of genes encoded in this region have been reported to express a lupus-like illness, including mice lacking FcγRIIB (Bolland and Ravetch 2000), complement receptors (CR1/2) (Prodeus et al. 1998; Wu et al. 2002), and decay-accelerating factor (CD55) (Miwa et al. 2002). In each case, the autoimmune phenotype was described in mice in which the null mutation was generated in 129 embryonic stem cells and then backcrossed to the C57BL/6 or another genetic background. Thus, in view of our findings, one may postulate that in each of these murine models of SLE, the effects of the targeted null gene were irrelevant. Similar conclusions may apply to other gene-targeted animals carrying mutations of genes mapped in the 129-derived susceptibility allele on Chromosome 7 (O'Keefe et al. 1996, 1999). The expression of anti-nuclear autoimmunity was identical comparing the congenic with the Apcs−/− mice. The only difference in phenotype between these mice was in the expression of glomerulonephritis, which was more pronounced in the Apcs−/− mice compared with the congenic mice. Although these findings demonstrate that Apcs is not implicated in the processing of autoantigens, as it had previously been suggested, they indicate that Apcs might still play an important protective role in lupus nephritis. In support of this, the expression of the human C-reactive protein, an acute-phase protein closely related to Apcs, has been shown to delay the onset and severity of lupus nephritis in the NZB/W strain by preventing the deposition of immune complexes in the renal cortex (Szalai et al. 2003). Consistent with this, a polymorphism associated with reduced basal level of C-reactive protein has been reported to be linked to SLE in humans (Russell et al. 2004). However, as the congenic mice and the Apcs−/− mice carried similar but not identical 129 regions on Chromosome 1, an alternative explanation for our findings may still lay in the numerous and complex synergistic and counteractive interactions between 129 and C57BL/6 genes involved in self-tolerance and end organ damage. Thus, whilst the lack of lupus nephritis in the congenic mice is consistent with the need for multiple susceptibility genes for the full expression of lupus, further studies will be required to fully elucidate the role of Apcs in the pathogenesis of renal damage. In summary, our findings demonstrate the impact of epistatic interactions between 129 and C57BL/6 genomes on the development of SLE and illustrate how these background gene effects may lead to incorrect interpretations when analysing the autoimmune phenotype of specific genetic disruptions. Materials and Methods Mice. All the mice were females. Wild-type C57BL/6 and 129/Sv (129S6, according to the revised nomenclature) were bred and maintained in the animal care facility at Imperial College, London, United Kingdom. (129 × C57BL/6)F1 mice were generated by intercrossing the two wild-type strains and (129 × C57BL/6)F2 mice by interbreeding the (129 × C57BL/6)F1 mice. The Apcs −/−mice were generated as previously reported (Botto et al. 1997), and the (129 × C57BL/6)F2.Apcs −/− mice were generated by intercrossing Apcs −/− mice on the 129 genetic background with Apcs −/− animals backcrossed onto C57BL/6 for ten generations. A total of 141 (129 × C57BL/6)F2 and 158 (129 × C57BL/6)F2.Apcs −/− female mice were produced and monitored for 1 y. Wild-type congenic C57BL/6.129(D1Mit105–223) mice were generated by backcrossing the 129 interval between microsatellites D1Mit105 and D1Mit223 (80 cM to 106 cM) onto the C57BL/6 strain. Inherited 129 regions were mapped with microsatellite markers polymorphic between 129 and C57BL/6 mice (see below). After seven generations of backcrossing, siblings were intercrossed to generate C57BL/6.129(D1Mit105–223) congenic mice homozygous for the 129 Chromosome 1 interval. Inside 129 markers at positions 81.6 cM (D1Mit159) and 105 cM (D1Mit17), respectively, and an outside C57BL/6 marker at position 74.3cM (D1Mit159) were used to further define the interval. In the C57BL/6.Apcs −/− mice (backcrossed onto C57BL/6 for ten generations), the 129 genome around the Apcs locus was mapped as a segment from 87.9 cM (D1Mit15) to 105 cM (D1Mit17). In this analysis, the inside 129 markers were at positions 93 cM (D1Mit36) and 99.7 cM (D1Mit115) and the outside C57BL/6 markers at positions 81.6 cM (D1Mit159) and 106 cM (D1Mit223). Along with 28 C57BL/6.Apcs −/−mice and 30 C57BL/6 wild-type animals, 26 C57BL/6.129(D1Mit105–223) female mice −/−were followed up to 1 y of age. Animals were maintained in specific pathogen-free conditions. All animal procedures were in accordance with institutional guidelines. Serological analyses. Sera, collected at 6 and 12 mo of age, were assayed for the presence of auto-Abs. Levels of IgG ANA were sought by indirect immunofluorescence using Hep-2 cells, and anti-dsDNA Abs were detected by indirect immunofluorescence on Crithidia luciliae as previously described (Mitchell et al. 2002). Serum samples were screened at a 1:80 (ANA) or 1:20 (anti-dsDNA) dilution and the positive samples titrated to endpoint. Abs to ssDNA and anti-chromatin were measured by ELISA, as previously described (Mitchell et al. 2002). Samples were screened at a 1:100 dilution, and the results were expressed in arbitrary ELISA units (AEUs) relative to a standard positive sample (derived from an MRL/Mp.lpr/lpr mouse), which was assigned a value of 100. For interplate comparison, serial dilutions of a positive control serum sample were included on each plate. Apcs levels were assessed by ELISA using sheep anti-mouse Apcs and rabbit anti-mouse Apcs Abs (Calbiochem, Nottigham, United Kingdom). Samples were screened at a 1:3,000 dilution, and the results were expressed in milligrams per liters, referring to a standard curve derived from an acute-phase serum with a known concentration of Apcs (Calbiochem). Apcs −/− mouse serum was included as a negative control. Histological analysis. All the mice, except the few that died before the end of the experiment, were sacrificed at 1 y of age, and kidney portions were fixed in Bouin's solution and paraffin embedded, and sections were stained with periodic acid–Schiff reagent. Glomerular histology was graded in a blinded fashion as follows: grade 0, normal; grade 1, hypercellularity involving greater than 50% of the glomerular tuft in 25%–50% of glomeruli; grade 2, hypercellularity involving greater than 50% of the glomerular tuft in 50%–75% of glomeruli; grade 3, glomerular hypercellularity in greater than 75% of glomeruli or crescents in greater than 25% of glomeruli. Statistical analysis Non-parametric data are expressed as median with range of values in parentheses. All statistics were calculated using GraphPad PrismTM version 3.0 for Windows (GraphPad Software, San Diego, California, United States). Non-parametric tests were applied throughout, with differences being considered significant for p values < 0.05. The Mann–Whitney test was used for comparison of two groups, whilst for analysis of three groups the Kruskal–Wallis test with Dunn's multiple comparison test was used. Genotypic analysis Genotyping was carried out by PCR of genomic DNA using 143 polymorphic markers (list available on request) distributed throughout all 19 autosomes. PCRs were performed using standard reagents containing 1.5 mM MgCl2 and 0.4 μM primers. Microsatellite markers were screened for size polymorphisms between 129 and C57BL/6 mice. Only primers with differences detectable on ethidium bromide-stained agarose gels or on SDS-polyacrylamide gels were used. Linkage analysis The QTL program MAPMANAGER.QTL (ftp://mcbio.med.buffalo.edu/pub/MapMgr/) was used, and the two experimental groups were examined independently. Only data from mice at 12 mo of age were analysed. Log transformations of auto-Abs levels resulted in more normalised distribution and were used in QTL mapping. LOD thresholds for suggestive and significant linkages were determined by using a cohort- and trait-specific permutation test (1,000 permutations). The average threshold for suggestive, significant, and highly significant linkages were LOD ≥ 2.1 (p ≤ 7.8 × 10−3), LOD ≥ 3.6 (p ≤ 2.4 × 10−4), and LOD ≥ 5 (p ≤ 1 × 10−5), respectively (Manly and Olson 1999). Supporting Information Accession Numbers The LocusLink (http://www.ncbi.nlm.nih.gov/LocusLink/) ID numbers for the genes and gene products discussed in this paper are Apcs (LocusLink ID 20219), CD35/CD21 (LocusLink ID 12902), CD55 (LocusLink ID 13136), the FAS receptor gene (LocusLink ID 14102), and FcγRII (LocusLink ID 14130). Figure 2 Linkage of Chromosome 8 with Anti-Chromatin and Anti-dsDNA Abs in (129 × C57BL/6)F2 Mice These linkages were not detected in (129 × C57BL/6)F2.Apcs−/− animals. Centimorgan positions were deduced by interval mapping, anchoring marker locations to data from http://www.informatics.jax.org. Dotted lines indicate the threshold over which linkage was considered suggestive, as defined in Materials and Methods. We are grateful to M. Lewis for the processing of the samples for histology and to F. Reid and D. Mitchell for their help. We thank all of the staff in the animal facility for their technical assistance. This work was supported by the Wellcome Trust (grant number 061438). JCH was a recipient of a fellowship from the National Institute of Health, Spain (BEFI 99/9212). Conflicts of interest. The authors have declared that no conflicts of interest exist. Author contributions. MJW, TJV, and MB conceived and designed the experiments. AEB, KLR, JW, JC-H, and RJR performed the experiments. AEB, KLR, RJR, and HTC analyzed the data. MB wrote the paper. Academic Editor: David Nemazee, Scripps Research Institute ¤ Current address: The Wellcome Trust, London, United Kingdom Citation: Bygrave AE, Rose KL, Cortes-Hernandez J, Warren J, Rigby RJ, et al. (2004) Spontaneous autoimmunity in 129 and C57BL/6 mice—Implications for autoimmunity described in gene-targeted mice. PLoS Biol 2(8): e243. Abbreviations Abantibody ANAanti-nuclear antibody AEUarbitrary ELISA unit Apcs−/−Apcs-deficient mice Apcsserum amyloid P component gene dsDNAdouble-stranded DNA LODlogarithm of odds QTLquantitative trait linkage SLEsystemic lupus erythematosus ssDNAanti-single-stranded DNA ==== Refs References Baltz ML Gomer K Davies AJ Evans DJ Klaus GG Differences in the acute phase responses of serum amyloid P-component (SAP) and C3 to injections of casein or bovine serum albumin in amyloid-susceptible and -resistant mouse strains Clin Exp Immunol 1980 39 355 360 7389204 Bickerstaff MC Botto M Hutchinson WL Herbert J Tennent GA Serum amyloid P component controls chromatin degradation and prevents antinuclear autoimmunity Nat Med 1999 5 694 697 10371509 Bolland S Ravetch JV Spontaneous autoimmune disease in FcγRIIB-deficient mice results from strain-specific epistasis Immunity 2000 13 277 285 10981970 Botto M Hawkins PN Bickerstaff MC Herbert J Bygrave AE Amyloid deposition is delayed in mice with targeted deletion of the serum amyloid P component gene Nat Med 1997 3 855 859 9256275 Botto M Dell'Agnola C Bygrave AE Thompson EM Cook HT Homozygous C1q deficiency causes glomerulonephritis associated with multiple apoptotic bodies Nat Genet 1998 19 56 59 9590289 Breathnach SM Kofler H Sepp N Ashworth J Woodrow D Serum amyloid P component binds to cell nuclei in vitro and to in vivo deposits of extracellular chromatin in systemic lupus erythematosus J Exp Med 1989 170 1433 1438 2794863 Butler PJ Tennent GA Pepys MB Pentraxin–chromatin interactions: Serum amyloid P component specifically displaces H1-type histones and solubilizes native long chromatin J Exp Med 1990 172 13 18 2358775 Drake CG Rozzo SJ Hirschfeld HF Smarnworawong NP Palmer E Analysis of the New Zealand Black contribution to lupus-like renal disease: Multiple genes that operate in a threshold manner J Immunol 1995 154 2441 2447 7868910 Drake CG Rozzo SJ Vyse TJ Kotzin BL Absence of coding sequence polymorphism in the serum amyloid P component gene (Sap) in autoimmune New Zealand black mice Mamm Genome 1996 7 466 467 8662234 Familian A Zwart B Huisman HG Rensink I Roem D Chromatin-independent binding of serum amyloid P component to apoptotic cells J Immunol 2001 167 647 654 11441067 Harley JB Moser KL Gaffney PM Behrens TW The genetics of human systemic lupus erythematosus Curr Opin Immunol 1998 10 690 696 9914226 Haywood ME Hogarth MB Slingsby JH Rose SJ Allen PJ Identification of intervals on chromosomes 1, 3, and 13 linked to the development of lupus in BXSB mice Arthritis Rheum 2000 43 349 355 10693874 Hintner H Booker J Ashworth J Aubock J Pepys MB Amyloid P component binds to keratin bodies in human skin and to isolated keratin filament aggregates in vitro J Invest Dermatol 1988 91 22 28 2455001 Hogarth MB Slingsby JH Allen PJ Thompson EM Chandler P Multiple lupus susceptibility loci map to chromosome 1 in BXSB mice J Immunol 1998 161 2753 2761 9743333 Izui S Kelley VE Masuda K Yoshida H Roths JB Induction of various autoantibodies by mutant gene lpr in several strains of mice J Immunol 1984 133 227 233 6609979 Izui S Higaki M Morrow D Merino R The Y chromosome from autoimmune BXSB/MpJ mice induces a lupus-like syndrome in (NZW × C57BL/6)F1 male mice, but not in C57BL/6 male mice Eur J Immunol 1988 18 911 915 3260184 Manly KF Olson JM Overview of QTL mapping software and introduction to map manager QT Mamm Genome 1999 10 327 334 10087288 Merino R Shibata T De Kossodo S Izui S Differential effect of the autoimmune Yaa and lpr genes on the acceleration of lupus-like syndrome in MRL/MpJ mice Eur J Immunol 1989 19 2131 2137 2599002 Mitchell DA Pickering MC Warren J Fossati-Jimack L Cortes-Hernandez J C1q deficiency and autoimmunity: The effects of genetic background on disease expression J Immunol 2002 168 2538 2543 11859149 Miwa T Maldonado MA Zhou L Sun X Luo HY Deletion of decay-accelerating factor (CD55) exacerbates autoimmune disease development in MRL/lpr mice Am J Pathol 2002 161 1077 1086 12213736 Morel L Tian XH Croker BP Wakeland EK Epistatic modifiers of autoimmunity in a murine model of lupus nephritis Immunity 1999 11 131 139 10485648 Morel L Blenman KR Croker BP Wakeland EK The major murine systemic lupus erythematosus susceptibility locus, Sle1, is a cluster of functionally related genes Proc Natl Acad Sci U S A 2001 98 1787 1792 11172029 Moser KL Neas BR Salmon JE Yu H Gray-McGuire C Genome scan of human systemic lupus erythematosus: evidence for linkage on chromosome 1q in African-American pedigrees Proc Natl Acad Sci U S A 1998 95 14869 14874 9843982 Obata Y Tanaka T Stockert E Good RA Autoimmune and lymphoproliferative disease in (B6-GIX+ × 129)F1 mice: Relation to naturally occurring antibodies against murine leukemia virus-related cell surface antigens Proc Natl Acad Sci U S A 1979 76 5289 5293 228283 O'Keefe TL Williams GT Davies SL Neuberger MS Hyperresponsive B cells in CD22-deficient mice Science 1996 274 798 801 8864124 O'Keefe TL Williams GT Batista FD Neuberger MS Deficiency in CD22, a B cell-specific inhibitory receptor, is sufficient to predispose to development of high affinity autoantibodies J Exp Med 1999 189 1307 1313 10209047 Pepys MB Role of complement in induction of antibody production in vivo : Effect of cobra factor and other C3-reactive agents on thymus-dependent and thymus-independent antibody responses J Exp Med 1974 140 126 145 4545894 Pepys MB Butler PJ Serum amyloid P component is the major calcium-dependent specific DNA binding protein of the serum Biochem Biophys Res Commun 1987 148 308 313 3675579 Pepys MB Baltz M Gomer K Davies AJ Doenhoff M Serum amyloid P-component is an acute-phase reactant in the mouse Nature 1979 278 259 261 423976 Prodeus AP Goerg S Shen LM Pozdnyakova OO Chu L A critical role for complement in maintenance of self-tolerance Immunity 1998 9 721 731 9846493 Rozzo SJ Vyse TJ Drake CG Kotzin BL Effect of genetic background on the contribution of New Zealand black loci to autoimmune lupus nephritis Proc Natl Acad Sci U S A 1996 93 15164 15168 8986781 Russell AI Cunninghame Graham DS Shepherd C Roberton CA Whittaker J Polymorphism at the C-reactive protein locus influences gene expression and predisposes to systemic lupus erythematosus Hum Mol Genet 2004 13 137 147 14645206 Santiago ML Mary C Parzy D Jacquet C Montagutelli X Linkage of a major quantitative trait locus to Yaa gene-induced lupus-like nephritis in (NZW × C57BL/6)F1 mice Eur J Immunol 1998 28 4257 4267 9862363 Santiago-Raber ML Lawson BR Dummer W Barnhouse M Koundouris S Role of cyclin kinase inhibitor p21 in systemic autoimmunity J Immunol 2001 167 4067 4074 11564828 Szalai AJ Weaver CT McCrory MA van Ginkel FW Reiman RM Delayed lupus onset in (NZB × NZW)F1 mice expressing a human C-reactive protein transgene Arthritis Rheum 2003 48 1602 1611 12794828 Theofilopoulos AN Dixon FJ Murine models of systemic lupus erythematosus Adv Immunol 1985 37 269 390 3890479 Theofilopoulos AN Kono DH The genes of systemic autoimmunity Proc Assoc Am Physicians 1999 111 228 240 10354363 Vyse TJ Todd JA Genetic analysis of autoimmune disease Cell 1996 85 311 318 8616887 Vyse TJ Rozzo SJ Drake CG Izui S Kotzin BL Control of multiple autoantibodies linked with a lupus nephritis susceptibility locus in New Zealand black mice J Immunol 1997 158 5566 5574 9164982 Wakeland EK Liu K Graham RR Behrens TW Delineating the genetic basis of systemic lupus erythematosus Immunity 2001 15 397 408 11567630 Wu X Jiang N Deppong C Singh J Dolecki G A role for the Cr2 gene in modifying autoantibody production in systemic lupus erythematosus J Immunol 2002 169 1587 1592 12133988 Xie S Chang SH Sedrak P Kaliyaperumal A Datta SK Dominant NZB contributions to lupus in the (SWR × NZB)F1 model Genes Immun 2002 3 Suppl 1 S13 S20 12215897 Zeng ZB Precision mapping of quantitative trait loci Genetics 1994 136 1457 1468 8013918

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020246Research ArticleCell BiologySaccharomyces 4932)Gcn4p and Novel Upstream Activating Sequences Regulate Targets of the Unfolded Protein Response Gcn4p and Novel Sequences in the UPRPatil Christopher K 1 2 Li Hao 2 3 Walter Peter pwalter@biochem.ucsf.edu 1 2 1Howard Hughes Medical Institute, Chevy ChaseMaryland, United States of America2Department of Biochemistry and Biophysics, University of CaliforniaSan Francisco, California, United States of America3California Institute for Quantitative Biomedical Research, San FranciscoCaliforniaUnited States of America8 2004 17 8 2004 17 8 2004 2 8 e24620 2 2004 17 5 2004 Copyright: © 2004 Patil et al.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. IRE1-Independent Gain Control of the Unfolded Protein Response Yeast Use Dual Gain Controls to Amplify Protein Processing Eukaryotic cells respond to accumulation of unfolded proteins in the endoplasmic reticulum (ER) by activating the unfolded protein response (UPR), a signal transduction pathway that communicates between the ER and the nucleus. In yeast, a large set of UPR target genes has been experimentally determined, but the previously characterized unfolded protein response element (UPRE), an upstream activating sequence (UAS) found in the promoter of the UPR target gene KAR2, cannot account for the transcriptional regulation of most genes in this set. To address this puzzle, we analyzed the promoters of UPR target genes computationally, identifying as candidate UASs short sequences that are statistically overrepresented. We tested the most promising of these candidate UASs for biological activity, and identified two novel UPREs, which are necessary and sufficient for UPR activation of promoters. A genetic screen for activators of the novel motifs revealed that the transcription factor Gcn4p plays an essential and previously unrecognized role in the UPR: Gcn4p and its activator Gcn2p are required for induction of a majority of UPR target genes during ER stress. Both Hac1p and Gcn4p bind target gene promoters to stimulate transcriptional induction. Regulation of Gcn4p levels in response to changing physiological conditions may function as an additional means to modulate the UPR. The discovery of a role for Gcn4p in the yeast UPR reveals an additional level of complexity and demonstrates a surprising conservation of the signaling circuit between yeast and metazoan cells. The yeast unfolded protein response activates a large set of target genes, but a characterized element found in the promoter of one target, KAR2, cannot account for most targets. Using computational and experimental methods, the authors identify additional elements, as well a role for GCN4p in the response ==== Body Introduction The vast majority of all cellular secretory and membrane proteins are folded and modified in the endoplasmic reticulum (ER), from which they are transported to their final destination in the secretory pathway. When the protein folding capacity of the ER is exceeded or experimentally impaired, unfolded proteins accumulate in the ER and activate the unfolded protein response (UPR). The UPR allows the ER to communicate with the nucleus (Patil and Walter 2001), where a comprehensive gene expression program is induced to adjust the protein folding capacity of the cell according to need. In the yeast S. cerevisiae, unfolded ER proteins stimulate the ER-resident bifunctional transmembrane kinase/endoribonuclease Ire1p (Cox et al. 1993; Mori et al. 1993; Sidrauski and Walter 1997). When activated, Ire1p excises a 252-nucleotide intron from the mRNA encoding Hac1p, a bZIP transcription factor required for induction of all UPR target genes (Cox and Walter 1996; Mori et al. 1996; Sidrauski and Walter 1997). Removal of the HAC1 intron and subsequent ligation of the two liberated exons by tRNA ligase (Sidrauski et al. 1996) produces a spliced mRNA that is efficiently translated (Kawahara et al. 1997). In the absence of splicing, the intron blocks translation of the mRNA (Rüegsegger et al. 2001). Splicing is therefore a prerequisite for Hac1p production and thus serves as the key regulatory step in the UPR. When it is produced, Hac1p binds an upstream activating sequence (UAS), the unfolded protein response element (UPRE), found in the promoters of UPR target genes (Mori et al. 1992; Kohno et al. 1993), thereby stimulating the transcriptional response to protein unfolding. Several salient features of the UPR are conserved between yeast and metazoans. In metazoans, Ire1p orthologs Ire1-α and Ire1-β remove a short intron from the XBP-1 mRNA, which encodes a bZIP transcription factor analogous to Hac1p (Wang et al. 1998; Miyoshi et al. 2000; Urano et al. 2000; Calfon et al. 2002). The metazoan UPR, however, is implemented by at least two additional ER-resident sensors, which are thought to act in parallel and induce multiple downstream transcriptional activators not known to exist in yeast. A second branch of ER-to-nucleus signaling is mediated by ATF-6, a bZIP transcription factor that is synthesized as an integral ER transmembrane protein (Haze et al. 1999). Upon UPR induction, ATF-6 is proteolytically cleaved, liberating a soluble fragment that moves to the nucleus to induce transcription in association with XBP-1 (Wang et al. 2000; Ye et al. 2000; Steiner et al. 2001; Yoshida et al. 2001; Lee et al. 2002a). A third branch of the metazoan UPR provides translational control by the ER transmembrane kinase PERK (Harding et al. 1999; Liu et al. 2000). When activated in response to protein misfolding in the ER, PERK phosphorylates the translation initiation factor eIF-2α, thereby down-tuning translation of many mRNAs (and decreasing the translocational load on the ER) (Harding et al. 2000a, 2000b). Under conditions of limiting eIF-2α activity, however, some mRNAs containing short upstream open reading frames (ORFs) in their 5′ UTR are preferentially translated. One of these mRNAs encodes a third bZIP transcription factor, ATF-4, which collaborates with XBP-1 and other cellular stress signaling factors to activate UPR targets (Harding et al. 2000a, 2003; Ma et al. 2002). The UPR target genes of yeast have been comprehensively defined by microarray expression profiling, where they comprise a significant fraction of the yeast genome (381 genes, more than 5% of the ORFs) (Travers et al. 2000). The UPR target genes encode many proteins that play critical roles in the ER, the Golgi apparatus, and throughout the secretory pathway. Hence, the UPR can be thought of as a means of homeostatic control, serving to remodel the secretory pathway according to the cell's need. The set of 381 genes was defined by microarray hybridization expression profiling, using a stringent quantitative “filter” that required the expression profile of each target gene to closely match that of previously known and well-characterized UPR target genes. In particular, the filter demanded that the expression profile of a target gene closely correlate to that of canonical UPR targets over a time course of UPR induction, and that induction be significantly greater in wild-type (WT) than in either Δire1 or Δhac1 cells. The identification of this vast set of target genes poses an enigma in light of the previously characterized UPRE. The UPRE was originally defined as a 22-bp sequence element of the KAR2/BiP promoter (Mori et al. 1992) and subsequently carefully refined to nucleotide precision as a semipalindromic seven-nucleotide consensus, CAGNGTG (Mori et al. 1998). Point mutations in any one of the six conserved nucleotides or deletion of the central nucleotide was shown to have severely detrimental effects on the ability of the element to function as an autonomous UAS when placed into an otherwise silent promoter. Yet, inspection of the 381 promoter sequences of the experimentally defined set of target genes failed to reveal a recognizable UPRE in most of them. This observation is particularly surprising given that the UPRE is thought to be the Hac1p binding site, and HAC1 has been shown to be required for activation of all UPR target genes. One possible resolution to this paradox is that additional, heretofore unrecognized UPREs exist that are required for the activation of the genes lacking the “classical” UPRE. A requirement for new cis-activating sequences in the promoters of UPR target genes raises the possibility that such sequences could be bound by other trans-acting factors, alone or in combination with Hac1p, and thus contribute to the transcriptional complexity of the UPR. Results Computational Identification of Target Motifs To identify sequence motifs shared by the set of UPR target genes, we employed a bioinformatics approach to build a “dictionary” of putative regulatory elements from the promoters of these genes. In this approach, DNA sequence is considered as a “text” (a long string of nucleotides), which is modeled as having been composed by concatenating “words” (short oligonucleotides) drawn from a probabilistic “dictionary” according to their frequencies. To infer the dictionary from the observed text, we employed the previously developed computational algorithm, MobyDick, which was developed based on a probabilistic segmentation model (Bussemaker et al. 2000a, 2000b). MobyDick has been used previously to identify regulatory sites in large sets of promoters activated during sporulation or by specific cell-cycle stage. We first constructed a dictionary from the UPR target gene promoters. To this end, we compiled a text from the promoters of all 381 UPR target genes as previously defined (Travers et al. 2000). We defined the promoter region for each ORF as the 600 nucleotides upstream of the initiation codon. Probabilistic segmentation analysis using the MobyDick algorithm indicated that the target gene promoters are best modeled by a dictionary of about 300 words of eight nucleotides or less (for details of this and subsequent calculations, see Materials and Methods; a complete report of the dictionary with associated statistics appears in Table S1). These words represent the sequences that are most frequent in the target gene promoters. Because words with similar sequences are likely to possess similar biological activity, we considered groups of related words as units in our subsequent analysis. We grouped the dictionary into motifs by performing every possible pairwise alignment between all words, and then clustering words with high mutual alignment scores. A motif may contain two or more words, or just a single word. For a multiword motif, the words defining the motif are similar to one another and share common core sequences (Figure 1B; Table S2). The clustering procedure yielded about 100 motifs, about half of which contain multiple words. Figure 1 Computational Selection of Candidate Regulatory Motifs (A) Candidate regulatory motifs are overrepresented in UPR target promoters. Sequence motifs were ranked in order of overrepresentation, i.e., on the number of observed appearances in target promoters relative to the expectation from the total appearances in all promoters. −log10 P, a metric of overrepresentation, is plotted against rank (circles). Eight motifs were chosen for experimental characterization (open circles). (B) Best words grouped into eight candidate motifs. The eight most overrepresented motifs from Fig. 1A, aligned to illustrate common core sequences. The example of each motif chosen for experimental characterization is underlined. We reasoned that motifs that are likeliest to represent bona fide regulatory elements will be nonrandomly distributed in the genome and appear more often in the UPR target gene promoters than expected by chance. Therefore, we counted the number of times each motif (i.e., a sequence match to any of the words the motif comprises) appeared in the approximately 6,000 promoters in the genome, and computed from this figure the frequency with which each motif would be expected to appear in a promoter if it were distributed randomly throughout the genome. We then counted the number of times the motif was actually found in the 381 target promoters and calculated the probability P of this many or more appearances occurring by chance. A small P value (high −log10 P) indicates that the motif is overrepresented relative to the expectation. Figure 1A shows the motifs ranked in order of decreasing overrepresentation, with −log10 P for each motif plotted against this rank. We chose the eight highest-ranking motifs (open circles) as candidates for experimental testing (Figure 1B), analyzing a single example of each (underlined sequences). Experimental Verification of Novel UPREs To determine whether any of the eight candidate motifs would function as bona fide UPREs, we introduced three tandem repeats of a single representative sequence of each motif into a lacZ reporter construct that contains a crippled version of the CYC1 promoter that is transcriptionally silent in the absence of a UAS (Guarente and Mason 1983). Analogous constructs containing the “classical,” KAR2-derived UPRE inserted upstream of the core promoter have been shown to drive transcription of this reporter gene under ER stress (Mori et al. 1992; Cox et al. 1993). As a positive control for UPR-dependent gene expression, we used a construct containing a triple repeat of the KAR2-derived UPRE (Cox and Walter 1996). We transformed the resulting plasmids into yeast and assayed for β-galactosidase activity in response to ER stress. Of the eight reporter constructs, the two containing Motif 1 and Motif 8 were transcriptionally activated when cells were treated with tunicamycin (Tm) (Figure 2A), or dithiothreitol (DTT) (unpublished data), both inducers of the UPR. The other six motifs showed no activity above baseline (unpublished data). Neither Motif 1 nor Motif 8 showed any activity in the absence of ER stress, and no activation was observed upon UPR induction in either Δire1 or Δhac1 strains. Hence, as with the “classical” UPRE, these two motifs are sufficient to confer transcriptional activation upon a promoter in an IRE1-, HAC1-, and ER stress-dependent manner. We therefore conclude that the bioinformatics analysis has identified two novel UPREs present in target gene promoters; hereafter, we refer to Motif 1 and Motif 8 as UPRE-2 and UPRE-3, respectively. Correspondingly, we shall refer to the classical, KAR2-derived UPRE as UPRE-1. Figure 2 Identification of Two Novel Sequence Motifs Necessary and Sufficient for UPR Activation (A) Motif 1 and Motif 8 are sufficient to confer UPR-responsive transcription on an artificial promoter. Single representative sequences of the KAR2-derived UPRE and candidate regulatory motifs Motif 1 and Motif 8 were cloned into a crippled promoter driving lacZ, transformed into yeast (WT, Δire1, and Δhac1), and β-galactosidase activity monitored in response to Tm treatment. (B) UPRE-2 (Motif 1) is necessary for UPR-dependent activation of the ERO1 promoter. lacZ was placed under the control of the WT ERO1 promoter (+ UPRE-2) or a mutant (− UPRE-2), and β-galactosidase activity monitored in response to DTT treatment. (C) UPRE-3 (Motif 8) is necessary for UPR-dependent activation of the DHH1 promoter. As in (B), except using the DHH1 promoter, in which UPRE-3 appears once. (D) Novel motifs explain a greater fraction of UPR target gene activation. Sets of genes whose promoters contain UPR-responsive UASs UPRE-1, UPRE-2, UPRE-3, or a combination, are here depicted in Venn diagram format as subsets of the 381-gene UPR target set. To test whether these motifs are also necessary for transcriptional activation, we designed lacZ reporter constructs derived from two native promoters in which the motifs appear. We chose for UPRE-2 the promoter of ERO1, encoding an ER resident redox protein, and for UPRE-3 the promoter of DHH1, encoding an RNA helicase. Both genes are robust targets of the UPR (Travers et al. 2000) and lack a recognizable UPRE-1. First, we verified that the reporters responded to ER stress in a UPR-dependent manner. WT but not Δire1 or Δhac1 cells bearing the UPRE-2-containing ERO1-promoter-driven reporter expressed higher levels of β-galactosidase after treatment with DTT (Figure 2B, “+ UPRE-2” columns). In a mutant version of this reporter construct, in which the UPRE-2 was ablated and replaced by an unrelated sequence of identical length, inducibility of the ERO1 promoter was decreased by approximately 4-fold (“− UPRE-2” columns). Similarly, WT but not Δire1 or Δhac1 cells bearing the UPRE-3-containing DHH1-promoter-driven reporter expressed higher levels of β-galactosidase after treatment with DTT (Figure 2C, “+ UPRE-3” columns); ablation of UPRE-3 from the DHH1 promoter entirely eliminated induction by ER stress ( “− UPRE-3” columns). Taken together, the data presented so far indicate that, as with the classical UPRE-1, UPRE-2 and UPRE-3 are both sufficient (Figure 2A) and necessary (Figure 2B and 2C) to confer UPR inducibility on a target promoter. The addition of UPRE-2 and UPRE-3 to the repertoire of UPREs triples the number of genes in the UPR target set whose induction we can explain by invoking the presence of a well-defined UAS (Figure 2D). Identification of High-Copy Activators of UPRE-2 The existence of functional cis-regulatory elements that differ in sequence from the canonical UPRE-1 suggests that trans-activating factors other than Hac1p may bind these elements. Alternatively, Hac1p, alone or accompanied by another factor or factors, may be able to recognize multiple sequences. To distinguish between these possibilities and potentially reveal novel regulatory factors, we attempted to identify genes which, when overexpressed, activate transcription of the UPRE-2 reporter plasmid in the absence of an ER stress signal. The design of this screen recapitulates the approach which identified HAC1 as a high-copy activator of the UPRE-1 (Cox and Walter 1996). We transformed a strain bearing the UPRE-2-lacZ reporter with a 2-μm-plasmid-derived ( high-copy) genomic DNA library (Miller et al. 1984). A Δire1 strain was used in order to focus the screen on genes acting downstream of IRE1. Use of the Δire1 strain also avoided a background of false positives resulting from library plasmids encoding secretory proteins whose overexpression might activate Ire1p. Transformants were plated on synthetic defined media and, after appearance of colonies, overlaid with soft agar containing the β-galactosidase substrate X-gal. Colonies that turned significantly more blue than control (untransformed) colonies were recovered and rescreened by the same assay. Plasmids from positively rescreened clones were retransformed into the Δire1 UPRE-2-lacZ strain to verify plasmid linkage of the activator phenotype. We screened a total of 112,000 transformants, representing a predicted genomic coverage of approximately 50x. Thirty-eight positive transformants passed through repetition and plasmid linkage tests, and 18 of these stably maintained the activator phenotype over many generations. Positive plasmids fell into two classes, as defined by the minimal region of overlap of their insert sequences. One class of inserts (ten plasmids) shared the IRE1 locus and surrounding sequences; IRE1 has been previously shown to be activated by overexpression and is a high-copy activator of UPRE-1 (Cox et al. 1993). Recovery of this locus demonstrates that the screen was able to capture genes of physiological relevance to the pathway. The second class of positive inserts (eight plasmids) shared the GCN4 locus. GCN4 encodes a bZIP transcription factor, which has been well-characterized as a component of the cellular response to amino acid starvation and other stresses (Natarajan et al. 2001; reviewed in Hinnebusch 1997) but has not been previously demonstrated to play a role in the UPR. We constructed a 2-μm plasmid bearing only GCN4, transformed it into WT, Δire1, and Δhac1 strains carrying UPRE-1-lacZ, UPRE-2-lacZ, and UPRE-3-lacZ reporters, and assayed for β-galactosidase activity (Figure 3A). GCN4 overexpression stimulated UPRE-2-driven reporter activity in all three genotypes ( “+ GCN4 2μ” columns), indicating that overexpression of GCN4 is sufficient to stimulate transcription from the UPRE-2-driven reporter gene in the absence of ER stress, Ire1p activity, or Hac1p production. We also starved cells for histidine by administering 3-aminotriazole (3-AT), which induces translation of Gcn4p (Albrecht et al. 1998). As when cells expressed high levels of GCN4, amino acid starved cells exhibited a significant increase of UPRE-2 transcription in the absence of ER stress ( “+3-AT, −Tm” columns). GCN4 overexpression alone did not activate transcription from either UPRE-1 or UPRE-3 reporter genes, emphasizing that these motifs are not synonymous with UPRE-2. Figure 3 GCN4 Encodes a Novel Transcription Factor in the UPR (A) Overexpression of GCN4 is sufficient for activation of UPRE-2, but not UPRE-1 or UPRE-3. UPRE-driven transcriptional activity as a function of Gcn4p levels, elevated either as a result of overexpression (+ GCN4–2μ) or amino acid starvation (+ 3-AT), in the presence or absence of ER stress (Tm). (B) GCN4 and GCN2 are necessary for ER stress-dependent activation of UPRE-1 and UPRE-2. UPRE-driven transcriptional activity as a function of GCN4 pathway genes (WT, Δgcn4, and Δgcn2) in the presence or absence of ER stress (Tm). (C) GCN4 and GCN2 are required for UPR-dependent transcriptional activation of a subset of target genes. Fold changes in mRNA levels were determined by microarray for DTT-treated vs. -untreated WT, Δire1, Δgcn4, and Δgcn2 strains (columns). Histograms show distribution of log2-fold changes for non-UPR target genes (light bars) and for UPR target genes (dark bars), which contain UPRE-1, UPRE-2, UPRE-3, or still unidentified UPREs (rows) in their promoters. (D) Target gene regulation differs significantly in WT and Δgcn4/Δgcn2 mutants. Means (μ) and standard deviations (σ) for log2-fold change in gene expression for non-UPR target genes, and for genes that fall inside the UPR target gene set and contain UPRE-1, UPRE-2, or UPRE-3 in their promoters. Z statistic (z) and P value (P): higher z reflects a greater difference between the distribution for UPRE-containing target genes and nontarget genes; lower P indicates a more highly significant difference. For detailed calculations, see Materials and Methods. GCN4 and GCN2 Are Required for Activation of All Three UPREs Having demonstrated that GCN4 overexpression is sufficient to activate transcription from a UPRE-2 reporter, we next asked whether GCN4 is also necessary to activate transcription in response to ER stress. We deleted GCN4 from strains bearing UPRE-1, UPRE-2, and UPRE-3 reporter constructs and assayed β-galactosidase activity in response to UPR activation. Upon UPR induction, HAC1 mRNA was spliced normally, and Hac1p was produced at WT levels in Δgcn4 mutants (unpublished data). However, Δgcn4 cells failed to induce transcription, not only of the UPRE-2-driven reporter but also of the UPRE-1- and UPRE-3-driven reporters (Figure 3B). Hence we conclude that GCN4 is required for ER stress responsiveness of all three UPREs. Consistent with the genetic requirement for GCN4, high levels of Gcn4p potentiate transcription from all UPREs when the UPR is activated. GCN4 overexpression increases the level of reporter activation in WT cells when the UPR is induced (Figure 3A, compare “GCN4 +Tm” to “GCN4 −Tm” data), suggesting that GCN4 activity is limiting for UPR-dependent transcription from all three UPREs. Similarly, stimulation of Gcn4p production by amino acid starvation also increases the magnitude of the transcriptional response (Figure 3A, “+3-AT, +Tm” data). In its role in the transcriptional response to amino acid starvation, GCN4 is activated at the translational level. Uncharged tRNAs are detected by the kinase Gcn2p, which phosphorylates initiation factor 2α (eIF-2α); when eIF-2α is phosphorylated, scanning ribosomes fail to initiate at upstream ORFs encoded by the GCN4 5′ UTR and are able to initiate translation at the GCN4 ORF itself (Hinnebusch 1997). We therefore asked whether GCN2 is also required for GCN4 activity in the context of the UPR. As with Δgcn4 cells, Δgcn2 strains were also unable to mount a transcriptional response from any of the reporter constructs (Figure 3B). Given that GCN4 and GCN2 are necessary for ER stress-dependent transcription in an artificial promoter context, we next asked whether these genes are required for upregulation of the target genes of the UPR. To this end, we measured steady-state mRNA levels by microarray hybridization, comparing WT, Δire1, Δgcn4, and Δgcn2 cells treated with DTT for 30 min (by which time the UPR is qualitatively complete; Travers et al. 2000) to untreated samples of the same genotype. WT cells were taken as a positive control for UPR induction, and Δire1 cells as a negative control. Fold change in expression of a given gene was computed as the ratio of mRNA level in the treated sample to the level in an untreated sample of the same genotype. In our analysis, we considered five subsets of genes: the sets of UPR target genes containing a UPRE-1, UPRE-2, or UPRE-3 in their promoter, the set of UPR target genes without an identified UPRE in their promoters (“no UPRE”), and the set of genes previously identified as UPR-independent (“nontargets”) (Travers et al. 2000). The distributions of the log2-fold changes for each subset of genes in each genotype relative to the set of nontarget genes are illustrated in Figure 3C. For each gene set in each genotype, we determined the difference between the distributions of log2-fold changes in UPRE target genes and those in nontarget genes. The statistical significance of these differences is represented by the z scores and P values enumerated in Figure 3D; higher z and lower P indicate a greater difference between distributions and higher significance (for details see Materials and Methods). The majority of the genes in the nontarget set (Figure 3C, all histograms, light bars) are not differentially regulated by ER stress in the WT and mutant strains. As previously shown, however, genes of the UPR target set are significantly more upregulated in the WT than in Δire1 cells (Figure 3C, compare dark bars versus light bars between histograms a and b, e and f, i and j, and m and n). This is the case both for target genes bearing any UPRE in the promoter (Figure 3C, histograms a–l) as well as the remainder of the target set for which a UPRE has not been identified (Figure 3C, histograms m–p). For those genes with an identified UPRE in their promoters, expression patterns in both Δgcn4 (Figure 3C, histograms c, g, and k) and Δgcn2 mutants (Figure 3C, histograms d, h, and l) show trends similar to those in Δire1. In both mutants, the sets of genes whose promoters contain a UPRE are significantly less upregulated relative to their induction in the WT. Some UPR target genes exhibit residual upregulation in Δgcn4 and Δgcn2, suggesting that these promoters have only a partial requirement for GCN4/GCN2. This effect is most prominent for genes containing UPRE-1 in the Δgcn2 mutant (Figure 3C, histogram j), where the residual induction crosses the threshold into marginal statistical significance (Figure 3D, “Δgcn2, UPRE-1”; p = 3.4 × 10−4); it is possible that the residual levels of Gcn4p present in a Δgcn2 mutant are sufficient to allow UPR transcription from these promoters, or alternatively that UPRE-1 promoters are relatively less sensitive to Gcn4p levels (and concomitantly, relatively more reliant on Hac1p) for induction (see Discussion). In contrast, induction of the “no UPRE” genes is quite high in Δgcn4 and Δgcn2 cells (Figure 3C, histograms o and p versus m). As a population, these genes are not significantly less upregulated in the mutants than in the WT. It would appear that the UPREs identified to date define a special subset of UPR target genes that are responsive not only to IRE1 and HAC1 but that are particularly sensitive to the GCN4/GCN2 branch of the pathway. Overall, in both Δgcn4 and Δgcn2 mutants, the pattern of gene regulation during the UPR is similar to that in the Δire1 mutant: Mean fold changes of UPRE-containing target genes are lower in these mutants than in the WT. We conclude that GCN4 and GCN2 play a broad role in the UPR, contributing significantly to the upregulation of a large subset of UPR target genes. Gcn4p Is Upregulated in Response to ER Stress Given the requirement for GCN4 in UPR-dependent transcription, and in particular the observation that Gcn4p appears to be limiting for the magnitude of the transcriptional response (Figure 3A), we asked next whether Gcn4p levels would be subject to posttranscriptional regulation under conditions of ER stress. We discounted the possibility that GCN4 would be regulated at the transcriptional level, as our previous studies showed that GCN4 mRNA levels are unchanged over the course of the UPR (Travers et al. 2000). We constructed strains expressing a C-terminally myc-epitope-tagged allele of Gcn4p, which complements the slow growth phenotype of a Δgcn4 mutant and is inducible by amino acid starvation resulting from 3-AT treatment (Figure 4A, “Gcn4p” lanes, compare “wt, +3-AT” to “wt, 0 min”). Over a time course of UPR induction, Gcn4p-myc levels exhibited a transient increase of 2.5-fold, peaking after 15 min and gradually decaying to uninduced levels after 60–120 min (Figure 4A, “WT” lanes; quantitated in Figure 4B). This temporary increase in Gcn4p was not observed in UPR-deficient mutants: neither Δire1 nor Δhac1 mutants exhibited increased levels of Gcn4p over the time course of UPR induction. Figure 4 Gcn4p Protein Levels Are Upregulated during the UPR (A) Gcn4p levels, but not eIF-2α phosphorylation, rise under ER stress in a UPR-dependent manner. Cells bearing a C-terminally myc-tagged allele of GCN4 were treated with Tm for 0, 15, 30, 60, or 120 min. Western blots probed with anti-myc recognizing Gcn4p-myc (top panels) or phospho-specific anti-eIF-2α antibody (bottom panel). Gcn4p blot for the Δgcn2 mutant is 5x overexposed so that the bands are visible. (B) Quantitation of the Gcn4p-myc protein levels in Figure 4A. Data reflect an average of four experiments, normalized against Gcn4p levels in the WT t = 0 samples. In the context of other stress responses (e.g., amino acid starvation), Gcn4p levels are regulated via phosphorylation of eIF-2α by Gcn2p (Dever et al. 1993; Hinnebusch 1993; Diallinas and Thireos 1994). Because GCN2 is required for induction of UPR-dependent transcription, we asked whether GCN2 was required for the rise in Gcn4p levels we observed during Tm treatment. Basal levels of Gcn4p are low in a Δgcn2 strain (less than 10% of WT), as previously reported (Hinnebusch 1993; Tavernarakis and Thireos 1996). We observed no increase in Gcn4p levels during the time course in this mutant (Figure 4B). These data are consistent with two possibilities: first, that Gcn2p is responsible for both basal levels of Gcn4p and its induction upon ER stress; or second, that Gcn2p is responsible only for maintaining basal levels of Gcn4p, while another pathway mediated by Ire1p/Hac1p further elevates Gcn4p levels during the UPR. If Gcn2p is responsible for upregulation of Gcn4p during the UPR, we should observe a concomitant increase in the level of eIF-2α phosphorylation. We did not observe such an increase (Figure 4A, “eIF-2α-P” lanes), which is consistent with the idea that Gcn2p's role in the UPR is primarily to maintain basal levels of Gcn4p, not to upregulate Gcn4p via increased eIF-2α phosphorylation. Other workers have observed a transient increase in phospho-eIF-2α under Tm treatment (Cherkasova and Hinnebusch 2003). It is possible that strain differences or the significantly greater doses of Tm used in the previous study (4 and 20 μg/ml versus our 1 μg/ml) explain this disparity. Consistent with our findings, Cherkasova and Hinnebusch (2003) predict derepression of GCN4 by ER stress mediated by increased phospho-eIF-2α. Here, we observe increased Gcn4p levels under ER stress conditions even when phospho-eIF-2α levels are not detectably altered. Epistasis of HAC1 and GCN4 GCN4 plays an essential role in the UPR, with a knockout phenotype closely resembling that of Δire1 and Δhac1: the absence of any of these genes prevents transcriptional activation by ER stress. This observation could be a consequence of one of several different mechanisms: Gcn4p might act upstream or downstream of Hac1p in the same linear pathway, or act in a parallel pathway that converges at target promoters. Two lines of evidence from data already introduced argue that Gcn4p does not act upstream of Hac1p. First, GCN4 overexpression is sufficient to activate transcription from UPRE-2 in a Δhac1 mutant (see Figure 3A), indicating that Gcn4p's influence on target promoters can occur by a Hac1p-independent mechanism. Second, the transient upregulation of Gcn4p levels observed under ER stress is absent in the Δhac1 mutant (see Figure 4A), indicating that Hac1p levels determine Gcn4p levels. Further evidence that Gcn4p does not act upstream of Hac1p is provided by the observation that expression of Hac1p cannot activate transcription in a Δgcn4 mutant (Figure 5). In a WT cell, expression of Hac1p produced from a HAC1 gene lacking the intron is sufficient to activate transcription from the UPRE-1 (Cox and Walter 1996; Figure 5, “UPRE-1” columns). Constitutive expression of Hac1p is also sufficient to activate UPRE-2, and to a lesser extent UPRE-3, in the absence of ER stress (Figure 5, “WT, +Hac1p” columns) and in the absence of Ire1p (Figure 5, “Δire1, +Hac1p” columns). In the absence of GCN4, however, the constitutive expression of Hac1p does not activate transcription from any of the three reporter constructs (Figure 5, “Δgcn4, +Hac1p” columns), suggesting that Hac1p's function at promoters containing any one of the three UPREs requires the presence of Gcn4p. Thus, Gcn4p must act at the same point as or downstream of Hac1p. Following the same line of reasoning, for UPRE-1 and UPRE-3, GCN4 overexpression alone is insufficient to activate transcription in the absence of HAC1 (e.g., see Figure 3A, Δhac1 mutants), indicating that at UPRE-containing promoters Hac1p must act at the same point as or downstream of Gcn4p. Thus, the observations enumerated here are consistent with the interpretation that Gcn4p and Hac1p act together at target gene promoters. Figure 5 GCN4 Acts with or Downstream of HAC1 UPRE reporter activity as a function of Hac1p expression and UPR pathway genes. To express Hac1p in the absence of ER stress, we used an intron-less allele of HAC1, which is constitutively translated. A Gcn4p/Hac1p Complex Binds Both the UPRE-1 and UPRE-2 To explore this possibility directly, we performed gel-retardation assays with the UPRE-1-containing segment of the KAR2 promoter (oligo 1), used in previous experiments demonstrating direct binding of Hac1p to UPRE-1 (Cox and Walter 1996), and the UPRE-2-containing segment of the ERO1 promoter (oligo 2). 32P-labeled oligonucleotides were incubated with cell extracts and subjected to native (nondenaturing) polyacrylamide gel electrophoresis, and visualized by autoradiography (Figure 6). Figure 6 Hac1p and Gcn4p Directly Interact with UPRE-1 and UPRE-2 32P-labeled oligos bearing either UPRE-1 or UPRE-2 promoter were incubated with crude cell extracts, and subjected to nondenaturing polyacrylamide gel electrophoresis. (A) Extract: Samples were of the WT, or bore deletions in IRE1Δire1), GCN4 (Δgcn4), or GCN2 (Δgcn2), and were treated with Tm (+) or mock treated (−). Labeled oligos contained either UPRE-1 (1) or UPRE-2 (2). Binding reactions were incubated with no unlabeled competitor (−) or with 100x excess of unlabeled WT UPRE-1 (1), an inactive mutant version of UPRE-1 (1*), UPRE-2 (2), or an inactive mutant version of UPRE-2 (2*). (B) Extract: Samples from a strain overexpressing GCN4 (2μ-GCN4; lanes 1 and 2) or from a strain expressing myc-tagged Gcn4p and HA-tagged Hac1p (GCN4-myc and HA-HAC1). Binding reactions were incubated with no antibody (−), anti-myc recognizing Gcn4p-myc (myc), anti-HA recognizing HA-Hac1p (HA), or both antibodies simultaneously (myc/HA). Bands represent the following: a, Gcn4p + Hac1p + anti-myc + anti-HA; b, Gcn4p + Hac1p + anti-HA; c, Gcn4p + Hac1p + anti-myc; d, Gcn4p + Hac1p; e, Gcn4p. *, an unidentified band that appears only when extracts include both Gcn4-myc and HA-Hac1p and when both antibodies are included in the binding reaction. As previously observed, oligo 1's mobility was retarded when incubated with crude extracts from UPR-induced cells, but not extracts from untreated cells (Figure 6A; compare lane 2 to lane 1). Likewise, oligo 2 was specifically shifted by extracts from UPR-induced cells (compare lane 6 to lane 5). The binding activity is specific: for both oligos, the mobility shift was competed out by 100-fold excess of an unlabeled identical sequence (lanes 3 and 7) but not by a transcriptionally inactive point mutant of the same sequence (lanes 4 and 8). The binding activity is dependent on an intact UPR. No gel retardation was observed for either sequence in an Δire1 mutant (lanes 9 and 12), in which Hac1p cannot be synthesized. Likewise, in both Δgcn4 and Δgcn2 mutants, the binding activity observed in WT cells was absent. In both Δgcn4 and Δgcn2 mutants, however, a faster migrating complex appeared, which likely represents Hac1p alone binding the oligos (lanes 10, 11, 13, and 14). To demonstrate Gcn4p and Hac1p binding conclusively, we performed supershift analyses of the WT complex by addition of antibodies to either protein. We constructed a strain expressing both HA-epitope-tagged Hac1p and myc-tagged Gcn4p. Extracts from Tm-treated cells were incubated with antibodies against either or both tagged proteins. Antibodies recognizing either the tagged Gcn4p-myc (Figure 6B, lanes 5 and 6) or HA-Hac1p (lanes 7 and 8) supershifted the bound complex to different extents (compare lanes 7 and 8 to lanes 3 and 4). Hence, both Gcn4p and Hac1p can bind to sequences containing UPRE-1 and UPRE-2. Addition of both antibodies to the same binding reaction resulted in an ultrashifted band, migrating more slowly than the bands in either of the single antibody reactions (lanes 9 and 10). If Hac1p and Gcn4p bound DNA in distinct, separate complexes, we would expect to see two bands of identical mobility to those seen in lanes 5–8. We conclude that the mobility-shifted complex observed in UPR-induced WT cells therefore must contain both transcription factors, since no ultrashift would occur if the proteins were bound to separate complexes, and that Hac1p and Gcn4p act together at the same location to activate transcription upon UPR induction. (Similar gel-shift experiments performed with an oligonucleotide representative of UPRE-3 failed, indicating that transcription factor binding may be of reduced affinity at this sequence. This interpretation is consistent with the overall lower activity of the UPRE-3 reporter constructs (see Figure 2A). Further evidence that Gcn4p can bind UPRE-2 is provided by the observation that overexpression of GCN4 alone in an otherwise WT cell, in the absence of ER stress, resulted in a mobility shift for oligo 2 (Figure 6B, lane 2). This complex migrated faster than the WT complex (e.g., Figure 6B, lane 4). Because the extract was made from untreated cells, no Hac1p was present, indicating that the complex contains Gcn4p alone. The GCN4-dependent shift is not observed for oligo 1, consistent with observations above that Gcn4p overproduction is sufficient to activate transcription of a UPRE-2 reporter but not a UPRE-1 reporter (see Figure 3A). Reciprocally, Hac1p is present in the Δgcn4 and Δgcn2 mutants, but Gcn4p is absent; it therefore seems likely that the faster migrating bands in Δgcn4/Δgcn2 mutants (Figure 6A, lanes 10, 11, 13, and 14) represent oligonucleotides bound to Hac1p alone. Discussion Identification of Novel UASs Beginning only with the set of genes induced by the UPR and the promoter sequences of all genes in the genome, we computationally identified candidate motifs that obeyed the statistical properties we would expect of regulatory sequences, i.e., high frequency in UPR target promoters, and enrichment in the target promoters relative to the rest of the promoters in the genome. Two of these motifs, UPRE-2 and UPRE-3, are both necessary and sufficient to confer ER stress responsiveness in an IRE1- and HAC1-dependent manner on promoters which contain them. These novel sequences are activated under the same conditions as UPRE-1. Functional non-synonymy of these sequences, however, is illustrated by the activation of UPRE-2 by GCN4 overexpression alone, a condition under which UPRE-1 and UPRE-3 are silent, and by the quantitative difference with which the motifs respond to UPR activation (UPRE-2 > UPRE-1 > UPRE-3). Although the two new UPRE sequences look at first glance entirely different from the well-characterized UPRE-1, one of them may share “half-site” similarity: UPRE-2 has a three base identity with UPRE-1 at the 3′ end (TACGTG versus CAGNGTG); whether these bases make equivalent contacts with the bound transcription factors remains to be determined. Taken together, the sequence diversity of the motifs conferring similar transcriptional control upon binding of the same transcriptional activators illustrates the difficulty of predicting biological regulation from promoter sequences alone, even if binding sites in one context are well defined experimentally. The identification of these novel sequences allows a greater proportion of UPR target gene regulation to be explained within the paradigm of modular transcriptional control, i.e., in which a “portable” sequence module (a UAS) located within a promoter confers pathway responsiveness on the gene in question. The two novel motifs described triple the number of target genes whose regulation can be described in terms of a modular control mechanism, thus adding significantly to the repertoire of cis-acting elements known to act in the UPR. And yet, the resulting description of UPR transcription remains incomplete, as approximately 50% of the target genes still lack a recognizable UPREs. It may be that more biologically active motifs exist among the 109 motifs that emerged from the overrepresentation analysis, as many of the untested motifs are overrepresented relative to chance in the UPR target set by many orders of magnitude. For the eight motifs tested, we tested whether a motif was necessary for promoter induction only if it had already been shown to be sufficient in the artificial promoter system. Because of this experimental approach, it remains possible that some motifs not found to be sufficient are dependent for their activity on some contextual parameter (e.g., particular nearby flanking sequences). Thus it may be that some UPREs are not generally portable to other contexts, but are nonetheless necessary for UPR responsiveness of the native promoters in which they reside. Also, particularly rare motifs would have been omitted from the dictionary; thus, it is possible that complementary computational approaches might allow detection of uncommon motifs that this analysis missed. Finally, some UASs may remain ultimately undiscoverable within the paradigm of modular regulation. Motifs that are particularly sensitive to chromatin structure or position relative to the transcription initiation site would not be detected by an approach that neglected these parameters. It might be argued that the approach here enjoys no relative advantage over testing random oligonucleotides from UPR promoters. If every sequence from each target promoter were to be tested for activity, it is possible that additional elements not revealed by the bioinformatic approach would be discovered. For example, the residual upregulation of ERO1 after removal of UPRE-2 (see Figure 2B) suggests that at least one cryptic element exists in that promoter. On the other hand, the DHH1 promoter shows no residual upregulation after removal of UPRE-3 (see Figure 2C). If the average number of sites (candidate plus cryptic) per promoter is similar (1–2) throughout the target gene set, our computational approach represents a highly efficient means of identifying a subset of regulatory motifs. On the other hand, if the average is significantly higher, it is possible that testing random subsequences of target promoters would also be efficient. From the small number of promoters we studied in depth, it is not possible to calculate a meaningful upper bound for the average number of undiscovered regulatory sites per promoter. Nonetheless, within the sample size of our study, the yield of active regulatory sites per candidate tested (two of eight) is much higher than any reasonable a priori estimate of the density of regulatory elements in the UPR target promoters. One indication of a possible shortcoming of our computational approach is the finding that the probabilistic segmentation did not return the classical UPRE-1 as a significant “word,” i.e., the approach failed to generate a comprehensive list of all known active UPREs. The absence of UPRE-1 from the dictionary indicates that no sequence matching the experimentally defined degenerate consensus CAGNGTG is intrinsically overrepresented in the target promoters, i.e., this motif does not occur in the “text” of target gene promoters with a higher frequency than that with which its component subsequences would appear together by chance. Neither is this sequence overrepresented in the target promoter set relative to the promoters of the nontarget genes. The motif CAGNGTG has an overrepresentation score −log10 P of 0.37, far beneath the enrichment of any of the 109 motifs assembled from dictionary words (see Figure 1A). Hence, among genes that possess a UPRE-1 in their promoters, there are more instances of unresponsiveness to the UPR than instances of regulation, even though UPRE-1 has been experimentally demonstrated to be necessary and sufficient for upregulation in response to ER stress. A plausible resolution to this paradox may be that the UPRE-1 is heavily dependent on context. The experiments that defined the key core nucleotides proceeded by single point mutation at each position while holding constant the identity of all other nucleotides from the source 22-bp stretch of the KAR2 promoter; thus the seven-nucleotide “core sequence” may only specify those bases which are necessary for activity, but not define a module which is generally functional outside its original context of flanking sequence. If this were the case, we would not expect to recover UPRE-1 in a bioinformatic analysis of all target genes. Indeed, alignment of the KAR2 promoter from S. cerevisiae and three related budding yeasts reveals that UPRE-1 lies in the middle of a highly conserved 21-bp sequence which is 100% identical across three of the species (Figure 7A). This conserved stretch may represent a context that is essential for the transcriptional function of the core sequence. We speculate that recognition of the extended context may be performed by Hac1p without the collaboration of Gcn4p, as suggested by the observation that promoters which contain a UPRE are more dependent on GCN4/GCN2 than are those genes in which a short modular UAS has not been identified (see Figure 3C, histograms o and p). Figure 7 Multiple Alignment of UPRE-1 and UPRE-2 from Three Budding Yeasts Alignment of partial promoter sequences from S. cerevisiae and homologous sequences in related yeasts. Numerical coordinates reflect the distance from the first nucleotide of the initiation codon in the S. cerevisiae promoter. (A) A segment of the KAR2/YJL034W promoter and homologs. The core sequence of UPRE-1 is indicated. (B) A segment of the ERO1/YML130C promoter and homologs. The core sequence of UPRE-2 is indicated (above). The consensus binding site of Gcn4p is aligned (below). Despite these qualifications, the approach has successfully uncovered novel information about how the UPR is regulated. The appealing aspect of the strategy described here is that such studies are not limited to the UPR but can be generally employed in the study of any transcriptional response in any organism for which promoter sequences for all genes are known and in which the comprehensive genomic output of the response can be measured by expression profiling. The sole requirement of the probabilistic segmentation/overrepresentation computations is that a partition of the genome (into “target genes” and “nontarget genes”) be made on the basis of some meaningful difference in expression levels under the conditions of interest; the analysis thereafter proceeds by comparing the distribution of candidate motifs in the target gene set and the remainder of the genome. Further refinement of the mathematical tools therefore promises to be of invaluable help in our quest for a comprehensive understanding of the logic and complex interactions of transcriptional programs in eukaryotic cells. GCN4 Is an Essential Transcription Factor of the UPR The overexpression screen for activators of UPRE-2 revealed a role for the transcription factor Gcn4p, which we show to be required not only for activity of UPRE-2 but for all three known UPREs. Gcn4p and its upstream activator Gcn2p thus join Ire1p, Hac1p, and Rlg1p in the list of essential players in the yeast UPR. GCN4 encodes a well-characterized transcription factor acting in several distinct stress responses including amino acid starvation, glucose limitation, and ultraviolet irradiation (Hinnebusch 1997; Yang et al. 2000; Natarajan et al. 2001; Stitzel et al. 2001), but has not previously been demonstrated to play any role in the UPR. Here, we demonstrate that GCN4 is required for normal induction of UPR transcription, both in the context of artificial promoters containing any of the known UPREs and in the context of the native promoters of most target genes. GCN2, a gene implicated in regulating GCN4 in other stress responses, is similarly required for a normal UPR, perhaps because GCN2 function is required to maintain the basal level of Gcn4p in a cell even under normal growth conditions. Our gel-mobility shift studies demonstrate a direct physical association between Hac1p and Gcn4p and the sequence motifs UPRE-1 and UPRE-2. Gcn4p and Hac1p are bZIP proteins, a family whose members bind DNA as dimers (Ransone et al. 1993; Hsu et al. 1994). It therefore seems likely that Gcn4p and Hac1p stimulate transcription by binding promoter DNA as a heterodimer, although we cannot rule out higher order complexes. The promoter sequences UPRE-1 and UPRE-2 have identical genetic requirements for activation, but their behavior in response to genetic perturbations is not strictly identical. UPRE-2 can be activated by high levels of GCN4 alone (see Figure 3A), but UPRE-1 cannot. This can be explained by the binding studies, which demonstrate that UPRE-2 (but not UPRE-1) can bind Gcn4p in the absence of Hac1p (see Figure 6B, lanes 1 and 2); indeed, Gcn4p is known to bind DNA as a monomer as well as a dimer (Cranz et al. 2004) and can bind DNA sequences containing even a consensus half-site (Hollenbeck and Oakley 2000). The basis for this differential affinity for Gcn4p is strongly suggested by a refined consensus sequence for UPRE-2, and is illustrated by multiple species alignment of the ERO1 promoter (Figure 7B). We searched for examples of UPRE-2 core sequences that were conserved in UPR target genes across five yeast species, and extracted core and flanking sequences to derive a generalized consensus (see Materials and Methods). The resulting consensus was revealed to be T(C/T)ACGTGT(C/T)(A/C), which differs from the experimentally established UPRE-1 consensus by two nucleotides essential for activity in the KAR2 promoter context. The conserved extended context of UPRE-2 in this promoter aligns with a consensus binding site for Gcn4p defined by computational analysis of the set of promoters that bind Gcn4p in a genome-wide chromatin immunoprecipitation assay (analysis by W. Wang and H. Li, unpublished data; chromatin immunoprecipitations in Lee et al. 2002b). Comparison of multiple alignments of the extended contexts of UPRE-1 and UPRE-2 in the KAR2 and ERO1 promoters (compare Figure 7A and 7B) reveals that the two sequence contexts share a six-nucleotide segment, CGTGTC. The match between UPRE-2 and the Gcn4p consensus is imperfect (five of seven positions), suggesting that the association with Gcn4p and UPR promoters is not identical to the binding of Gcn4p to its “classical” amino acid starvation targets. Rather, these observations suggest that the proposed Gcn4p/Hac1p heterodimeric complex binds to a composite site, of which UPRE-1 and UPRE-2 represent different forms with stronger relative affinities to Hac1p and Gcn4p, respectively. Such a model would explain the residual upregulation of UPRE-1-containing genes in a Δgcn2 mutant (see Figure 3C, histogram j), which retains some expression of Gcn4p. In the absence of Hac1p but in the presence of high concentrations of Gcn4p (e.g., when GCN4 is overexpressed), Gcn4p can bind the UPRE-2 on its own, either as a homodimer or a monomer. Upregulation of Gcn4p by ER Stress The transient upregulation of Gcn4p levels, which we observe upon UPR induction, may therefore serve to increase the transcriptional output of the response, especially early in the response. Most UPR target genes are robustly induced after 15 min of ER stress (Travers et al. 2000); hence, the increase in Gcn4p levels occurs at a time suggestive of a role in the initial response. Gcn4p itself mediates a broad transcriptional program in response to a diverse set of cellular conditions and stresses (Natarajan et al. 2001). The recruitment of Gcn4p therefore provides an opportunity for crosstalk between regulatory pathways and fine-tuning of the magnitude of the UPR. For example, under amino acid starvation, Gcn4p levels are high relative to the baseline of normal growth. In this state, cells with accumulated unfolded ER protein might wish to upregulate ER-associated protein degradation (one output of the UPR; Casagrande et al. 2000; Friedlander et al. 2000; Travers et al. 2000) beyond the level normally provided by the UPR. Such a mechanism might provide for an additional source of amino acids through protein catabolism. Elevated Gcn4p levels and the concomitant increased induction of UPR target genes would serve this need. This view raises the possibility that those genes that most stringently require GCN4 for normal UPR induction are those that are most urgently required by the cell under specific conditions, under which UPR is induced and Gcn4p levels are high for reasons unrelated to ER stress. The relationship between the cellular stress responses that regulate Gcn4p and the potentiation of UPR transcription will therefore be an important subject for future study. The mechanism by which IRE1 and HAC1 mediate the transient increase in Gcn4p remains to be elucidated. Given that Hac1p and Gcn4p are observed in the same complex with DNA, one intriguing possibility is that association with Hac1p serves to stabilize Gcn4p. GCN4 and the Super-UPR: Two Ways to Modulate the UPR We propose a model of UPR transcriptional activation that is illustrated in Figure 8. According to the circuit diagram in Figure 8A, HAC1 mRNA splicing retains its role as the “switch” that turns the UPR on or off. Gcn4p, whose levels appear to be limiting for the extent of gene regulation, would therefore play a role in setting the “gain” or “volume” of the response, perhaps allowing communication from other stress response pathways in the cell. Such a gain control could serve as an adjunct to the “Super-UPR” (S-UPR) gain control described in the accompanying paper (Leber et al. 2004), whereby an IRE1-independent ER surveillance mechanism regulates the transcription of the HAC1 mRNA in response to compound stresses on the secretory pathway. S-UPR induction proceeds unimpaired in Δgcn4 cells, indicating that the S-UPR is mechanistically distinct from the regulation described here (Leber et al. 2004). Whereas the S-UPR monitors conditions of the ER, the GCN4 branch would integrate information gleaned from the cytosol. Both of these gain controls have the potential to act not only as modulators of the magnitude of the response but also as a tuning dial: UPR targets respond differentially to increased level of HAC1 during the S-UPR (see the Class 1, 2, and 3 genes in Figure 6 of Leber et al. [2004]). Likewise, different UPR targets exhibit differential dependence on Gcn4p, as is apparent from the variable upregulation of UPR targets in Δgcn4 and Δgcn2 mutants (see Figure 3C). The observations suggest that increased levels of Gcn4p might serve to differentially upregulate a subset of target genes. Figure 8 Model of Gcn4p/Hac1p Action in the UPR (A) The expanded circuitry of the UPR. The classical UPR (red), the S-UPR (blue), and regulated Gcn4p levels (green) are integrated at target promoters. Transcriptional regulation of HAC1 mRNA levels, providing one level of gain control, is depicted as a rheostat under supervision of a logical AND gate informed by multiple inputs from the ER. Splicing of HAC1 mRNA by Ire1p, providing a binary on/off control, is depicted by a switch. Regulation of Gcn4p levels by Gcn2p under changing cellular conditions adds an additional layer of gain control. Together, activity levels of Hac1p, Gcn4p, and the proposed UPR modulatory factor (Leber et al. 2004) collaborate to determine the magnitude of the transcriptional output signal. (B) Mechanism of Gcn4p/Hac1p action at target promoters. In the absence of Hac1p, Gcn4p is present in the cell as a consequence of baseline activity of Gcn2p. At normal concentrations, Gcn4p is unable to bind or activate a target UPRE, but it may bind when Gcn4p levels are elevated. Upon induction of the UPR, Ire1p is activated and Hac1 is synthesized. Hac1p can bind, but not activate, target UPREs. Binding of target DNA by a Gcn4p/Hac1p heterodimer results in a transcriptionally active complex. Gcn4p levels are upregulated under UPR induction, perhaps as a consequence of stabilization by interaction with Hac1p. From a mechanistic standpoint, ER stress activates Ire1p, which, through nonconventional splicing, induces Hac1p production (Figure 8B). Hac1p can bind to the known UPREs, but by itself forms a protein–DNA complex that is not competent to upregulate transcription. Gcn4p, which is present at a basal level in cells under normal growth conditions as a result of baseline Gcn2p activity, is unable to bind UPREs in the absence of Hac1p. Gcn4p may bind some UPRE sequences, providing a weak bypass of Hac1p, when it is present at physiologically elevated levels. When Hac1p is produced, Gcn4p is recruited to the UPRE, presumably forming a more stable ternary complex containing promoter DNA, Gcn4p, and Hac1p, and transcription is induced. This ternary complex could be established serially, in which case an inactive Hac1p/UPRE complex would be recognized by Gcn4p, or by recognition of the UPRE by a preformed heterodimer of Gcn4p and Hac1p. Conservation between Yeast and Mammalian UPR Advances in the understanding of the metazoan UPR system has been richly informed by the study of yeast. The elucidation of a role for Gcn4p in the yeast UPR allows us to draw even stronger parallels between the yeast and metazoan systems. In higher eukaryotes, the ER-resident transmembrane kinase PERK is activated by protein unfolding. PERK's cytosolic domain is homologous to Gcn2p and likewise phosphorylates eIF-2α, thereby downregulating general translation but also promoting the selective translation of mRNAs containing upstream ORFs in their 5′ UTR sequences. One of these mRNAs encodes ATF-4, a bZIP transcription factor that represents the metazoan ortholog of Gcn4p. Intriguingly, and in strict analogy to the joint action of Gcn4p and Hac1p proposed here, ATF-4 in metazoan cells collaborates with the Hac1p ortholog XBP-1 to stimulate UPR target gene transcription. The analogies between the roles of Gcn4p/Hac1p/Gcn2p and ATF-4/XBP-1/PERK suggest that the function of these proteins has been amazingly conserved in the UPR, although the nature of the connections between pathway components may have been adapted over evolutionary time: Yeast does not have an identified PERK ortholog that feeds ER-derived information into the GCN4 branch of the network. Another parallel concerns S-UPR regulation. In the accompanying paper, Leber et al. (2004) demonstrate that compound secretory stress upregulates HAC1 mRNA. The mode of modulation of the UPR by the superimposed control of the S-UPR bears a resemblance to the known function of another metazoan transcription factor, ATF-6, which is activated by regulated proteolysis in response to ER stress and in turn upregulates XBP-1 transcription. In comparison to the metazoan UPR, where multiple ER-resident proteins communicate in a seemingly parallel way with multiple downstream transcription factors, Ire1p and Hac1p remain the central players in the yeast UPR. GCN4 and the S-UPR provide modulatory functions. Nonetheless, the addition to the repertoire of the yeast UPR effectors of an additional transcription factor (Gcn4p) and of a mechanism for transcriptional regulation of Hac1p (S-UPR; Leber et al. 2004) suggests that the UPR functions as a regulatory network, with its opportunities for crosstalk with other pathways and regulation by cellular state. But most importantly, both the central players and the connectivity of the circuits involved appear to be conserved among eukaryotes and evolutionarily ancient. Materials and Methods Computational and quantitative methods To build the dictionary of putative regulatory elements for UPR target genes, we first extracted the 600-bp upstream regions of all UPR target genes. To get rid of simple repeats unlikely to be regulatory elements (such as AT-rich repeats and transposable elements), we removed exact repeats of lengths 15 bp or longer, and kept the remaining fragments of lengths longer than 50 bp. What remained was the input sequence for the dictionary construction. We used the MobyDick algorithm based on probabilistic segmentation (Bussemaker et al. 2000b) to build a dictionary of putative regulatory elements. MobyDick builds the dictionary by iterating through fitting and testing steps. Starting with the frequencies of single bases, the algorithm finds overrepresented two-nucleotide pairs (testing step), adds them to the dictionary, determines their probabilities by maximizing the likelihood of observing the sequence data (fitting step), and continues to build larger fragments iteratively. Adjustable parameters were as follows: L, the maximum word length, was set to 8, and MaxP, the probability of seeing at least one false positive at each testing step when all words of length up to L are tested, was set to 0.999 (relaxed cutoff). MobyDick generated a dictionary of 328 words. We filtered out words that were too short, appeared in too many copies (such as AT-rich short repeats), or were of low quality (the algorithm calculates a quality factor for each word describing how likely it is that the word can be made by chance from shorter words). With the filters number_of_copies < 200, length > 4, and quality_factor > 0.2, we obtained 201 words. Using the filtered dictionary, we grouped similar words into motifs using the clustering algorithm CAST (Ben-Dor et al. 1999), as follows: We first computed pairwise alignment scores for all the words in the dictionary, using gapless alignment with a scoring scheme derived from a simple mutation model. The model assumes that a base x mutates to any other given base y with probability p/3, and remains the same base with a probability (1 − p). The score for a pair x–y is given by the log-odds-ratio of observing the pair under the mutation model versus observing the pair at random. With the choice of p = 0.5 (the result is insensitive to the actual p value chosen as long as p is much smaller than 0.75), a matching pair scores ln(2), and a mismatch scores ln(2/3). We normalized the scores to fall between 0 and 1 by the largest score. We then used the CAST algorithm to group words into clusters, with the threshold parameter set at 0.7 (the lower bound of the normalized score averaged over all pairs in a cluster). This procedure generated 109 motifs. To test which motifs are significantly overrepresented in the promoters of UPR target genes, we counted for each motif the total number of occurrences in all promoters, and calculated the expected number of occurrences Nexp in the UPR target gene promoters based on the genome-wide frequencies. We then counted the observed number of occurrences Nobs of the motif in the promoters of UPR target genes. We used Poisson statistics to calculate the probability P of observing a number of occurrences equal to or greater than Nobs by chance, based on Nexp. The test based on Poisson statistics is a very good approximation of the more rigorous test based on the binomial distribution, where the probability P is the probability of seeing a specific instance of the motif in the UPR gene set and the total number of trials Nt is the total number of copies of the motif in the genome. Since P is small (0.059) and Nt is large (ranging from approximately ten to approximately 1000) but the product Nexp is finite, the resulting distribution is well approximated by a Poisson distribution with mean = Nexp. To derive a general consensus for UPRE-2 that includes context information beyond the core motif, we took the five-nucleotide core ACGTG from the Motif 1 alignment (see Figure 1B) and searched the promoters of UPR target genes for the occurrences of this core motif that are conserved across five yeast species. We first took the sequence data for S. cerevisiae, S. bayanus, S. mikatae, S. paradoxus, and S. kudriavevii (Cliften et al. 2003; Kellis et al. 2003) and performed multiple sequence alignment on all the orthologous promoters. We then searched for conserved blocks on both strands where ACGTG occurs in all species and is correctly aligned. We found 60 instances of conserved blocks in UPR target gene promoters for which multiple sequence alignment data were available. We then extracted ACGTG plus 10-bp flanking sequences on both side in S. cerevisiae and performed a multiple local sequence alignment of the S. cerevisiae sequences from each of the 60 conserved blocks using the Consensus algorithm (Hertz and Stormo 1999), setting matrix_width to 15. The result of the alignment was a position-specific frequency matrix. We derived a consensus sequence from the matrix using the convention by Cavener (1987). The alignment matrix and raw sequence data are available in Table S3. Plasmids and recombinant DNA DNA manipulations, cloning, and yeast culture were performed as previously described (Sherman et al. 1986; Ausubel 1988; Guthrie and Fink 2002) unless otherwise noted. UPRE reporter constructs (used in Figures 2A, 3A, 3B, and 5) were based on the plasmid pPW344/pJC104 (Cox et al. 1993), which contains a triple repeat of the KAR2-derived UPRE; this plasmid was used as the UPRE-1 reporter in all experiments. To construct UPRE reporters used to test Motifs 1–8, we removed the UPRE-1 repeat from pPW344 by digestion with BglII and XhoI, and replaced it with a triple repeat of a 15-nucleotide sequence encompassing the motif in question and the flanking sequence context. Source sequences were chosen from promoters that exhibited robust induction by the UPR (Travers et al. 2000) and, if possible, did not contain a match to the canonical (KAR2-derived) UPRE. Intact promoter reporter constructs (pPW668–pPW671) used in Figure 2B and 2C were also based on plasmid pPW344. Here the promoter of pPW344 (BamHI/BglII fragment) was replaced by a single PCR fragment spanning the approximately 600 nucleotides immediately upstream of either the ERO1 or DHH1 initiation codon, or by two fragments spanning the same sequence but with the UPRE motif replaced by a restriction site. The high-copy GCN4 plasmid (pPW672) used in Figure 3A consists of the region plus1000 nucleotides one either side of the GCN4 ORF. Source sequence contexts, olignucleotide sequences, and select PCR primers are compiled in Table S4. The plasmids expressing the activated allele of HAC1 used in Figure 5 (pPW322/pRC43) and the N-terminally HA-tagged allele of HAC1 (pPW353/pJC316) used in Figure 6B were as previously described (Cox and Walter 1996). Knockouts of GCN4 and GCN2 and the integrated GCN4-myc were constructed by PCR cassette/generic primer mutagenesis (Longtine et al. 1998). Yeast strains All base strains used in this study are enumerated in Table 1. As appropriate, these strains were transformed with plasmids from Table 2 for use in experiments. Table 1 Yeast Strains Table 2 Yeast Plasmids Cell culture and growth conditions For all experiments, samples were diluted from saturated overnight cultures and regrown to midlog phase (OD600 = 0.5) prior to addition of drug. DTT (Sigma, St. Louis, Missouri, United States) was added to cultures to a final concentration of 2 mM. Tm (Boehringer Mannheim, Indianapolis, Indiana, United States) was added to cultures to a final concentration of 1 μg/ml. 3-AT (Sigma) was added to cultures to a final concentration of 10 mM. All 3-AT treatments were performed on strains WT for the HIS3 gene; for histidine-deprived cultures, overnight cultures were washed three times in SD-histidine, then diluted to low density in SD-histidine and grown to midlog phase before the addition of the drug. To assay β-galactosidase activity on solid growth media, we overlaid plates with buffered soft agar containing X-gal (Sigma) as described previously (Cox and Walter 1996). For liquid cultures, we used a colorimetric ONPG assay (Holley and Yamamoto 1995). Gene expression profiling. Strains were grown in YPD (pH 5.4) as in Travers et al. (2000) to midlog phase (OD = 0.5) and then either treated with 2 mM DTT or left untreated. RNA was extracted as described by Ruegsegger et al. (2001), and mRNA was purified with a PolyATtract kit (Promega, Madison, Wisconsin, United States). Microarray analysis used yeast spotted-cDNA ORF arrays printed at the University of California, San Francisco, Core Center for Genomics and Proteomics (http://derisilab.ucsf.edu/more) and was performed as described previously (Carroll et al. 2001). Measurements reported are the average of three independent experiments. We tested the statistical significance of the induction for the three gene sets (UPRE-1, UPRE-2, and UPRE-3 genes) in four different strains (WT, Δire1,Δgcn4, and Δgcn2) using a z-score scheme. For a given gene set and a given strain, we calculated the average fold induction for genes in the set and compared it to the value for the genome overall. The null hypothesis was that the selected gene set was no different from a randomly selected set (same total number) from the genome overall. Under this hypothesis, the average μ has a distribution well approximated by a normal distribution (due to the central limit theorem) with mean μgenome and standard deviation σ/√(Nset), where Nset is the total number of genes in the test set. We computed a z-score, z=√(Nset)(μ−μgenome)/σ, which should have a standard normal distribution (zero mean and unit variance) under the null hypothesis. The P value was calculated by integrating the standard normal curve from z to infinity. Isolation and detection of protein. Protein preparation, electrophoresis, and Western blotting proceeded as described in the accompanying paper (Leber et al. 2004). Gcn4p-myc (see Figure 5A) was detected using a mouse anti-myc monoclonal antibody (Molecular Probes, Eugene, Oregon, United States); eIF-2α-phosphate was detected by a commercial phospho-specific mouse polyclonal (Upstate Biotechnology, Lake Placid, New York, United States). Gel retardation analysis. Gel shifts were performed as previously described (Cox and Walter 1996) except that we found it important to elevate the acrylamide concentration to 5% and lower the in-gel glycerol concentration to 4%. UPRE-1 oligo and UPRE-1 mutant are based on sequences previously described (Cox and Walter 1996). UPRE-2 oligo is a fragment of the ERO1 promoter centered around the UAS. UPRE-2 mutant is a point mutation that does not support transcription in an artificial promoter context (unpublished data). For sequences, see Table S4. Competition experiments used a 100-fold excess of unlabeled oligonucleotide. Supporting Information Table S1 Dictionary of “Words” Compiled by MobyDick This table contains an alphabetical list of the dictionary “words” compiled by the MobyDick algorithm from the “text” comprising the promoters of UPRE target genes. Associated statistics for each word are as follows: N, the average number of times the string is delimited as a word among all segmentations of the data; Xi, the number of matches of the word anywhere in the text; p, the frequency of drawing the word from the dictionary, optimized over all words to give the maximum likelihood of observing the text; Z = p + ps, where ps is the probability with which the word can be made by combining shorter words from the dictionary; sig = significance = Np/sqrt(N[Z − p]). (10 KB TXT). Click here for additional data file. Table S2 Ranked Listing of the Motifs Assembled by Clustering from the Dictionary Words Ntot is the number of times a given motif appeared in the promoters of the genome overall; Nexp is the number of times one would expect a given motif to appear in the 381 promoters of UPR target genes if the motif were distributed randomly throughout all promoters; Nobs is the number of times a given motif actually appears in the target gene promoters; and −log10 P is a measure of overrepresentation based on Poisson statistics (P is the likelihood that a given observed distribution would occur by chance). (3 KB TXT). Click here for additional data file. Table S3 UPRE-Containing Promoter Alignments This table contains CLUSTALW alignments for the KAR2 and ERO1 promoters, derived from S. cerevisiae and related budding yeasts. Asterisk indicates 100% conserved residues. Scer, S. cerevisiae; Skud, S. kudriavevii; Spar, S. paradoxus; Smik, S. mikatae; Sbay, S. bayanus. (8 KB TXT). Click here for additional data file. Table S4 Oligonucleotide Sequences and Cloning Schemes This table contains the sequences of primers and olignonucleotide sequences used in construction of plasmids for this study, as well as oligonucleotide sequences used for probes in the gel-shift analysis. (38 KB DOC). Click here for additional data file. Accession Numbers The GenBank accession numbers of the gene products discussed in this paper are Dhh1p (NP_010121), Ero1p (NP_013576), Gcn4p (NP_010907), Gcn2p (NP_010569), Hac1p (NP_011946), and Ire1p (NP_116622). Microarray data can be accessed at the Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) database as platform number GPL1001 and sample numbers GSM16985–GSM1988. The authors wish to thank Jason Bricker, Isabella Halama, Jess Leber, and Feroz Papa for enthusiastic technical assistance with all experiments; Adam Carroll for particular assistance with microarray hybridization experiments; Sebastian Bernáles, Jason Brickner, Jess Leber, and Feroz Papa for close readings of the manuscript; and Jeffery Cox, Steven McCarroll, Aaron McGee, Jonathan Weissman, and past and present members of the Walter lab for expert advice and valuable discussion throughout the course of the project. This work was supported by an Howard Hughes Medical Institute predoctoral fellowship and a Burroughs Welcome Fund/Program in Quantitative Biology predoctoral fellowship for CP; by a Sandler's opportunity award and a Packard Science and Engineering Fellowship to HL; and by grants from the National Institutes of Health to HL and PW. PW is an Investigator of the Howard Hughes Medical Institute. Conflicts of interest. The authors declare that no conflicts of interest exist. Author contributions. CP and PW conceived and designed the experiments. CP performed the experiments. HL analyzed the data. CP, HL, and PW wrote the manuscript. Academic Editor: Steven McKnight, University of Texas Southwestern Citation: Patil CK, Li H, Walter P (2004) Gcn4p and novel upstream activating sequences regulate targets of the unfolded protein response. PLoS Biol 2(8): e246. Abbreviations 3-AT3-aminotriazole DTTdithiothreitol ERendoplasmic reticulum ORFopen reading frame S-UPRSuper-UPR Tmtunicamycin UASupstream activating sequence UPRunfolded protein response UPREunfolded protein response element WTwild-type. ==== Refs References Albrecht G Mosch HU Hoffmann B Reusser U Braus GH Monitoring the Gcn4 protein-mediated response in the yeast Saccharomyces cerevisiae J Biol Chem 1998 273 12696 12702 9582292 Ausubel FM editor Current protocols in molecular biology, Volumes 1–4 1988 New York Greene/Wiley Interscience Ben-Dor A Shamir R Yakhini Z Clustering gene expression patterns J Comput Biol 1999 6 281 297 10582567 Bussemaker HJ Li H Siggia ED Building a dictionary for genomes: Identification of presumptive regulatory sites by statistical analysis Proc Natl Acad Sci U S A 2000a 97 10096 10100 10944202 Bussemaker HJ Li H Siggia ED Regulatory element detection using a probabilistic segmentation model Proc Int Conf Intell Syst Mol Biol 2000b 8 67 74 10977067 Calfon M Zeng H Urano F Till JH Hubbard SR IRE1 couples endoplasmic reticulum load to secretory capacity by processing the XBP-1 mRNA Nature 2002 415 92 96 11780124 Carroll AS Bishop AC DeRisi JL Shokat KM O'Shea EK Chemical inhibition of the Pho85 cyclin-dependent kinase reveals a role in the environmental stress response Proc Natl Acad Sci U S A 2001 98 12578 12583 11675494 Casagrande R Stern P Diehn M Shamu C Osario M Degradation of proteins from the ER of S. cerevisiae requires an intact unfolded protein response pathway Mol Cell 2000 5 729 735 10882108 Cavener DR Comparison of the consensus sequence flanking translational start sites in Drosophila and vertebrates Nucleic Acids Res 1987 15 1353 1361 3822832 Chapman RE Walter P Translational attenuation mediated by an mRNA intron Curr Biol 1997 7 850 859 9382810 Cherkasova VA Hinnebusch AG Translational control by TOR and TAP42 through dephosphorylation of eIF2alpha kinase GCN2 Genes Dev 2003 17 859 872 12654728 Cliften P Sudarsanam P Desikan A Fulton L Fulton B Finding functional features in Saccharomyces genomes by phylogenetic footprinting Science 2003 301 71 76 12775844 Cox JS Walter P A novel mechanism for regulating activity of a transcription factor that controls the unfolded protein response Cell 1996 87 391 404 8898193 Cox JS Shamu CE Walter P Transcriptional induction of genes encoding endoplasmic reticulum resident proteins requires a transmembrane protein kinase Cell 1993 73 1197 1206 8513503 Cranz S Berger C Baici A Jelesarov I Bosshard HR Monomeric and dimeric bZIP transcription factor GCN4 bind at the same rate to their target DNA site Biochemistry 2004 43 718 727 14730976 Dever TE Chen JJ Barber GN Cigan AM Feng L Mammalian eukaryotic initiation factor 2 alpha kinases functionally substitute for GCN2 protein kinase in the GCN4 translational control mechanism of yeast Proc Natl Acad Sci U S A 1993 90 4616 4620 8099443 Diallinas G Thireos G Genetic and biochemical evidence for yeast GCN2 protein kinase polymerization Gene 1994 143 21 27 8200534 Friedlander R Jarosch E Urban J Volkwein C Sommer T A regulatory link between ER-associated protein degradation and the unfolded-protein response Nat Cell Biol 2000 2 379 384 10878801 Guarente L Mason T Heme regulates transcription of the CYC1 gene of S. cerevisiae via an upstream activation site Cell 1983 32 1279 1286 6301690 Guthrie C Fink GR editors Guide to yeast genetics and molecular and cell biology, Volume B 2002 Amsterdam Academic Press 657 Harding HP Zhang Y Ron D Protein translation and folding are coupled by an endoplasmic-reticulum-resident kinase Nature 1999 397 271 274 9930704 Harding HP Novoa I Zhang Y Zeng H Wek R Regulated translation initiation controls stress-induced gene expression in mammalian cells Mol Cell 2000a 6 1099 1108 11106749 Harding HP Zhang Y Bertolotti A Zeng H Ron D Perk is essential for translational regulation and cell survival during the unfolded protein response Mol Cell 2000b 5 897 904 10882126 Harding HP Zhang Y Zeng H Novoa I Lu PD An integrated stress response regulates amino acid metabolism and resistance to oxidative stress Mol Cell 2003 11 619 633 12667446 Haze K Yoshida H Yanagi H Yura T Mori K Mammalian transcription factor ATF6 is synthesized as a transmembrane protein and activated by proteolysis in response to endoplasmic reticulum stress Mol Biol Cell 1999 10 3787 3799 10564271 Hertz GZ Stormo GD Identifying DNA and protein patterns with statistically significant alignments of multiple sequences Bioinformatics 1999 15 563 577 10487864 Hinnebusch AG Gene-specific translational control of the yeast GCN4 gene by phosphorylation of eukaryotic initiation factor 2 Mol Microbiol 1993 10 215 223 7934812 Hinnebusch AG Translational regulation of yeast GCN4: A window on factors that control initiator-trna binding to the ribosome J Biol Chem 1997 272 21661 21664 9268289 Hollenbeck JJ Oakley MG GCN4 binds with high affinity to DNA sequences containing a single consensus half-site Biochemistry 2000 39 6380 6389 10828952 Holley SJ Yamamoto KR A role for Hsp90 in retinoid receptor signal transduction Mol Biol Cell 1995 6 1833 1842 8590809 Hsu W Kerppola TK Chen PL Curran T Chen-Kiang S Fos and Jun repress transcription activation by NF-IL6 through association at the basic zipper region Mol Cell Biol 1994 14 268 276 8264594 Kawahara T Yanagi H Yura T Mori K Endoplasmic reticulum stress-induced mRNA splicing permits synthesis of transcription factor Hac1p/Ern4p that activates the unfolded protein response Mol Biol Cell 1997 8 1845 1862 9348528 Kellis M Patterson N Endrizzi M Birren B Lander ES Sequencing and comparison of yeast species to identify genes and regulatory elements Nature 2003 423 241 254 12748633 Kohno K Normington K Sambrook J Gething MJ Mori K The promoter region of the yeast KAR2 (BiP) gene contains a regulatory domain that responds to the presence of unfolded proteins in the endoplasmic reticulum Mol Cell Biol 1993 13 877 890 8423809 Leber JH Bernáles S Walter P IRE1-independent Gain Control of the Unfolded Protein Response PLoS Biol 2004 2 e235 10.1371/journal.pbio.0020235 15314654 Lee K Tirasophon W Shen X Michalak M Prywes R IRE1-mediated unconventional mRNA splicing and S2P-mediated ATF6 cleavage merge to regulate XBP1 in signaling the unfolded protein response Genes Dev 2002a 16 452 466 11850408 Lee TI Rinaldi NJ Robert F Odom DT Bar-Joseph Z Transcriptional regulatory networks in Saccharomyces cerevisiae Science 2002b 298 799 804 12399584 Liu CY Schroder M Kaufman RJ Ligand-independent dimerization activates the stress response kinases IRE1 and PERK in the lumen of the endoplasmic reticulum J Biol Chem 2000 275 24881 24885 10835430 Longtine MS McKenzieA 3rd Demarini DJ Shah NG Wach A Additional modules for versatile and economical PCR-based gene deletion and modification in Saccharomyces cerevisiae Yeast 1998 14 953 961 9717241 Ma Y Brewer JW Diehl JA Hendershot LM Two distinct stress signaling pathways converge upon the CHOP promoter during the mammalian unfolded protein response J Mol Biol 2002 318 1351 1365 12083523 Miller AM Sternglanz R Nasmyth KA The role of DNA replication in the repression of the yeast mating-type silent loci Cold Spring Harb Symp Quant Biol 1984 49 105 113 6397296 Miyoshi K Katayama T Imaizumi K Taniguchi M Mori Y Characterization of mouse Ire1 alpha: Cloning, mRNA localization in the brain and functional analysis in a neural cell line Brain Res Mol Brain Res 2000 85 68 76 11146108 Mori K Sant A Kohno K Normington K Gething MJ A 22 bp cis-acting element is necessary and sufficient for the induction of the yeast KAR2 (BiP) gene by unfolded proteins Embo J 1992 11 2583 2593 1628622 Mori K Ma W Gething MJ Sambrook J A transmembrane protein with a cdc2+/CDC28-related kinase activity is required for signaling from the ER to the nucleus Cell 1993 74 743 756 8358794 Mori K Kawahara T Yoshida H Yanagi H Yura T Signalling from endoplasmic reticulum to nucleus: Transcription factor with a basic-leucine zipper motif is required for the unfolded protein-response pathway Genes Cells 1996 1 803 817 9077435 Mori K Ogawa N Kawahara T Yanagi H Yura T Palindrome with spacer of one nucleotide is characteristic of the cis-acting unfolded protein response element in Saccharomyces cerevisiae J Biol Chem 1998 273 9912 9920 9545334 Natarajan K Meyer MR Jackson BM Slade D Roberts C Transcriptional profiling shows that Gcn4p is a master regulator of gene expression during amino acid starvation in yeast Mol Cell Biol 2001 21 4347 4368 11390663 Patil C Walter P Intracellular signaling from the endoplasmic reticulum to the nucleus: The unfolded protein response in yeast and mammals Curr Opin Cell Biol 2001 13 349 355 11343907 Ransone LJ Kerr LD Schmitt MJ Wamsley P Verma IM The bZIP domains of Fos and Jun mediate a physical association with the TATA box-binding protein Gene Expr 1993 3 37 48 7685215 Ruegsegger U Leber JH Walter P Block of HAC1 mRNA translation by long-range base pairing is released by cytoplasmic splicing upon induction of the unfolded protein response Cell 2001 107 103 114 11595189 Sherman F Fink GR Hicks JB editors Methods in yeast genetics 1986 Woodbury (New York) Cold Spring Harbor Laboratory Press 180 Sidrauski C Walter P The transmembrane kinase Ire1p is a site-specific endonuclease that initiates mRNA splicing in the unfolded protein response Cell 1997 90 1031 1039 9323131 Sidrauski C Cox JS Walter P tRNA ligase is required for regulated mRNA splicing in the unfolded protein response Cell 1996 87 405 413 8898194 Steiner H Winkler E Shearman MS Prywes R Haass C Endoproteolysis of the ER stress transducer ATF6 in the presence of functionally inactive presenilins Neurobiol Dis 2001 8 717 722 11493036 Stitzel ML Durso R Reese JC The proteasome regulates the UV-induced activation of the AP-1-like transcription factor Gcn4 Genes Dev 2001 15 128 133 11157770 Tavernarakis N Thireos G Genetic evidence for functional specificity of the yeast GCN2 kinase Mol Gen Genet 1996 251 613 618 8709969 Travers KJ Patil CK Wodicka L Lockhart DJ Weissman JS Functional and genomic analyses reveal an essential coordination between the unfolded protein response and ER-associated degradation Cell 2000 101 249 258 10847680 Urano F Bertolotti A Ron D IRE1 and efferent signaling from the endoplasmic reticulum J Cell Sci 2000 113 3697 3702 11034898 Wang XZ Harding HP Zhang Y Jolicoeur EM Kuroda M Cloning of mammalian Ire1 reveals diversity in the ER stress responses EMBO J 1998 17 5708 5717 9755171 Wang Y Shen J Arenzana N Tirasophon W Kaufman RJ Activation of ATF6 and an ATF6 DNA binding site by the endoplasmic reticulum stress response J Biol Chem 2000 275 27013 27020 10856300 Yang R Wek SA Wek RC Glucose limitation induces GCN4 translation by activation of Gcn2 protein kinase Mol Cell Biol 2000 20 2706 2717 10733573 Ye J Rawson RB Komuro R Chen X Dave UP ER stress induces cleavage of membrane-bound ATF6 by the same proteases that process SREBPs Mol Cell 2000 6 1355 1364 11163209 Yoshida H Okada T Haze K Yanagi H Yura T Endoplasmic reticulum stress-induced formation of transcription factor complex ERSF including NF-Y (CBF) and activating transcription factors 6alpha and 6beta that activates the mammalian unfolded protein response Mol Cell Biol 2001 21 1239 1248 11158310

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PLoS Biol. 2004 Aug 17; 2(8):e246

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10.1371/journal.pbio.0020246

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020250SynopsisBiotechnologyEcologyGenetics/Genomics/Gene TherapyPlant SciencePlantsInsectsNicotine Keeps Leaf-Loving Herbivores at Bay Synopsis8 2004 17 8 2004 17 8 2004 2 8 e250Copyright: © 2004 Public Library of Science.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. Nicotine's Defensive Function in Nature ==== Body Sooner or later, a gardener looking for “nontoxic” ways to control the inevitable attack on a favorite plant will discover the nicotine remedy. Steep a cup of loose tobacco in a gallon of water, let it sit overnight, strain, and spray away. Caterpillars, aphids, and a diverse array of insects predisposed to devouring plants will soon abandon your vegetables and flowers in search of less disagreeable forage. The ultimate sitting duck, plants rely on an arsenal of chemical metabolites to fend off predators. Many of these chemicals harbor anti-herbivore properties, which have been exploited for commercial use. Nicotine, it turns out, is so toxic that it was one of the first chemicals used in agricultural insecticides. It's not clear, though, whether these toxic metabolites are really defending plants against hungry herbivores in their natural environment, especially since many insects can tolerate various plant chemicals and sometimes even incorporate them into their own defenses. Though scientists have cataloged a long list of these presumed resistance traits, there's no evidence that they offer plants a competitive advantage against their leaf-covetous foes in nature. Spodoptera exigua larva feeding on Nicotiana attenuata With plant and plant-eater engaged in an ever-escalating battle of evolutionary one-upmanship and with plants capable of producing an array of defensive responses, teasing out the predator-resistant effects of individual plant metabolites has proved challenging. Theoretically, one could track down a resistance gene by breeding plants that are genetically identical save for the gene that controls expression of a particular resistance trait. In practice, however, traditional breeding techniques aren't that precise and tend to generate additional variations in genomic regions that are linked to the target gene and that might affect resistance as well. The tools of genetic engineering have largely overcome such limitations, allowing scientists far greater control and specificity. Following this approach, Ian Baldwin and colleagues use transgenic silencing (which introduces gene “constructs” into an organism to inactivate a gene of interest) to investigate a single resistance trait, nicotine production. Even though nicotine is one of the best-studied putative resistance traits, its specific role has been unclear. To isolate the resistance effects of nicotine from possible confounding factors, Baldwin and colleagues blocked nicotine production in the Nicotiana attenuata tobacco plant. Focusing on an enzyme, called putrescine methyl transferase (PMT), central to nicotine biosynthesis, the authors used two techniques that interfere with PMT production by silencing the gene, pmt, that encodes the enzyme. One of the techniques (which adds genetic sequences called “inverted repeats” to gene fragments) proved far more effective at silencing pmt, producing 29 out of 34 plant lines with only 3%–4% of normal nicotine levels. With suitably nicotine-deprived plants, Baldwin and colleagues could directly test nicotine's role in tobacco fitness. They transplanted the transgenic plants, along with nonmutant cultivated plants, in southwestern Utah, N. attenuata's native habitat. A subset of the plants was also treated with a chemical known to increase both nicotine content and resistance to herbivore attack. Predictably, several of the plant's natural insect enemies made an appearance. Untreated nicotine-deficient transgenic plants fared the worst, losing twice as much foliage to herbivores as nonmutant plants. Transgenic plants treated with the chemical boost performed much better, showing about the same amount of damage as the nonmutants. Interestingly, tobacco hornworms—which, as their name implies, feed primarily on tobacco—preferred nicotine-free plants when given the choice. Though the worms have evolved strategies for coping with nicotine's deleterious effects, these adaptations come at a price: worms feeding on nicotine-deficient tobacco grew bigger and faster than those feeding on plants with normal nicotine levels. These results clearly show that nicotine protects tobacco plants in their native habitat, the authors conclude, and that tobacco-chewing insects “prefer low nicotine diets.” Removing nicotine from the equation reveals the relentless pressure that plants face from herbivores. Without such defenses, plants would be unceremoniously eliminated posthaste, leaving a world without greenery, not to mention oxygen. But these experiments also demonstrate the unprecedented power of transgenic tools to peel back the obfuscating layers inherent in ecological interactions to reveal the fundamental properties of those interactions. And that scientists working to unravel the tangled web of ecological interactions would do well to take advantage of the longest running experiment on earth—the natural environment.

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PLoS Biol. 2004 Aug 17; 2(8):e250

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10.1371/journal.pbio.0020250

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020254SynopsisDevelopmentGenetics/Genomics/Gene TherapyNeuroscienceMus (Mouse)Finding Mutations That Disrupt Cortical Development Synopsis8 2004 17 8 2004 17 8 2004 2 8 e254Copyright: © 2004 Public Library of Science.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. A Focused and Efficient Genetic Screening Strategy in the Mouse: Identification of Mutations That Disrupt Cortical Development ==== Body As the presumed “seat of consciousness,” the cerebral cortex mediates the higher-level cognitive processing—such as abstract thought—that humans like to think distinguishes them from other animals. The cerebral cortex is, in fact, significantly larger in the human brain and has far more “columns” than it does in other mammals, particularly compared to the rat, a traditional model for brain study. Neurons in these cortical columns have similar response properties and form fundamental units of brain processing. It is the larger brain surface area, accommodating a greater number of cortical columns, that gives humans the computational edge. By studying the genetic and molecular agents of cortex development, scientists hope to understand the nature and extent of cortical cognitive function and identify effective therapies to repair brain injury and disease. Analyses of mutant mice have provided insights into the mechanisms controlling cerebral cortex development, but many details of cortical development remain to be revealed. Identifying individual molecules and genes involved in discrete brain processes is particularly difficult given the complexity of brain structure and function. Geneticists have traditionally linked genes to specific biological pathways by first screening large numbers of individuals of a species for unusual physical traits (phenotypes) and then determining the genetic makeup of these mutants to home in on the faulty gene. This approach, called forward genetics, typically requires large numbers of individuals to find unusual phenotypes and so has traditionally focused on fast-breeding organisms like zebrafish and fruitflies. But zebrafish and fruitflies are unlikely to reveal the secrets of higher consciousness. Now Andrew Peterson and colleagues have updated the forward genetic screen and added a new resource to the neuroscientist's “brain dissection” toolkit. Their approach, which labels specific populations of neurons with protein “reporters,” offers a novel way to find mutations in developing neurons and to identify mutations that interfere with cerebral cortex development. The reporter used here highlights mutations that disrupt interneuron migration into the cortex as well as those that affect cortex growth and morphology. (Interneurons are one of the primary types of cortical neurons.) Distribution of GABAergic interneurons in wild-type (top) and mutant (bottom) cortex Like most forward genetic approaches, the researchers started with a genetically well-characterized breed, then used a chemical mutagen to damage the organism's DNA. After two or three rounds of breeding, the researchers looked for cortical-related defects in the developing embryos. In this case, however, the region of the mouse brain that gives rise to developing interneurons was labeled in the original mice. Thus, when the researchers screened for mutants with defects associated with forebrain development and interneuron migration, they could easily find the cells and genes involved. The screen identified thirteen mutations affecting cortical development and interneuron migration. (Developing neurons travel along the fibers of other brain cells before reaching their ultimate destination in the brain.) Three mutations are variants of genes known to play a role in cortical development; nine mutations were in genes that had not been linked to cortical development before. The screen described here takes advantage of a chemical mutagen (called ENU) that induces mutations at a single base pair, or nucleotide, in DNA. These mutations tend to have quite selective effects on protein function—by changing the composition of a single domain—which can provide information on how the protein should normally function and highlight its role in a particular process. The selective nature of ENU, the authors argue, offers new information about how the mutated genes identified here function in cortical development and how these putative roles might be tested. Altogether, the results suggest that this type of focused screening, so long a resource in fly genetics, can be a powerful tool in mammalian biology as well. That the strategy outlined here could identify novel mutations in a process as complicated as cerebral cortex development suggests that it could do the same for a broad range of biological processes. If the success of other model systems moving in this direction is any indication, this new strategy in the mouse offers researchers a powerful resource for identifying the genetic underpinnings of living systems.

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2021-01-05 08:26:26

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PLoS Biol. 2004 Aug 17; 2(8):e254

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10.1371/journal.pbio.0020254

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020255SynopsisCell BiologyDevelopmentImmunologyDrosophilaA Protein Required for Fruitflies to Dispatch Wasp Parasites Synopsis8 2004 17 8 2004 17 8 2004 2 8 e255Copyright: © 2004 Public Library of Science.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. Cellular Immune Response to Parasitization in Drosophila Requires the EBF Orthologue Collier ==== Body For a three-millimeter invertebrate, the Drosophila fruitfly has a remarkably sophisticated immune system. Granted, it can't customize an immune response by grooming cells to “remember” and target specific pathogens. But it can rally the less specialized tools of innate immunity to fight disease and infection, and in so doing draws on several aspects of blood cell development (called hematopoiesis)—the foundation of the cellular immune response—also found in vertebrates. In fruitflies, as in vertebrates, hematopoiesis occurs in distinct stages and locations, with nascent cell populations migrating to establish new hematopoietic frontiers. A population of progenitor cells generates all the blood cell types in the organism. These cells arise in two distinct waves and in two distinct locations, with their progeny differentiating into the specialized tissues and organs of the hematopoietic system. In mammals, these organs include the liver and bone marrow, an ongoing source of blood cells after embryogenesis. In fruitflies, the definitive hematopoietic organ is the lymph gland, which churns out three types of blood cells: plasmatocytes and crystal cells, which are also produced by embryonic hematopoietic precursors, and lamellocytes. Plasmatocytes account for up to 95% of circulating fruitfly blood cells and act much like their mammalian counterpart, the macrophage, engulfing substances deemed foreign and dangerous. Crystal cells account for most of the rest and are involved in melanization reactions, which trigger mechanisms involved in containing and killing invading microbes. Unlike plasmatocytes and crystal cells, lamellocytes appear en masse and only under certain conditions, such as the unwelcome appearance of parasitic wasp eggs. Lamellocytes encapsulate and neutralize the invader. Cellular immune response to parasitization in Drosophila requires the EBF ortholog Collier Molecular factors involved in determining the fate of hematopoietic cells have been identified for plasmatocytes and crystal cells but not for lamellocytes—until now. In a search for genes that might precipitate lamellocyte differentiation, Marie Meister, Alain Vincent, and colleagues homed in on a protein, called Collier (Col), that is expressed in lymph glands at the end of embryogenesis. Col is quite similar to a mammalian protein, called Early B-cell Factor (EBF), that controls B-cell development in mice. Both proteins are transcription factors, exerting control by initiating gene transcription. To investigate Col's part in lamellocyte development, the researchers had to get around the fact that mutations that render Col nonfunctional eventually kill the embryo. Using tricks of the genetics trade, Meister and colleagues generated fly larvae that survive loss-of-function mutations in the gene that encodes Col, allowing them to study its role in hematopoiesis. The mutants had normal amounts of circulating plasmatocytes and crystal cells, but when exposed to parasitic wasp eggs, could not muster the requisite response: lamellocyte production. With no lamellocytes, fly larvae had no means of protection against encroaching wasp eggs, which, uncontested, developed into parasitic larvae. The flies with normal Col levels had no such problem, producing considerable numbers of lamellocytes. In these flies, Col expression was restricted to a lymph region called the posterior signaling center (PSC). Col's influence on lamellocyte fate was strong enough that forcing Col expression in precursor blood cells induced lamellocyte differentiation even in the absence of wasp infestation. Based on these findings, Meister and colleagues propose a model for Col-mediated lamellocyte differentiation in which wasp infestation activates Col-expressing cells in the PSC, which then instructs immature blood cells in the lymph gland to become lamellocytes and dispatch the gathering threat. Col's role in fruitfly hematopoiesis closely parallels that of its mammalian ortholog in white blood cell development, EBF. Both are required to generate specialized populations of cells in response to a particular immune threat, and both confer an extra line of defense when faced with special circumstances—key features of vertebrate adaptive immunity. Could it be that building blocks of adaptive immunity were already in place some 550 million years ago, when flies and vertebrates parted ways? Researchers will have to investigate the molecular agents of immunity in intervening species to find out.

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PLoS Biol. 2004 Aug 17; 2(8):e255

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PLoS Biol

10.1371/journal.pbio.0020255

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020262Book Reviews/Science in the MediaDevelopmentGenetics/Genomics/Gene TherapyHomo (Human)Mutants on the Small Screen Book Reviews/Science in the MediaHodgkin Jonathan 8 2004 17 8 2004 17 8 2004 2 8 e262Leroi A, presenter (2004) Human Mutants [three-part television series]. United Kingdom: Channel 4. Broadcast June 2004  Copyright: © 2004 Jonathan Hodgkin.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.A recent television series in the UK celebrates the genetic diversity of human life ==== Body My graduate adviser, Sydney Brenner, used to exclaim ‘Revenons à nos mutants!’ as he sat down at the bench to search for yet more genetic variants of C. elegans. Those mutants won him a Nobel Prize, some thirty years later. Armand Leroi is another aficionado of C. elegans mutants, but he decided to write a book—and then to make a television series—on mutants of humanity, not of worms. He says at the beginning and end of the series: “We are all mutants, but some of us are more mutant than others.” This is a good slogan, and very proper for embracing humanity as a whole. He backs it up with an aphorism from Etienne Geoffroy Saint-Hilaire, pioneer of teratology, who proclaimed: “There are no monsters and Nature is one.” What Geoffroy meant was that abnormalities provide clues to normal processes, and hence are invaluable to science, if they can be properly understood. But monsters and mutants are, undeniably, fascinating in their own right. Mutants, the book, is excellent: impressively researched and illustrated and extremely well written. The resulting television series on Channel 4 in the United Kingdom has a distinctly different impact. The series covers only a few of the subjects dealt with in the book, and handles the material in a different way. Inevitably, television can't include much science or scholarly detail, but it compensates with human images that are wholly gripping—both the preserved specimens and the living subjects who talk about the strange conditions that they live with. It's a freak show, but a freak show with thoughtful scientific commentary. Each of the three programmes in the series has a particular theme. The first, ‘The Mystery of Growth’, is devoted mainly to skeletal disorders. We meet Carole Ozel, who copes with extraordinary courage with a terrible disease called fibrodysplasia ossificans progressiva (FOP), in which bony tissue forms throughout the body, gradually immobilizing the body in a second skeleton. Later we encounter a crew of charming and articulate dwarfs taking time out from a disco at the Reno convention of the Little People of America. They are happy to be called dwarfs or little people, but midget is no longer an acceptable term. Being a dwarf, in fact, is sometimes a ticket to fame and fortune, as in the case of Joseph Boruwlawski, last of the court dwarfs, who enchanted European royalty, married a beautiful woman, and lived happily to the age of 98. The second part, ‘The Dangerous Womb’, is about birth defects, conjoined twins, and basic embryology. The makers of the piece went to the trouble of getting the developmental biologist Eddie de Robertis to reconstruct the classic experiment of Mangold and Spemann that revealed the underlying basis of some of these defects. The programme goes into some detail about what is now known about the molecular basis of normal and abnormal development, and how we can begin to explain such extraordinary forms as that of the Parodi twins, who had distinct heads and shoulders, but merged into a single torso and a single pair of legs. The third programme, ‘The Meaning of Beauty’, deals with lesser but still striking abnormalities such as albinism and hypertrichosis (excess hair). It also moves into contentious areas, in a frank discussion of race genetics. Leroi makes the essential point loudly and clearly: there is much more genetic variation within any village on earth than there is between different human populations. We are extraordinarily unified, from a genetic standpoint. But, as he notes, the idea of race persists, and about 7% of global genetic variation in human DNA includes AIMs, ancestry informative markers. Some of these distinguish, for example, Africans and Europeans and provide objective information about the ancestry of different human populations. This being television, the series closes with a discussion of beauty, which Leroi proposes to be simply the absence of visible mutant defects, using Saira Mohan, Newsweek's idea of human facial perfection, as an exemplar. Yes, she looks nice, but nice can be boring. Beauty, above all other human attributes, is profoundly influenced by culture, and it is hard to take this interpretation of beauty as an adequate explanation, rather than just a pretty way to finish the series. For the most part, Leroi makes an agreeable and humane commentator, though he is not immune to the slight self-satisfaction that seems to overcome all scientists on television. The camera also spends an excessive amount of time dwelling on him, to a point where it becomes irritating to see him walking—frequently in slow motion— into yet another museum or laboratory. Sometimes the focus on the presenter pays off, as when we see the six-foot scientist looking like a small child beside Chris Greener, the tallest man in Britain, or witness Leroi's faint chagrin at discovering that his DNA is mostly European, despite his cosmopolitan family history. More questionable are the bits where he paddles casually through a tub of preserved viscera from some long-gone sufferer from situs inversus (mirror-reversed organs) and succumbs to laughter at the sight of Ditto, the amazing two-faced pig. This may be an honest attempt at portraying the conflicted reactions we all have to abnormality, but it seems bound to cause trouble. Arty camerawork is a running feature of the programmes, and there is a great deal of smoke and mirrors about the whole production. Perhaps this is deliberate, reminding us that it is hard to look directly at extreme deformity, but there is an air of ‘I wants to make your flesh creep’ about the many sidelong shots of mutant babies in bottles in the Vrolik Museum, to which we return again and again throughout the series. Viewing the already distorted fetuses through further distorting camera angles and under green lighting doesn't really achieve anything. The treatment begins to resemble the first Alien movie, in which the audience was never allowed to see the monster directly. In the end, what is most memorable about these programmes is the living people themselves, and how they have coped with their various genetic disorders. It is very touching to see the home movies of Tiffany York, born with mermaid syndrome, or sirenomelia (in which the legs are fused together), taking her first tottery steps after corrective surgery, and to listen to her talking philosophically about her life as she floats in a Florida swimming pool. It is similarly cheering to hear from the dwarfs and albinos, or from Chuy Aceves, who has hypertrichosis and looks like the original Hollywood wolfman but suffers no ill effects and is proud of his rare condition. For these sections alone, let alone the serious and well-explained scientific background, the series is well worth seeing. It makes one feel surprisingly good about the human race and the human spirit. Jonathan Hodgkin is in the Genetics Unit, Department of Biochemistry, University of Oxford, Oxford, United Kingdom. E-mail: jonathan.hodgkin@bioch.ox.ac.uk

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2021-01-05 08:28:06

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PLoS Biol. 2004 Aug 17; 2(8):e262

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020266SynopsisCell BiologyDevelopmentFrogsRegenerating Lost Muscle: Msx1 to the Rescue Synopsis8 2004 17 8 2004 17 8 2004 2 8 e266Copyright: © 2004 Public Library of Science.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. The Regenerative Plasticity of Isolated Urodele Myofibers and Its Dependence on Msx1 ==== Body Cell and molecular biologists have a good start at understanding the adult salamander's enviable ability to completely regrow a lost limb or jaw. (Salamanders can even regenerate portions of their eyes and heart.) Happily, mammals share many of the required cellular skills—though in an untapped form. In response to injury, fully differentiated salamander muscle cells can produce less specialized cells that are capable of multiplying and recreating lost tissue. In this month's PLoS Biology, biochemist Jeremy Brockes and his colleagues at University College London tie this muscle cell de-differentiation to expression of a single gene, Msx1, a player in limb development and regeneration across species. An adult salamander The protein encoded by Msx1 appears at the borders of maturing tissues in salamanders, chickens, and mice, and represses differentiation of muscle cells (called myofibers) during development. Msx1 promotes amphibian limb and tail regeneration, zebrafish fin repair, and regrowth of the tips of digits in mice. Here, Anoop Kumar et al. clarify the gene's role in muscle repair by demonstrating that Msx1 expression is required for de-differentiation of salamander myofibers—mature muscle tissue without the ability to produce new cells—into cells with single nuclei (mononucleate cells) that are able to multiply. Large, elongated cells, myofibers are distinguished by a striped pattern of actin and myosin, the proteins that produce muscle contractions. They develop from precursor cells, which proliferate and fuse together into multinucleate intermediates called myotubes. As myotubes bulk up on actin and myosin, pushing their many nuclei to the cell periphery, they mature into myofibers. Once differentiated, myofibers are committed to the life of a muscle workhorse. They cannot divide; mature muscle in mammals adds strength and repairs injury by accumulating more actin and myosin, and by fusing single-nucleus “satellite” cells into new or existing myofibers. Unlike their mammalian counterparts, salamander and newt myofibers respond to injury by splitting into several multinucleated fragments, or by budding off several of their nuclei to create individual cells. These mononucleate progeny multiply and develop to replace lost tissue. Kumar et al. found that more than half of salamander myofibers spontaneously fragment and bud when dissected and placed in cell culture. Prior study has shown that mouse myofibers don't normally behave this way, although cultured mouse myotubes can imitate amphibian myofibers if given a push, in the form of Msx1. A fraction of mouse myotubes made to express Msx1 break off mononucleate cells that can be induced to express markers for bone, cartilage, fat, or muscle. In the salamander cells, Msx1 RNA and protein appeared in actively fragmenting and budding myofibers, especially in and around their nuclei. When Kumar et al. blocked the translation of Msx1 mRNA, the myofibers did not generate new cells. The results confirm Msx1 as a pivotal regulator of muscle cell re-entry into the cycle of cell division and tissue growth. In this context, it doesn't drive cell division—on the contrary, the authors showed that Msx1 induced cell splitting without DNA replication. The gene drove committed muscle cells to donate nuclei, creating a pool of new cells to divide, differentiate, and repair damage. Given what it can do for mouse cells in culture, the question remains whether Msx1 might help awaken a latent capacity for regeneration in living mammals.

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2021-01-05 08:21:13

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PLoS Biol. 2004 Aug 17; 2(8):e266

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10.1371/journal.pbio.0020266

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020267FeatureNeuroscienceHomo (Human)Opening a Window to the Autistic Brain FeaturePowell Kendall 8 2004 17 8 2004 17 8 2004 2 8 e267Copyright: © 2004 Kendall Powell.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.Research focuses have shifted from "curing" autism to finding better diagnostics for early intervention, improving behavioral therapies, and gaining insight into the autistic brain ==== Body At first glance, the preschool classroom on the other side of the two-way mirror looks like any other—brightly colored rugs, scattered toys, and tiny chairs. But almost immediately an observer notices differences in the Team Toddle students here at the Neuropsychiatric Institute of the University of California at Los Angeles (UCLA) (Los Angeles, California, United States). A therapist instructs a toddler on his colors, flashing a rapid sequence of blocks at him. When the toddler starts rocking in his chair and repeatedly touching his forehead, the therapist physically restrains his hands, placing them back on the tabletop until he stops the repetitive behaviors and focuses once again on her face and the blocks. During playtime, a two-year-old girl sits by herself in the corner, fixated on some picture cards, oblivious to a group of other children playing with a racetrack and to the therapist who tries to draw her out to join the group. These children lack some of the key social skills that normal toddlers pick up naturally—looking to others for reassurance or cues, focusing on faces, and playing together. Social and communication impairment is a hallmark of autism and can show up as early as 12–18 months of age. But with an unknown cause, and genetic linkages still hazy, there is little consensus among researchers on how the disorder develops in children and how it causes a broad spectrum of social, language, and behavioral deficits. Following one line of research, David Amaral's laboratory at the M.I.N.D. Institute at the University of California at Davis Medical Center in Sacramento (California, United States) has recorded, in autistic brains, a brain volume increase in a specific structure, the amygdala, which is thought to be important for social behavior. A similar study at the University of Washington in Seattle (UW) (Seattle, Washington, United States) has reached the same conclusion. “There are so few facts about autism, to have two labs come up with the same data is phenomenal,” says Amaral. “We feel confident this is a real finding, but what does it mean to these kids?” On another research track, using functional imaging, Ralph-Axel Müller, a cognitive neuroscientist at San Diego State University (San Diego, California, United States) sees a scattering of brain activation in autistic brains that he views as an indication of a more general brain development problem underlying the disorder (Figure 1). He has hypothesized that the early-developing basic functions may require more brain area in autism, pushing out and disturbing the later specialization for more complex functions. “I'm sure this is wrong,” he says, “but it will allow us to look in a more hypothesis-driven way at animal studies of how the cerebral cortex develops specialization.” Animal models may, in turn, yield clues about normal and abnormal brain development in humans. Figure 1 Brain Activation Scattering in Autism Autistic individuals show less activity, during a movement task, in areas that are normally activated (premotor and superior parietal cortex; blue areas), but unusually increased activity around these normal sites of activation (red areas). Images courtesy of Ralph-Axel Müller. “Since there is no major hypothesis as to cause [of autism], there are many plausible ideas,” says Amaral. “If we go after all of them, we will waste all of our resources. [We have to] come to some consensus about which are most plausible.” At least two levels of pursuit exist for tracing brain problems associated with autism—the exploration of the general developmental disruptions that result in an autistic brain, and the examination of more specific problems in particular brain structures that produce symptoms. Although scientists still debate how autism evolves in a patient, the field has begun in the last decade to replicate findings and make science-based arguments for interventions. Progress has come in small steps, with advances in neuroimaging and more rigorous experimental designs. Research focuses have shifted from “curing” autism to finding better diagnostics for early intervention, improving behavioral therapies, and gaining insight into the development and function of the autistic brain. Both advocacy groups and government programs have started to bring together neuroscience and genetics experts, clinicians, and families to sharpen the focus of studies and ensure progress in what has often been a messy field. A World Apart Autism spectrum disorder strikes between one and six out of every 1,000 children around the world, but diagnosis and treatment are currently limited to developed countries. Autism is four times more prevalent in boys than girls, but makes no racial, ethnic, or socioeconomic distinctions. It is characterized by three main symptoms: impaired language, social and communicative deficits, and repetitive and stereotyped behaviors, such as hand flapping, rocking, and unusual responses to sensory stimuli. Autism spectrum disorders can be broken down into other categories, such as low-functioning autism (IQ below 70), high-functioning autism (IQ above 70), and Asperger syndrome (similar to high-functioning autism but with no language deficit). Researchers suspect that there are even more distinct subsets of autism patients. For example, some patients also have epilepsy, and it has been suggested that there is a regressive form of autism—children who, at two or three years of age, appear to regress and lose developmental milestones they had already achieved. Researchers say that sorting out these different profiles—or phenotypes—of autism will be especially important in sorting out which genes or which brain abnormalities are implicated for particular deficits. This sorting should also help clarify the mounds of contradictory data that have dogged the field, by tamping down the experimental “noise” in studies. Boosting the number of children studied and following them from early infancy through adolescence and beyond will also be key components of future studies. “There is not going to be rapid progress in autism research unless we subtype,” Amaral says. He predicts that “brain differences in kids with a regressive form of autism will be different than those of kids with the more congenital type of autism.” He and others are teaming up in an autism phenotyping project that will characterize 600 children into categories of autism (comparing them to 600 children with mental retardation and 600 controls). Splitting autism into subtypes will boost both neurobiology and genetics studies (Box 1) to find real effects related to specific traits. Facing Up to Autism A key area of research explores the brain's response to human faces at a young age. Studies at the UW Autism Center have shown that unlike typically developing three-year-olds, autistic children do not show a differential brain response to their mother's face compared to that of a stranger. While dysfunctional face recognition may be one of the more devastating symptoms for caregivers, it is also one of the most promising avenues for research to determine how autistic brains process their world differently. Sara Webb, a child psychologist at UW, has followed about 70 autistic children since the age of three for a longitudinal study that will test many parameters until they reach age nine. Her work has already shown that autistic three-year-olds process seeing a strange toy differently from seeing a favorite toy, in the same way a normal child does. But activity in their brains—measured through a network of electrodes placed on the scalp—is similar whether the face is familiar (for example, mom) or strange. This, Webb says, led to two hypotheses: either the brain area for face processing is not set up correctly in autistic children, or the way these children incorporate experiences from their environment is so different that the brain area develops improperly. “We think the latter is a more likely explanation at this point,” says Webb. “By the time they are adolescents or adults, they are showing the [proper] response for familiar faces.” Indeed, a functional MRI (fMRI) study by UW neuroimaging researcher Elizabeth Aylward showed that the brains of high-functioning adolescents and adults did activate the face-recognition center, the fusiform gyrus, when shown a very familiar face. However, the same subjects did not activate the center when viewing strange faces. This points to the possibility that greater experience seeing the familiar face (i.e., on a daily basis for many years) can eventually influence the appropriate brain areas. “You need the biological wiring set up properly, but you also need experience for it to function normally,” says Aylward. “We're guessing what is missing is the experience.” To test that idea, one of her graduate students will “train” half of the autistic patients in face recognition—something most children pick up on their own—by having them study, manipulate, and match faces using computer games. Then fMRI scans will be done again to see if the fusiform gyrus might now be activated when viewing strange faces, as it is in control subjects. Intense training of a similar type for reading has already been shown to effect change in brain activation in as little as three weeks for children with dyslexia. In their model, it is as if “all the parts are there, ready to go, but somehow they haven't gotten the ignition turned on,” says Aylward. At the 2004 annual meeting of the American Association for the Advancement of Science (Washington DC, United States), the UW center director Geraldine Dawson explained that this tackling of specific deficits will help researchers attach them to particular “mind modules” in the brain and will ultimately lead to the genes that control the development or function of those modules. That modular view, however, is not shared by many of her colleagues elsewhere, who argue that autistic behaviors are the result of a system-wide perturbation of early brain development and connectivity. Structural Support For example, Müller points to structural studies that seem to uphold his theory of overall disorganization of the brain's cortex. Work by Manuel Casanova and colleagues at the University of Louisville (Louisville, Kentucky, United States) shows that the “minicolumns” of neurons that make up the cortex are narrower and more numerous in autistic brains. Normally, these organized bundles appear very early in the developing fetal brain. In postmortem studies of autistic brains, Casanova found that the minicolumns had the same number of neurons, but smaller margins between the bundles. The margins, Casanova says, may act like “a shower curtain of inhibition that prevents information from flooding adjacent minicolumns.” Reducing those margins, he hypothesizes, could mean that an autistic brain has too much positive feedback, acting like a noisy amplifier. “For an autistic individual who is trying to piece together too much information from a face, maybe it's like looking at the sun,” he says. More general studies of adult autistic neuroanatomy have given conflicting results—most likely from diversity in the study populations—that make functional inferences difficult, if not impossible. But recent studies that focus on developing autistic brains earlier in life have revealed intriguing differences from normally developing children. Several studies have shown that from ages two to four, autistic children have larger overall brain volumes (and correspondingly larger head circumferences) than normal children, but that the difference had disappeared by about age six or seven. Since autism is usually diagnosed around age two or three, when the brain is already abnormally large, Eric Courchesne and colleagues at University of California, San Diego (San Diego, California, United States) hypothesized that brain overgrowth must occur earlier, before signs of autism appear. In an elegant retrospective study, the team analyzed head circumference and brain volume measurements of autistic children that started at birth and continued until 14 months of age. The study revealed that at birth, autistic children's head size is much smaller than healthy children, in the 25th percentile, but by 6–14 months, their head size had increased to the 84th percentile, an excessive growth rate. The increase correlated with increased brain volumes of both gray and white matter regions measured by structural imaging between ages two to five. The Courchesne study strongly suggests that with autism, significant unregulated brain growth occurs in the first year of life. The team also found an association between greater increases in brain size in infancy and a later age for first word, worse repetitive behavior, and a trend toward more severe autistic symptoms later, at diagnosis. The rapid growth of autistic brains may produce too many connections too quickly, without the opportunity to be shaped by the experience and input that a typically developing child accumulates over many years. At age six or later, when the growth slows, the already derailed connections may no longer be able to incorporate experiences. “By that time,” write Courchesne et al., “the period of plasticity that allows the exquisite and graceful complexity of the human brain to emerge will have passed.” Playing Well with Others This idea that autistic brains are developing at warp speed, to their detriment, fits intriguingly well with what is known about treatment of autism—the earlier and more intense behavioral therapy an autistic child receives, the better the outcome will be. That's why the toddlers at UCLA get one-on-one training by therapists, who fire rapid questions and physically repeat tasks until they sink in. Stephanny Freeman, co-director of the Early Childhood Partial Hospitalization program at UCLA (Los Angeles, California, United States), says these methods would be alien to, and lost on, typically developing two-year-olds, who would be bewildered by such a highly structured environment. Her colleague and co-director, Tanya Paparella, chimes in, “It as if we are opening a window or door to the autistic brain.” Keeping that door open as long as possible in very young autistic patients seems to give them a better prognosis than older children, who are more difficult to treat. But while most agree that early and intense therapy is good for autistic children, until recently, little research on intervention methods existed. Connie Kasari, an educational psychologist at UCLA, along with Freeman and Paparella, has run one of the first randomized, controlled trials on therapies designed to teach autistic kids social skills. The group tested two skills in particular—sharing attention with others and pretend playing (Figure 2). The team hypothesizes that these skills, which normal children pick up easily and early, lay important groundwork for language development. Figure 2 Pointing as an Example of Joint Attention A child with autism (three years old) pointing to the fish in an aquarium. Photo courtesy of Connie Kasari. The team's results show that autistic children can learn these skills from intense training. At least anecdotally, some of these children have gone on to function in normal school classrooms, even making a few friends, although they are still a bit socially awkward. Whether or not improvements in those skills will correlate with language improvements will require further testing. But Kasari notes that this work is not universally accepted in the autism therapy community, and that many more controlled studies will have to be published before a system-wide change in autism preschool education can occur. Funding the Search In the last decade, National Institutes of Health funding for autism research has increased from $10 million to $80 million, and much of that has been funneled into large, multidisciplinary research projects. Advocacy groups such as Cure Autism Now (Los Angeles, California, United States) and the National Alliance for Autism Research (Princeton, New Jersey, United States) greatly influence which autism research projects get funded, both through their own grant programs and also by lobbying Congress for increased federal grants. Some question whether it is wise to let emotions and the desire to find a cure drive research agendas. In the past, tensions between government programs and advocacy programs have run high. Casanova, for one, criticizes the disproportionate flow of money to what he calls imaging and genetic “fishing expeditions” and says more should go to neuropathology studies. He points out that only about 40 postmortem, mostly adult, autistic brains have been studied so far, a tiny fraction compared to those studied in other neuropathological disorders like Alzheimer's disease or schizophrenia. But Daniel Geschwind, a neurogeneticist at UCLA, defends this approach, saying that a well-planned fishing expedition that uses the right technology and looks in the appropriate places can result in a “freezer full of fish.” He also says that parent organizations keep the field honest by “constantly reminding us to keep an eye on the ball and don't get distracted.” Geschwind, Amaral, and other top experts have recently been recruited by advocacy groups or by friends with autistic children to shift some of their research questions to examining autism. As more researchers in genetics and neuroscience have become involved, Amaral says, the tensions between the parent groups and the National Institutes of Health have eased. “The parents communicated to the scientists the tremendous need for research and the scientists convey back to them which [research projects] make sense to fund,” he says. He adds that advocacy groups have been indispensable to research, setting up large genetic and brain tissue banks and enlisting families to participate in those efforts. So, researchers say, the goals of the National Institutes of Health programs and the advocacy programs have started to come together to focus on well-executed studies that might lead to better diagnostics and earlier, proven interventions. The work of Courchesne et al. suggests that children at risk for autism might easily be diagnosed by head circumference measurements as early as the first few months of life. Imaging studies combined with training programs, such as the work at UW on face recognition, may one day be able to verify that behavioral interventions are effective at activating target brain areas. As researchers work to untangle the causes and effects of brain dysfunctions in autism, Aylward notes, there is good reason to be hopeful: “Although this is a genetic disorder, we know there is plasticity in the young brain.” Box 1. Genetic Power-Up Evidence abounds that autism results from multiple gene mutations. Identical twins share an autism diagnosis 60%–95% of the time, and a younger sibling of an autistic child is 50 times more likely to have autism. There are also four times as many autistic males as females, indicating a possible sex chromosome difference in inheritance. Genetics researchers estimate that autism is the result of mutations in anywhere from 2 to 20 genes. By studying the commonly inherited pieces of chromosomes in autistic siblings, geneticists have identified a handful of chromosome hotspots. However, each region contains hundreds of individual genes, and narrowing down to specific mutations will require studies that either involve thousands of families or tackle specific phenotypes. Daniel Geschwind, a neurogeneticist at UCLA, has already completed such a study. It reveals a linkage—the probability that a region contains a gene or genes linked to the disorder—between language deficits and a hotspot region on Chromosome 7. His team looked at a more homogenous group of autistic patients, all of whom had a similar language delay measured quantitatively by time to first spoken word. “Endophenotypes measure something that underlies the disorder in a significant way and [therefore probably] also underlies a genetic component,” says Geschwind. “We're trying to identify characteristics that really underlie the genetic peaks of interest.” Another such study, by Margaret Pericak-Vance and colleagues at Duke University Medical Center (Durham, North Carolina, United States), used the characteristic of “insistence on sameness”—a subset of stereotyped behaviors such as resisting change in routine or environment, and compulsions. By running a genetic analysis on a group of patients with the highest “insistence on sameness” scores from diagnostic tests, the Duke team increased the linkage score and further narrowed the hotspot region on Chromosome 15. Kendall Powell is a freelance journalist from Broomfield, Colorado, United States of America. E-mail: kendall2@nasw.org Abbreviations fMRIfunctional MRI UCLAUniversity of California at Los Angeles UWUniversity of Washington in Seattle ==== Refs Further Reading Alarcón M Cantor RM Liu J Gilliam C Geschwind DH Evidence for a language quantitative trait locus on chromosome 7q in multiplex autism families Am J Hum Genet 2002 70 60 71 11741194 Amaral DG Bauman MD Schumann CM The amygdala and autism: Implications from non-human primate studies Genes Brain Behav 2003 2 295 302 14606694 Casanova MF Buxhoeveden D Gomez J Disruption in the inhibitory architecture of the cell minicolumn: Implications for autism Neuroscientist 2003 9 496 507 14678582 Courchesne E Carper R Akshoomoff N Evidence of brain overgrowth in the first year of life in autism JAMA 2003 290 337 344 12865374 Dawson G Carver L Meltzoff AN Panagiotides H McPartland J Neural correlates of face and object recognition in young children with autism spectrum disorder, developmental delay, and typical development Child Dev 2002 73 700 717 12038546 Müller R.-A Kleinhans N Kemmotsu N Pierce K Courchesne E Abnormal variability and distribution of functional maps in autism: An fMRI study of visuomotor learning Am J Psychiatry 2003 160 1847 1862 14514501 Shao Y Cuccaro ML Hauser ER Raiford KL Menold MM Fine mapping of autistic disorder to chromosome 15q11-q13 by use of phenotypic subtypes Am J Hum Genet 2003 72 539 548 12567325

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PLoS Biol. 2004 Aug 17; 2(8):e267

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10.1371/journal.pbio.0020267

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020269SynopsisCell BiologySaccharomyces--4932Yeast Use Dual Gain Controls to Amplify Protein Processing Synopsis8 2004 17 8 2004 17 8 2004 2 8 e269Copyright: © 2004 Public Library of Science.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. IRE1-Independent Gain Control of the Unfolded Protein Response Gcn4p and Novel Upstream Activating Sequences Regulate Targets of the Unfolded Protein Response ==== Body Machinery within the endoplasmic reticulum (ER) of eukaryotic cells modifies, folds, and assembles proteins as needed to suit their functions at or past the cell membrane. When this system is hampered or overtaxed, a buildup of unfolded or misfolded proteins within the ER triggers the “unfolded protein response,” which alerts the nucleus to boost production of protein-processing machinery that helps proteins fold. This system for adjusting manufacturing capacity is similar in organisms from yeast to human. If the unfolded protein response cannot be turned on when needed, cells die. Prior study suggested that, in yeast cells, the response to unfolded protein buildup is binary: either off or on. In this month's PLoS Biology, biochemist Peter Walter and his colleagues from the University of California at San Francisco demonstrate two new signaling mechanisms that appear to give the yeast unfolded protein response the means for amplitude adjustment. In yeast, a transcription regulator called Hac1p activates the genes required for the unfolded protein response. A cytoplasmic pool of HAC1 messenger RNA waits in readiness for ER emergencies, each molecule locked against translation into protein by intronic RNA sequences that interrupt mRNA translation. Accumulation of unfolded or misfolded proteins in the ER releases this translational block, triggering production of Hac1p and activating the unfolded protein response. Previously, this binary HAC1 signal was the only known regulator of the unfolded protein response in yeast. In two complementary papers, Walter and colleagues now present evidence that the repertoire includes new factors and regulators that amplify the unfolded protein response under conditions of ER stress. Wiring the unfolded protein response Leber et al. stressed yeast cells by exposing them to substances that cause protein misfolding or buildup in the ER. In response, the cells ratcheted up transcription levels of HAC1 severalfold. Primed with high levels of HAC1 mRNA, the cells were ready to produce a bumper crop of Hac1p and to induce a supercharged unfolded protein response. In the accompanying paper by Patil et al., the authors show that Hac1p is not working alone. A second regulator of transcription called Gcn4p is required to activate most of the genes associated with the unfolded protein response. The regulatory elements of these genes now appear far more diverse than previously appreciated. The authors propose that cells adjust the levels of Hac1p and Gcn4p to drive a continuum of transcriptional programs equipped to deal with incoming challenges. Together, these two papers demonstrate that the control of the unfolded protein response is far from a simple on/off mechanism, but exhibits complex fine-tuning through a network of signaling pathways that interpret and respond to the cell's needs. Control elements of UPR target genes

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PMC509313

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2021-01-05 08:21:13

no

PLoS Biol. 2004 Aug 17; 2(8):e269

utf-8

PLoS Biol

10.1371/journal.pbio.0020269

oa_comm

==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020270SynopsisCancer BiologyCell BiologyDevelopmentMolecular Biology/Structural BiologyHomo (Human)Inhibition of the DNA Damage Pathway by a Telomere-Binding Protein Synopsis8 2004 17 8 2004 17 8 2004 2 8 e270Copyright: © 2004 Public Library of Science.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. The Telomeric Protein TRF2 Binds the ATM Kinase and Can Inhibit the ATM-Dependent DNA Damage Response ==== Body To maintain the integrity of their genetic content, cells closely monitor the state of their chromosomal DNA. Any break or pairing anomaly in the double helix is perceived as damage that must be repaired. Mechanisms that sense DNA damage enlist the help of cell cycle checkpoint proteins, which stall cell division until the damage has been repaired. The exposed ends of linear chromosomes of eukaryotic cells (cells with nuclei) resemble the double-strand breaks of damaged DNA, which should make them vulnerable to unnecessary manipulations by repair enzymes. But chromosomes have special DNA sequences at their tips, called telomeres, that are coated with telomere-binding proteins that appear to protect ends from the unwanted attentions of repair enzymes. For instance, removing a telomere-specific DNA-binding protein, called TRF2, from telomeres leads to a rapid attack on chromosome tips, associated with the activation of the DNA damage pathway. The biochemical basis for TRF2's shielding effects remains obscure. In this issue of PLoS Biology, Jan Karlseder et al. propose that TRF2 is a direct inhibitor of an early mediator of the DNA damage signal. Their observations offer new insights into how telomeres resist the inappropriate interventions of the DNA repair machinery. Ataxia telangiectasia mutated (ATM) kinase is an enzyme that induces the activation of DNA repair enzymes as well as regulators of the cell cycle and apoptosis. Its enzymatic function is triggered by DNA damage sensors. Several observations suggest an antagonism between TRF2 and ATM: ATM is activated in aging cells with shortened telomeres and participates in ushering the cell into replicative senescence. (Cells divide only so many times during their lives before forgoing the process altogether.) In contrast, TRF2 overexpression protects shortened telomeres from decay and delays cell entry into senescence. Here the authors examine the effect of TRF2 overexpression in cells subjected to radiation-induced DNA damage. This treatment is expected to lead to cell cycle arrest, an outcome mediated for the most part by ATM activation. Irradiated cells that overexpress TRF2, however, continue to enter cell division. Known targets of ATM's enzymatic activity are activated to a lesser degree in these cells, which harbor only about half the amount of active ATM detected in controls. This suggests that TRF2 may interfere with the DNA damage pathway early on, when ATM is activated. Do these findings reflect a direct interaction between ATM and TRF2? Karlseder et al. suggest they might. Though only a small fraction of TRF2 associates with ATM in normal cells, ATM and TRF2 proteins can form a complex in a test tube. The region of the ATM protein that interacts with TRF2 is the very region required for ATM's activation by DNA damage sensors. The authors propose that TRF2 binds to inactive ATM, and in so doing, prevents ATM's transition to an active state. The authors integrate their results in an elegant proposal that relates a cell's health to the length of its telomeres. They have previously shown that TRF2 binds another protein called Mre11, a DNA damage sensor known to activate ATM. Thus, by inhibiting ATM, TRF2 may nip in the bud any misguided attempts by Mre11 to “repair” DNA breaks in telomeres. But in aging cells, whose shortened telomeres no longer retain large amounts of TRF2, ATM activation, no longer muffled, eventually allows the onset of senescence. While TRF2 is abundant in normal cells, the authors note that its strict association with telomeres should locally limit its effect on ATM, leaving the DNA damage pathway intact at other chromosomal locations.

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PMC509314

CC BY

2021-01-05 08:21:13

no

PLoS Biol. 2004 Aug 17; 2(8):e270

utf-8

PLoS Biol

10.1371/journal.pbio.0020270

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020272EssayEcologyEvolutionInfectious DiseasesMicrobiologyZoologyVirusesEubacteriaExtinction, Slime, and Bottoms EssayNee Sean 8 2004 17 8 2004 17 8 2004 2 8 e272Copyright: © 2004 Sean Nee.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.Is biodiversity decreasing or is it being replaced by a splendid profusion of microbes -- and does this matter? ==== Body There is an old Chinese curse: ‘May you live in interesting times.’ According to those who know about such things, we live in a momentous time, the time of the Sixth Mass Extinction! But most of us do not feel at all cursed. Because, in fact, the Sixth is quite different to the previous Big Five—no-one would notice this one if we were not repeatedly reminded of it by ecologists. Previous mass extinctions were not so bashful, so discreet. The fossil record reveals the disappearance of pollen during previous ones, replaced by an abundance of fungus spores, telling us of a world of devastated forests rotting away. The earliest sediments after the mass extinction that did away with the dinosaurs are barren of fossils: so it is not just that species were going extinct, conditions for life itself were bad. Not only did species diversity drop, the abundance of life did as well. But conditions for life itself have never been better than today. In the history of the planet, there has never been anything as productive of life as a wheat field in Kansas. It may not have a large diversity of species, but that is a different matter. In fact, one of the reasons for the ongoing loss of plant diversity from grasslands is the very reason the wheat field is so productive—fertilisation. We are pouring nitrogen fertiliser into the environment and, through the wellstudied ‘paradox of enrichment’, this reduces species diversity while increasing actual biomass. Now, there is no question that if current trends of habitat alteration and climate change continue then we will ultimately lose large numbers of species—diversity will drop—but this does not necessarily translate into a loss of abundance of life, and that is a big difference between now and previous mass extinctions. Looking at specific groups of organisms tells the same story. So, for example, many island bird species are threatened, like the kagu of New Caledonia, but British seabird populations, like puffins, are booming. Worldwide amphibian diversity is threatened, but cane toads are a pest in Australia. Introduced species pose a threat to diversity—the ‘McDonald-isation’ of nature—precisely because they achieve enormous abundances. Actually, all six mass extinctions may have one very important thing in common: from the point of view of the vast bulk of life on the planet they are probably not mass extinctions at all. By any criterion—number of individuals or total biomass—the vast majority of life on earth is invisible—microbial. So, for example, at least 10% of the living biomass on earth consists of bacteria living deep in the oceans' sediments: it would take more than an asteroid impact to disturb them. And microbial life is extraordinarily robust: microbes can be found living happily in pressurised water hotter than your boiling kettle, in concentrated acid, and in rock, and their spores can survive for years in the rigours of outer space. In talks and lectures, the renowned oceanographer and paleontologist Jeremy Jackson paints a vivid picture of what is currently happening to coastal ecosystems, talking about a wall of slime emanating from populated areas and growing outwards inexorably towards the open oceans, replacing beloved ecologies like coral reef systems. What he means is that the visible life that we find attractive and useful—pretty fish, turtles, and so on—is being replaced by microbes in splendid profusion. It is taken completely for granted that this is disastrous. From a utilitarian point of view indeed it is disastrous, since we like eating fish and turtles, and don't like snorkling in slime. But from the point of view of life per se, again things have never been better. Life is so abundant that in some places all the oxygen in the water is completely used up. These are called ‘dead zones’, but they are no more ‘dead’ than the Dead Sea, which is actually teeming with life—just not fish. But, nonetheless, we consider what is occurring to be a disaster not just from a utilitarian point of view, but at some deeper level giving us an emotional reaction to the word ‘slime’—somehow it is just plain wrong. But this reflects nothing other than our evolutionary origins. Evolution has programmed us to be positively interested in plants and animals, our food, and to be repelled by slimes and oozes, teeming with potentially harmful microbes. These emotional responses colour our view of ecology, for example, in a way that has no parallel in other sciences: physicists do not just study particles that they find pretty. No ecologist wants to study the rich ecosystem that each of us carries around inside our gut, because evolution has programmed our brains to find bottom-related matters disgusting. I think it likely that naturalists from a different planet, silicon entities evolved under very different circumstances, would find tropical forests uninteresting (mainly primary producers with some herbivory and mutualisms) and animal guts fascinating, with their complex metabolic networks in which each node is manned by different species with wildly varying means of energy production. Our guts should be an ecological scientist's dream come true, ecological theatres that are replicated billions of times, which operate on a fast time scale and are easy to get to! (If aliens are ecologists, this would explain why they always ‘probe’ their abductees.) Many natural experiments are going on all the time as antibiotics and probiotics are administered and people find all sorts of different ways, voluntary or otherwise, to establish migration links between their gut ecologies. Microbiologists are increasingly interested in our guts from an ecological point of view but, unlike ecologists, they are used to faeces from their work in sewage plants. Two thousand years ago the Roman senator Cicero noted the creation of barren desert-like land in North Africa after the forests were felled for their timber, providing the earliest record of an ecosystem ‘service’ provided by forests—the stabilisation of soils. Other services provided by biodiversity readily come to mind, like pollination and carrion clean-up, and there may be many more. But perhaps the clearest example of an ecosystem service provided by biodiversity comes from our gut. Throughout our history, until very recently, we all had worms. In rich countries we have quite happily eradicated them from our inner ecosystems with none of the handwringing we expend on rhinos. But it is increasingly believed that the loss of worms from our internal ecology is responsible for the upsurge in inflammatory bowel disorders such as Crohn's disease and colitis. In fact, there are clinical trials underway in the United States testing the efficacy of worms as treatment for these diseases. The mechanism is clear: worms trigger one arm of the immune system which down-regulates another, inflammatory arm. Our immune system has evolved to expect a certain constellation of species in our gut: in that context, worms provide an ecosystem service of balancing the immune system. Our perception of our impact on the planet as equivalent to a mass extinction simply reflects the evolutionary prism through which we view life. Of course, we may yet live up to our own publicity and pull off something apocalyptic like a runaway greenhouse that sterilises the Earth. But it is at least as likely that the microbial world, resentful at being either ignored or exterminated, will come up with something to consign us to a footnote in the history of life when it is ultimately written by the silicon entities. The Spanish flu, SARS, and HIV have just been early experiments. Sean Nee is at Ashworth Laboratories, University of Edinburgh, Edinburgh, Scotland, United Kingdom. E-mail: sean.nee@ed.ac.uk

15314670

PMC509315

CC BY

2021-01-05 08:21:13

no

PLoS Biol. 2004 Aug 17; 2(8):e272

utf-8

PLoS Biol

10.1371/journal.pbio.0020272

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020276PrimerCell BiologyImmunologyMicrobiologyMolecular Biology/Structural BiologyDrosophilaInnate Immunity in Fruit Flies: A Textbook Example of Genomic Recycling PrimerGovind Shubha Nehm Ross H 8 2004 17 8 2004 17 8 2004 2 8 e276Copyright: © 2004 Govind and Nehm.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.Drosophila serve as a wonderful model for studying aspects of innate immunity, i.e. the physical, cellular, and molecular features that provide the first lines of defense against infections in flies and man ==== Body Organisms of vastly differing morphologies, ecologies, and behaviors—such as fruit flies and humans—are now known to share a multitude of molecular, cellular, and developmental processes. Not only is there extensive similarity in the sequences of fly and human genes, but in addition, almost all of the proteins and major signal transduction pathways that control cell division and differentiation in mammals are also found in the fruitfly Drosophila melanogaster (Rubin et al. 2000; http://flybase.bio.indiana.edu/). Components in these pathways perform the same biochemical functions and act in the same order in both fruitfly and mammalian cells. Evolutionary conservation is of considerable practical and theoretical importance to biologists. First, it provides a valuable source of data for the reconstruction of phylogeny (Salemi and Vandamme 2003). Evolutionary connections between organisms that were once hidden by morphology have now been exposed in genomic analyses. Second, the conservation of evolutionary processes or traits is a prime area of investigation in theoretical evolutionary biology (Gould 2002). What can, and cannot, be changed evolutionarily? In a constantly evolving world, how can any biological system or trait survive unchanged (Van Valen 1973)? Finally, conservation provides fundamental insights into how complex biological systems, such as immunity, are assembled, maintained, and altered in evolution. Elements of Immunity “Innate” immunity refers to the variety of physical, cellular, and molecular features that provide the first lines of defense against infections. The relatively quick innate immune responses operate along with slower but more targeted adaptive immune responses that generate antigen-specific mechanisms that eventually lead to the destruction and elimination of the pathogen. In mammals, the skin and the epithelial lining of the mucosal tissues act as the primary nonspecific barriers, impeding infectious agents from entering the body. The mucous membrane barrier traps microorganisms, and the cilia present on the epithelial cells assist in sweeping the microbes towards the external openings of the respiratory and gastrointestinal tracts. If infectious agents gain entry into the body, internal innate immune responses become activated and rapidly eliminate the infection. Internal innate immune agents and responses include (amongst others) low pH of the stomach and vagina, proteolytic enzymes and bile in the small intestine, and phagocytosis. Phagocytosis is a fundamental innate immune mechanism carried out by a number of different cell types, including macrophages. Specific macrophage subpopulations are associated with different tissues (alveolar macrophages in the lung, microglial cells in the central nervous system, etc.). Their main function is to consume microorganisms, other foreign substances, and old, dying cells. Innate immunity is present from birth, and the information for innate immune responses is inherited. Cells in the mammalian innate immune system (e.g., macrophages) detect “microbial nonself” by recognizing pathogen-associated molecular patterns (PAMPs; Janeway 1989). PAMPs are products of microbial metabolism that are conserved over evolution, distributed in a wide variety of pathogens, and not found in host cells. Lipopolysaccharide is an example of a PAMP and is found in bacteria, viruses, and fungi. Receptors, called pattern recognition receptors, are present on surfaces of host cells and recognize PAMPs. When activated, pattern recognition receptors induce intracellular signaling via the transcription factor NF-κB, resulting in the activation of genes involved in host defense. Adaptive immunity is characterized by greater specificity than innate immunity, as the adaptive immune response can not only distinguish foreign cells from self, but can also distinguish one foreign antigen from another. Another hallmark of adaptive immunity is memory, which enables the body to remember specific adaptive responses in response to specific antigens. Immunological memory allows the body to make a greater and more rapid second response when the body is reinfected by the same pathogen. Immunological memory underlies both immunization and resistance to reinfection, conferring a tremendous evolutionary advantage to vertebrates. The adaptive immune response has nearly infinite flexibility: the T and B lymphocytes of the acquired immune system can rearrange the elements of their immunoglobulin and T-cell receptor genes to create billions of clones with distinct antigen receptors. In organisms where both innate and acquired immune systems are present, there is a clear interdependence between the two systems. For a fully functional immune system, these components must act in synergy. Innate Immunity in Drosophila Because it lacks an adaptive immune response, Drosophila melanogaster serves as a wonderful model for studying aspects of the innate immune system that might otherwise be obscured by the actions of the adaptive immune response. Insects defend themselves against parasites and pathogens by invoking a multitude of innate immune responses (Figure 1; for more details, see recent reviews by Hoffmann and Reichhart [2002], Hultmark [2003], Brennan and Anderson [2004], Meister [2004], and Theopold et al. [2004]). Like humans, Drosophila protects itself against microbes and parasites via epithelial barriers: for example, epithelial cells of the trachea, gut, genital tract, and Malpighian tubules produce antimicrobial peptides (local response). Figure 1 Innate Immune Responses of Drosophila (A) Posterior region of a third instar larva showing the cuticle and the trachea. These structures provide a physical barrier against infections. Cellular immune reactions consist of phagocytosis, encapsulation, and melanization. (B) A dead and melanized crystal cell phagocytosed by a plasmatocyte. (C) Encapsulation of an egg of a Drosophila parasite. The parasite is a wasp that normally infects larvae. Cells surrounding the egg are lamellocytes. The cells and the egg are stained with a fluorescent nuclear stain. (D) Clot formation occurs during wound healing. (E) Crystal cells in contact with the larval cuticle. The contents of the crystal cells are melanized. Melanization occurs in response to intruding pathogens or parasites and is also observed during wound healing. (F) Humoral immune reaction. The expression of antimicrobial peptides in the larval fat body is induced by microbes. Cells of the fat body appear green due to the presence of a transgene encoding the green fluorescent protein, under the control of the drosomycin promoter. The drosomycin promoter is activated in response to fungal infections and is under the control of the Toll pathway (see Figure 2). Antimicrobial peptides are released from the fat body into the hemolymph. This response is therefore systemic. A similar antimicrobial gene activation response can occur locally in specific body parts such as the trachea or the gut (not shown). Once within the body cavity, microbes may be consumed by the phagocytic blood cells called plasmatocytes (Figure 1). Larger pathogens (such as eggs of parasitic wasps) are inactivated by encapsulation, an immune response carried out by specialized cells called lamellocytes (Figure 1). Lamellocytes differentiate in response to macroscopic pathogens, and their precursors are thought to reside in the larval lymph gland. The transcription factors (GATA, Friend-of-GATA, and Runx family proteins) and signal transduction pathways (Toll/NF-κB, Serrate/Notch, and JAK/STAT) that are required for specification and proliferation of blood cells during normal hematopoiesis, as well as during the hematopoietic proliferation that accompanies immune challenge, are conserved (Evans et al. 2003; Meister 2004). In this issue of PLoS Biology, Crozatier et al. (2004) identify the transcription factor Collier as being critical for the differentiation of lamellocytes in Drosophila. The mammalian ortholog of Collier (Early B-cell Factor) is involved in B-cell differentiation in mice. In addition to triggering cellular immune responses, invading pathogens also activate humoral reactions. Microbes induce the rapid secretion of antimicrobial peptides from the cells of the fat body into the larval or adult body cavity (systemic response; Figure 1). A microbial infection initiates a zymogen cascade that plays a crucial role in the activation of the antimicrobial genes in the fat body. Infection or wounding also triggers a protein-cleaving cascade that results in the production of toxic intermediates and melanin around microbes or wound sites. This proteolytic cascade is similar to the vertebrate clotting cascade. Drosophila hemolymph also coagulates and participates in host defense and wound healing (Figure 1; Theopold et al. 2004). Given the evolutionary success of insects, this combination of defense mechanisms has proven to be extremely effective, allowing insects to thrive in septic environments. NF-κB Activation: The Toll and Imd Pathways of Drosophila The Drosophila genome encodes several members of the multifunctional Toll family of receptors (Beutler and Rehli 2002). Mutations in the Drosophila Toll gene (as well as in other components in the pathway) make the fly susceptible to fungal or gram-positive bacterial infections. However, Toll does not act as a pattern recognition receptor in the fly; instead its activation depends on the presence of the processed (active) form of the growth-factor-like polypeptide Spätzle. Processing of Spätzle depends on a serpin-controlled proteolytic cascade (Figure 2). Figure 2 Molecular Components of the Toll and Imd Pathways Involved in Drosophila Immunity Toll is activated by the processed Spätzle (left). Toll activation leads to intracellular signaling via cytoplasmic proteins Tube and Pelle, leading to the degradation of Cactus and nuclear localization of NF-κB proteins Dorsal and Dif. These transcription factors bind to promoters of target genes, such as drosomycin, activating their transcription. The NF-κB protein for the Imd pathway, Relish, activates diptericin transcription. The signaling events resulting in Dorsal/Dif/Relish activation in the fly are “recycled” in mammals in the activation of mammalian NF-κB. See reviews and De Gregorio et al. (2002) for more details. While components of the Drosophila Toll pathway were identified in earlier genetic screens for developmental mutants, those in the Imd pathway have been the focus of more recent studies, mainly in the context of Drosophila immunity (Hoffmann and Reichhart 2002; Hultmark 2003). The effector NF-κB transcription factor of the Imd pathway is Relish, which upon immune activation is cleaved by the Dredd caspase (Figure 2). Using a combination of the RNA interference approach of silencing gene function and a high-throughput cell culture assay, Foley and O'Farrell (2004) report the identification of two new conserved members of this Imd pathway: Sickie is a novel protein required for Relish activation, and Defense repressor 1 is a novel inhibitor of the Dredd caspase. The impressive progress in our understanding of innate immunity in Drosophila is now guiding scientists to explore the immune system of other insects such as the mosquito, Anopheles gambiae, that spreads human malaria. Immune responses in this mosquito are linked to the elimination of the malarial parasites (Osta et al. 2004). A comparison of the immunity-related genes in Anopheles and Drosophila reveals the presence of the Toll signaling pathway in the mosquito genome, even though there are some differences in genes encoding pathogen recognition and signal transduction molecules (Christophides et al. 2002). A detailed and comparative view of the genetic mechanisms underlying their host defense will contribute to the identification of new targets for insecticide development, and provide opportunities for controlling the transmission of pathogens. Concluding Remarks The homologs of many genes involved in innate immune responses in flies and humans have also been found in mice, sharks, nematodes, and plants (e.g., Pujol et al. 2001; Nurnberger and Brunner 2002). In species studied to date, host defense appears to be mediated by homologous proteins. Taken together, these findings suggest that the regulatory mechanisms of host defense may be hard-wired in the genome much as DNA replication and cell division are. Protein motifs, domains, and signaling elements have, for millions of years, not only retained their ancestral biochemical features but have also continued to participate in similar physiological responses. It is crucial that our evolving knowledge of “genomic recycling” be used to enhance our understanding of the evolution of humans, not only in the context of “descendants of ancient apes,” but in the larger context of our fundamental unity and shared genetic history with all other species. This simple but fundamental idea has yet to be adopted by the majority of our students and teachers. Unless we do more to overcome resistance to the idea that humans share deep evolutionary connections with all animal life, students will become increasingly isolated from an understanding of, and participation in, the genomics and bioinformatics revolution that is transforming the biological and biomedical sciences. Shubha Govind and Ross H. Nehm are in the Department of Biology and The Graduate Center, City College of New York, New York, New York, United States of America. E-mail: sgovind@ccny.cuny.edu (SG) Abbreviation PAMPpathogen-associated molecular pattern ==== Refs References Brennan CA Anderson KV Drosophila: The genetics of innate immune recognition and response Annu Rev Immunol 2004 22 457 483 15032585 Beutler B Rehli M Evolution of the TIR, tolls and TLRs: Functional inferences from computational biology Curr Top Microbiol Immunol 2002 270 1 21 12467241 Christophides GK Zdobnov E Barillas-Mury C Birney E Blandin S Immunityrelated genes and gene families in Anopheles gambiae Science 2002 298 159 165 12364793 Crozatier M Ubeda JM Vincent A Meister M Cellular immune response to parasitization in Drosophila requires the EBF orthologue Collier PLoS Biol 2004 2 8 e196 10.1371/journal.pbio.0020196 15314643 De Gregorio E Spellman PT Tzou P Rubin GM Lemaitre B The Toll and Imd pathways are the major regulators of the immune response in Drosophila EMBO J 2002 21 2568 2579 12032070 Evans CJ Banerjee U Hartenstein V Thicker than blood: Conserved mechanisms in Drosophila and vertebrate hematopoiesis Dev Cell 2003 5 673 690 14602069 Foley E O'Farrell PH Functional dissection of an innate immune response by a genome-wide RNAi screen PLoS Biol 2004 2 8 e203 10.1371/journal.pbio.0020203 15221030 Gould SJ The structure of evolutionary theory 2002 Cambridge (Massachusetts) Harvard University Press 1433 Hoffmann JA Reichhart JM Drosophila innate immunity: An evolutionary perspective Nature Immunol 2002 3 121 126 11812988 Hultmark D Drosophila immunity: Paths and patterns Curr Opin Immunol 2003 15 12 19 12495727 Janeway CA Approaching the asymptote? Evolution and revolution in immunology Cold Spring Harb Symp Quant Biol 1989 54 1 13 Meister M Blood cells of Drosophila : Cell lineages and role in host defense Curr Opin Immunol 2004 16 10 15 14734104 Nurnberger T Brunner F Innate immunity in plants and animals: Emerging parallels between the recognition of general elicitors and pathogen-associated molecular patterns Curr Opin Plant Biol 2002 5 318 324 12179965 Osta MA Christophides GK Kafatos FC Effects of mosquito genes on Plasmodium development Science 2004 303 2030 2032 15044804 Pujol N Link EM Liu LX Kurz CL Alloing G A reverse genetic analysis of components of the Toll signaling pathway in Caenorhabditis elegans Curr Biol 2001 11 809 821 11516642 Salemi M Vandamme AM The phylogenetic handbook: A practical approach to DNA and protein phylogeny 2003 Cambridge Cambridge University Press 450 Rubin GM Yandell MD Wortman JR Gabor Miklos GL Nelson CR Comparative genomics of the eukaryotes Science 2000 287 2204 2215 10731134 Theopold U Schmidt O Soderhall K Dushay MS Coagulation in arthropods: Defense, wound closure and healing Trends Immunol 2004 25 289 294 15145318 Van Valen L A new evolutionary law Evol Theor 1973 1 1 30

15314671

PMC509316

CC BY

2021-01-05 08:21:14

no

PLoS Biol. 2004 Aug 17; 2(8):e276

utf-8

PLoS Biol

10.1371/journal.pbio.0020276

oa_comm

==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020281SynopsisGenetics/Genomics/Gene TherapyVirologyVirusesHomo (Human)Retrovirus Integration into the Human Genome Synopsis8 2004 17 8 2004 17 8 2004 2 8 e281Copyright: © 2004 Public Library of Science.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. Retroviral DNA Integration: ASLV, HIV, and MLV Show Distinct Target Site Preferences ==== Body When gene therapy was introduced nearly fifteen years ago, it was widely hailed as a panacea. Since many diseases have a genetic component, the hope was that gene therapy could replace compromised genes with healthy versions to treat everything from inherited disorders like cystic fibrosis to cancer and HIV. That great promise was quashed when a teenager suffering from a rare hereditary liver disorder died after participating in an experimental gene therapy trial in 1999: four days after being injected with millions of viruses engineered to deliver healthy genes to his liver, Jesse Gelsinger died. It seems the virus, derived from an adenovirus, targeted his immune cells rather than his liver cells, which triggered an immune response against the virus, resulting in massive organ failure. In another case, two young boys who received gene therapy for the severe immunodeficiency disorder known as “bubble boy disease” developed leukemia-like symptoms 30 months after treatment. In this case, the viral vector inserted itself near a promoter region—a site that initiates gene transcription—of a proto-oncogene, a gene that can initiate cancer. Since viral vectors can integrate at various genomic locations, the safety and effectiveness of gene therapy ultimately depends on being able to predict a virus's particular bias. Comparing retroviral vectors derived from three viruses, including two common gene therapy vectors, Rick Mitchell et al. report 3,127 sites where these viruses typically integrate into the human genome. The different vectors, they found, show different target preferences. Retroviruses use viral enzymes to copy their own genome, which is stored in an RNA transcript, into DNA. Now recognizable by the host's genome, the virus can integrate into one of the host's chromosomes. In this study, Mitchell et al. studied vectors derived from the human immunodeficiency virus (HIV), avian sarcoma-leukosis virus (ASLV), and murine leukemia virus (MLV). Introducing the viral vectors into human cells, the authors analyzed the gene expression profiles of the cells to determine where vectors integrate into human chromosomes and which, if any, genes they activate. Mitchell et al. then compared the integration sites with the transcription profiles. Each retrovirus, they discovered, showed distinct preferences for genome integration. HIV vectors tend to integrate into sites of active transcription, favoring chromosomal regions rich in expressed genes. MLV vectors tend to integrate near transcription initiation sites, confirming the results of a previous study, with a weak bias toward active genes. In contrast, the authors report, the ASLV vector “does not favor integration near transcription sites, nor does it strongly favor active genes.” Early efforts to understand how chromosomes may influence where viruses insinuate themselves into a chromosome focused on factors governing accessibility. Viruses are more likely to be integrated into chromosomal regions that are more accessible, which tend to be transcriptionally active sites. But since each of the three viruses studied here routinely targeted different sequences, the authors note, accessibility is probably just one factor. Specific chromosomal proteins, for example, might interact with the viral integration machinery and facilitate integration at nearby sites. Another possibility, the authors propose, is that DNA-binding proteins that bind to specific DNA sequences assist integration of one virus while impeding another. This could explain why ASLV behaved as it did in the human cells studied here. The virus might have more refined integration preferences during normal infection of chicken cells, the authors note, but its integration machinery can't interact properly with human cells. The leukemia-like effects of the bubble boy gene therapy stemmed from integration of a mammalian retrovirus—the MLV vector—near an oncogene promoter region. Since ASLV tends to avoid both transcription initiation sites and active gene sites, it could be a more promising candidate for human gene therapy. With the draft chicken genome sequence now complete, researchers can investigate whether that proves true. But for now, Mitchell et al. make the case that scientists can gain more control over where viral vectors integrate into the human genome by selecting different retroviral integration systems. Only time will tell whether more control translates into safer gene therapy protocols.

0

PMC509317

CC BY

2021-01-05 08:21:13

no

PLoS Biol. 2004 Aug 17; 2(8):e281

utf-8

PLoS Biol

10.1371/journal.pbio.0020281

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020282SynopsisCell BiologyDevelopmentGenetics/Genomics/Gene TherapyDanio (Zebrafish)A Red-Blooded Transcription Factor Synopsis8 2004 17 8 2004 17 8 2004 2 8 e282Copyright: © 2004 Public Library of Science.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. The Zebrafish moonshine Gene Encodes Transcriptional Intermediary Factor 1γ, an Essential Regulator of Hematopoiesis ==== Body Every multicellular organism depends on the coordinated actions of a multitude of cell types, each designed to carry out specific jobs. In vertebrates, for example, the task of ferrying oxygen to organs, tissues, and cells throughout the body is shouldered by red blood cells. These cells must develop early in the embryo to nourish the body and must be maintained at the right levels throughout adulthood to keep the organism healthy. Specialized red blood cells arise from undifferentiated stem cells in a developmental process called hematopoiesis. All vertebrates have the same basic plan for hematopoiesis during their development, with one group of stem cells producing embryonic blood cells and, later, another group in a different part of the body making adult blood cells. Such developmental programs are tightly orchestrated by suites of transcription factors—proteins that turn genes on and off. But which transcription factors act—and how and where they act—is still largely unknown. Scientists and doctors alike want to better understand differentiation in order to grasp not only how it proceeds normally but also how it can go wrong and lead to diseases, such as leukemia, in which white blood cells become cancerous, and aplastic anemia, in which bone marrow stem cells make too few red blood cells. To discover the genes involved in hematopoiesis, Leonard Zon's group at Children's Hospital, Boston, and their collaborators exposed zebrafish to mutagens and then studied the individuals that developed relevant disorders. In 1996, the group produced three zebrafish lines with embryos lacking fully differentiated red blood cells; since these fish also had especially shimmery tails, the lines were named moonshine. Now Zon and his colleagues have identified the mutant gene responsible for the moonshine zebrafish lines' peculiar traits. The moonshine (mon) gene, it turns out, encodes a transcription factor with wide effects on the embryo's mesoderm, the set of cells that eventually form the circulatory system, muscles, and skeleton. The researchers found that all three lines of mutant zebrafish had mutations in the mon gene. In the mutant fish, stem cells that produce red blood cells were present initially, but the defective moonshine protein was unable to keep the blood cells alive. These blood cells underwent apoptosis, or programmed cell death, leaving the fish unable to make red blood cells, and they died at about two weeks old. Hemoglobin staining shows that hematopoiesis is defective in a moonshine mutant (bottom) compared to a wild-type zebrafish embryo (top) The researchers found that the protein encoded by the mon gene is most similar to the human and mouse Tif1-gamma, one of a family of proteins known to link DNAbinding proteins with other factors that activate or repress gene activity. Using a DNA analysis technique in mouse cell cultures, the researchers found Tif1-gamma in nuclear bodies, multi-protein complexes in cell nuclei that help regulate gene expression. But the Tif1-gamma nuclear bodies didn't fit into any known class of such complexes, so it's an open question how Tif1-gamma acts and what other proteins help regulate it. Finding a transcription factor such as Tif1-gamma involved in early cell specialization opens a door to a suite of studies on the targets of the transcription factor, as well as other genes that act along with mon to affect red blood cell development.

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PMC509318

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2021-01-05 08:21:13

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PLoS Biol. 2004 Aug 17; 2(8):e282

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PLoS Biol

10.1371/journal.pbio.0020282

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020283SynopsisAnimal BehaviorNeuroscienceRattus (Rat)How the Brain Retrieves Forgotten Memories Synopsis8 2004 17 8 2004 17 8 2004 2 8 e283Copyright: © 2004 Public Library of Science.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. Forgetting, Reminding, and Remembering: The Retrieval of Lost Spatial Memory ==== Body In the 2002 thriller Memento, the protagonist, Lenny, is plagued by a crippling neurological disorder that renders him incapable of storing memories for longer than fifteen minutes. He wants nothing more than to avenge the murder of his wife, but as another character in the film tells him, “Even if you get revenge, you're not going to remember it. You're not even going to know it happened.” Lenny has anterograde amnesia, a condition typically caused by stroke or other illness. (In the film, it's caused by a blow to the head.) Most forms of amnesia—including the more common retrograde amnesia, which involves the loss of long-term memory—are caused by some type of brain injury— particularly to the hippocampus. Retrograde amnesia can arise from brain damage that interferes with memory storage, retrieval, or consolidation. And it is by studying retrograde amnesia that scientists have developed theories explaining where the brain stores memory traces and how it consolidates them into long-term memories. What ultimately causes amnesia—a failure to store memories or a failure to retrieve them—is not clear. A major challenge in resolving this question experimentally is being able to determine whether an animal has truly recovered a lost memory or has simply re-learned the task at hand. By refining a classic behavioral neuroscience experiment to test spatial learning and memory, Livia de Hoz, Stephen Martin, and Richard Morris have developed a novel protocol that distinguishes retrieval from new learning. The experiment, developed by Morris over fifteen years ago, takes advantage of the fact that rats are good swimmers but prefer life out of water. Rats are placed in a pool and trained to remember the location of an escape platform, hidden just under the surface. (The rats can't see it because the water is cloudy.) Here, de Hoz et al. trained rats to a particular platform location—their escape route—then gave them hippocampal lesions. One group received “sham” lesions, another partial lesions, and a third complete lesions. Partial lesions, the authors explain, should damage only a subset of the stored memory traces and thus weaken the rats' memory rather than completely disrupting it. The rats' postoperative memory was tested by first placing them in the pool with the platform hidden: as expected, the lesioned rats couldn't remember where it was. After a minute, the platform was raised above the water, to remind them that it existed and that they could escape by climbing onto it. The platform was revealed in the original location for half the animals and in a novel location—which could be construed as misleading information if you're a rat—for the other half. If raising the platform was facilitating re-learning, then animals capable of learning would look for the platform in the new location. But if raising the platform functioned as a reminder, then animals should gravitate toward the place they were trained to, regardless of whether the platform reminder was in the original location or a new one. And that's what happened to the rats with partial lesions. De Hoz et al. then repeated the experiments in a new environment. If the rats managed to escape in this situation, the authors explain, then the reminder treatment could be causing new learning rather than triggering recall of the original training experience. Not surprisingly, the rats with total lesions failed to learn in this new environment (or to be reminded in the previous experiment), while the control rats adapted to the new location. The group with partial lesions failed to learn. Since partially lesioned rats responded to the reminder treatment by recalling the original platform location, their initial memory failure couldn't have resulted from a storage failure. And since they did not realize they could escape from the new location, the reminder didn't induce new learning. Among the many questions these results raise is what role the hippocampus plays in memory storage and retrieval. It could be, as the authors propose, that essential components of spatial memory traces are either stored in the hippocampus or reactivated there, since only the partially lesioned rats responded to reminders. Whether that proves true, de Hoz et al. have contributed a much needed resource for investigating the neural basis of memory loss. Rats given partial hippocampal lesions after training in a watermaze are initially unable to remember the location of the escape platform

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PMC509319

CC BY

2021-01-05 08:21:18

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PLoS Biol. 2004 Aug 17; 2(8):e283

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PLoS Biol

10.1371/journal.pbio.0020283

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020284SynopsisCancer BiologyCell BiologyDevelopmentMus (Mouse)Deterministic Tumor Evolution Synopsis8 2004 17 8 2004 17 8 2004 2 8 e284Copyright: © 2004 Public Library of Science.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. p19Arf Suppresses Growth, Progression, and Metastasis of Hras-Driven Carcinomas through p53-Dependent and -Independent Pathways ==== Body The essential difference between cancer cells and normal cells is that cancer cells evolve. Most cancers arise from a single cell through a sequential evolutionary process of mutation and selection. Cancer cells harbor mutations in a number of critical genes that, at various stages during the evolution of the tumor, provide those cells with a selective advantage. Many of the phenotypes, or physical outcomes, conferred by these mutant genes are subverted from a normal cell's repertoire, including proliferation, invasion, migration, loss of differentiation, and loss of apoptosis (programmed cell death); other phenotypes, such as immortalization, are novel. Tumor evolution is thought to adhere to Darwinian principles, with mutations arising randomly within an individual cell, followed by selection for mutant clones with favorable traits. Support for this idea stems from the observation that end-stage tumors have mutations in a number of genes. But linking mutations in particular genes with defined stages is difficult for most human cancers and especially so for the last and deadliest stage: when cancer disseminates throughout the body during metastasis. It's unclear, for example, whether there are mutations in particular genes or sets of genes that enhance metastasis. That is, do metastatic lesions develop through a continuation of Darwinian evolution, or is metastasis an intrinsic property of the primary tumor, meaning that further genetic evolution is not required? It is also unclear whether there is a “preferred” sequence of mutations, such that selective pressure for particular mutations depends on preexisting mutations. Squamous cell carcinoma invading muscle layer from ARF-null mouse Since the earliest days of research on oncogenes—genes that can cause a cell to become cancerous—it has been known that certain oncogenic mutations cooperate to transform normal cells into cancer cells. For example, an “activating” mutation in the oncogene Ras and the loss of the tumor suppressor p53 cooperate to transform cells. The paper by Christopher Kemp and his colleagues at the Fred Hutchinson Cancer Research Center sheds light on some of these questions, and many of the issues center around the most notorious oncogene: Ras. Using a well characterized mouse model of squamous cell carcinogenesis, which generates a form of skin cancer, the authors examine both the functional and evolutionary relationships between three cancer genes that play major roles in most human cancers: Ras and the tumor suppressors Arf and p53. Two seminal early observations set the stage: mutational activation of Ras is the initiating genetic event in this cancer model, while mutation of p53 occurs later, during the benign to malignant transition; and expression of mutant Ras in cells activates p53 via signaling through the protein encoded by Arf. Kemp et al. confirm that this pathway is active in “autochthonous” tumors—which grow and develop where they are initiated—by showing that p53 expression in tumors with Ras mutations is dependent on the presence of Arf. Thus, during the early benign stages of tumor growth, Ras activates Arf, which in turn activates p53, thereby inhibiting tumor progression. This provides strong selective pressure in favor of cells with mutations in either Arf or p53, and these mutations are indeed observed as the tumors progress to malignancy. That Arf and p53 function as tumor suppressors was confirmed by demonstrated accelerated tumor progression in mice lacking either Arf or p53. This answers a longstanding question concerning the nature of the signal that activates p53 during autochthonous tumor development: Mutation of Ras not only initiates tumor development but, through its intracellular signaling through Arf and p53, directly influences the subsequent evolutionary trajectory of the tumors. In this view, secondary evolutionary events are determined by the preexisting genetic lesion, as a result of direct signaling interactions. The authors go on to show that tumors lacking Arf or p53 show accelerated metastatic dissemination, a phenomenon rarely seen in mouse squamous cell cancer models. Thus both benign and malignant tumors lacking these tumor suppressors are at high risk for metastasis. As Ras is well known to confer many phenotypes required for the metastatic process, it appears that Ras, together with loss of its inhibitors, Arf and p53, may be sufficient to drive this process. More direct evidence that metastasis does or does not require further genetic evolution awaits.

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PMC509320

CC BY

2021-01-05 08:21:13

no

PLoS Biol. 2004 Aug 17; 2(8):e284

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PLoS Biol

10.1371/journal.pbio.0020284

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020287SynopsisEvolutionGenetics/Genomics/Gene TherapyHomo (Human)Evolution's “Molecular Clock”: Not So Dependable After All? Synposis8 2004 17 8 2004 17 8 2004 2 8 e287Copyright: © 2004 Public Library of Science.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. Evidence for Widespread Convergent Evolution around Human Microsatellites ==== Body DNA mutates, and it's a good thing it does. If it didn't, there could only be one kind of life, not the millions there are today, and species could not adapt to new challenges. This is because mutations in genes—the coding portion of DNA—are the raw material for evolution. However, genes make up a surprisingly small fraction of our DNA. If the genome were a cookbook, its 30,000-odd genetic recipes would be scattered among millions of pages of apparently meaningless nonsense. Mutations affect all DNA, not just the genes, and this provides population geneticists with a veritable toolbox of methods useful, for example, in DNA profiling. Importantly, all these methods rely on the idea of a “molecular clock,” the notion that mutations rain down on noncoding DNA like a fine drizzle, so constantly that genetic similarity is a good measure of evolutionary time. Thus, if orangutans diverged from humans twice as long ago as did chimpanzees, on any given piece of DNA we would find twice as many differences between the orangutan sequence and the human sequence as between humans and chimps. The mutations are marking time. If the molecular clock works, scientists can do wonderful things like estimating how long ago it was that the common ancestor of all humans lived, or when birds evolved from dinosaurs. The clock assumes that mutations occur independently of each other and at a constant rate. By analyzing thousands of noncoding DNA sequences scattered throughout the human genome, Edward Vowles and William Amos have found that the clock is anything but constant. Instead, a mutation in one spot in the genome affects the chance of getting another mutation nearby. Non-random base frequencies around microsatellites Not all noncoding DNA is made up of benign tracts of random letters. Some sequences appear to be more difficult to copy than others, and these trouble spots can give rise to alphabetic stuttering. DNA is made up of four component chemical units, called nucleotides, which are often referred to by their initial letters: A, C, G, and T. Stuttering occurs when the same pairs or triplets of letters occur together, for example ACACAC. Such regions are called microsatellites, and instead of mutating by swapping one letter for another, as most nucleotides do, these sequences evolve mainly by gaining and losing triplets or pairs like “AC.” In this study, Vowles and Amos used the published sequence of the human genome to track down and compare thousands upon thousands of microsatellites. If the molecular clock ran smoothly, they would expect to find no similarity at all between the DNA sequences surrounding any pair of unrelated microsatellites. To their surprise, they found the complete reverse, with entirely unrelated microsatellites showing widespread and obvious similarities in their flanking DNA. This meant that mutations near microsatellites were not random, but favored certain letters in certain positions. Just as a new shipwreck will attract its own special community of marine life, so microsatellites appear gradually to change the surrounding DNA towards a common pattern. The result is convergent evolution, an unusual state of affairs where, as time goes by, DNA sequences become more similar, not less. As yet, the exact mechanisms remain unclear, though it probably has something to do with how comfortably different combinations of letters sit next to each other. In English, “U” always follows “Q” and “B” never follows “V.” Similar rules may apply to DNA, albeit on a much subtler level. For example, if a microsatellite contains alternating As and Cs, the flanking regions also tend to have As at alternate positions, in phase with the As in the microsatellite. It is as if the DNA prefers the pattern in the microsatellite to extend into the flanking DNA, rather than abruptly stopping at the end of the microsatellite. These findings suggest that it may be wise to take the notion of a molecular clock at face value. With a perfect clock, two or three identical mutations would be highly unlikely, but we now know that this may be possible near microsatellites. Vowles and Amos estimate that as much as 30% of the genome may show evidence of convergent evolution, simply because microsatellites are so common. These mutation biases probably exist to a lesser extent in most sequences. Once scientists understand more fully how and where these biases operate, they may be able to estimate more accurately the risk of any given mutation occurring, be it one that causes human disease or makes a virus more virulent. These findings represent yet another windfall from the Human Genome Project, and act as a powerful reminder that unexpected results always lurk around the corner as we delve deeper into the secret world of the genome.

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PMC509321

CC BY

2021-01-05 08:21:13

no

PLoS Biol. 2004 Aug 17; 2(8):e287

utf-8

PLoS Biol

10.1371/journal.pbio.0020287

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020231Research ArticleCell BiologyHomo (Human)Emerin Caps the Pointed End of Actin Filaments: Evidence for an Actin Cortical Network at the Nuclear Inner Membrane Emerin Stabilizes the Pointed End of F-ActinHolaska James M 1 Kowalski Amy K 1 Wilson Katherine L klwilson@jhmi.edu 1 1Department of Cell Biology, The Johns Hopkins University School of MedicineBaltimore, MarylandUnited States of America9 2004 24 8 2004 24 8 2004 2 9 e2311 12 2003 24 5 2004 Copyright: © 2004 Holaska et al.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. A Case for a Functional Actin Network in the Nucleus X-linked Emery-Dreifuss muscular dystrophy is caused by loss of emerin, a LEM-domain protein of the nuclear inner membrane. To better understand emerin function, we used affinity chromatography to purify emerin-binding proteins from nuclear extracts of HeLa cells. Complexes that included actin, αII-spectrin and additional proteins, bound specifically to emerin. Actin polymerization assays in the presence or absence of gelsolin or capping protein showed that emerin binds and stabilizes the pointed end of actin filaments, increasing the actin polymerization rate 4- to 12-fold. We propose that emerin contributes to the formation of an actin-based cortical network at the nuclear inner membrane, conceptually analogous to the actin cortical network at the plasma membrane. Thus, in addition to disrupting transcription factors that bind emerin, loss of emerin may destabilize nuclear envelope architecture by weakening a nuclear actin network. Loss of emerin leads to Emery-Dreifuss muscular dystrophy (EDMD). Biochemical studies presented here suggest that emerin drives the formation of an actin-based cortical network at the nuclear membrane, and that network destabilization may contribute to EDMD ==== Body Introduction Emery-Dreifuss muscular dystrophy (EDMD) is inherited through mutations in either of two different genes: LMNA, encoding A-type lamins, and STA, which encodes a nuclear membrane protein named emerin (Nagano et al. 1996; Emery 2000; Bengtsson and Wilson 2004). Lamin filaments and emerin interact at the nuclear inner membrane (Burke and Stewart 2002; Holaska et al. 2002). Together, emerin and lamin A form stable tertiary complexes with other binding partners in vitro (Holaska et al. 2003), suggesting that emerin and lamins together provide a structural foundation for oligomeric protein complexes. Mutations in emerin cause the X-linked recessive form of EDMD (Bione et al. 1995; Bonne et al. 2003). Both emerin and lamin A are expressed in most cells, but EDMD disease strikes specific tissues: skeletal muscles, major tendons, and the cardiac conduction system. To explain the tissue specificity of EDMD, it was proposed that emerin might have tissue-specific binding partners such as transcription factors and signaling molecules that regulate gene expression (Wilson 2000; Bonne et al. 2003; Östlund and Worman 2003). There is growing evidence to support “gene expression” models for emerin, as discussed further below. However, a second model, not mutually exclusive, proposes that emerin helps maintain the structural integrity of the nuclear envelope. According to structural models, loss of emerin selectively disrupts tissues under high mechanical stress, such as skeletal muscle and tendons (Bonne et al. 2003; Östlund and Worman 2003). Although this model fails to explain the cardiac conduction phenotype of EDMD, it is consistent with structural defects (aberrant shape and nuclear envelope herniations) seen in nuclei from EDMD patients (Fidzianska and Hausmanowa-Petrusewicz 2003) and in a subset of patients with other diseases linked to mutations in LMNA (“laminopathies”; Holaska et al. 2002; Östlund and Worman 2003). Whereas structural and mechanical roles are expected for lamins, which form nuclear intermediate filaments, mechanical roles for emerin have not been investigated. Emerin is detected in most human cells tested, except the nonmyocytes of the heart (Manilal et al. 1996). In Caenorhabditis elegans emerin is expressed ubiquitously (Lee et al. 2000; Gruenbaum et al. 2002). Emerin belongs to the LEM-domain family of proteins, which are defined by an approximately 40-residue folded domain known as the LEM domain. In vertebrates, other family members include LAP2β and MAN1 at the nuclear inner membrane (Dechat et al. 2000; Lin et al. 2000; Cohen et al. 2001), LAP2α in the nuclear interior (Dechat et al. 2000), and at least three additional uncharacterized LEM-domain proteins (Lee and Wilson 2004). A major shared function of all characterized LEM-domain proteins is their binding (via the LEM domain) to a small protein named barrier-to-autointegration factor (BAF; reviewed by Segura-Totten and Wilson 2004). BAF is a highly conserved chromatin protein essential for cell viability (Zheng et al. 2000), with direct roles in higher order chromatin structure and nuclear assembly (Haraguchi et al. 2001; Segura-Totten et al. 2002), and gene regulation (Wang et al. 2002; Holaska et al. 2003). Supporting gene regulation models for EDMD, emerin binds directly to BAF and two other transcription repressors, germ cell-less (GCL; Holaska et al. 2003) and Btf (Haraguchi et al. 2004) as well as an mRNA-splicing factor named YT521-B (Wilkinson et al. 2003). Interestingly, GCL and LAP2β, a LEM-domain protein closely related to emerin, comediate transcription repression in vivo (Nili et al. 2001). On the other hand, emerin also has a growing number of structural or anchoring partners, including a spectrin-repeat (SR) membrane protein named nesprin-1α (Mislow et al. 2002a, 2002b), lamins A and C (Clements et al. 2000; Lee et al. 2001; Sakaki et al. 2001), and lamin B (Dreger et al. 2002). Lamins form type-V intermediate filaments that are critical for the integrity of the nucleus and confer unique elasticity and incompressibility properties to the nuclear envelope (Dahl et al. 2004). Nuclear morphology and lamina architecture are disrupted in a fraction of cells that express disease-causing missense mutations in A-type lamins (Östlund and Worman 2003). However, the line between gene expression and mechanical models for disease has become blurred. For example, the subnuclear localization of Rb, a transcription and cell-fate regulator, depends on both LAP2α and lamin A, since Rb is mislocalized in cells that either lack A-type lamins (Johnson et al. 2004) or express disease-causing lamin-A mutations (Markiewicz et al. 2002). A second putative anchoring partner for emerin is nesprin-1α, an integral nuclear inner-membrane protein with seven SR domains (Zhang et al. 2001; Mislow et al. 2002b). Each SR domain consists of approximately 100 residues and folds into a tightly packed triple α-helical structure (Bennett and Baines 2001). Tandem SR domains, as seen in nesprin-1α, form a rigid, elongated tertiary structure (Djinovic-Carugo et al. 2002). More important, SR domains provide binding sites for other proteins, the specificity of which is determined by exposed residues (Bennett and Baines 2001). SR domains 1–7 (and particularly domains 1–5) of nesprin-1α mediate high-affinity binding to emerin (Mislow et al. 2002a). Interestingly, SR domains 5–7 of nesprin-1α bind directly to lamin A in vitro, suggesting that nesprin-1α, lamin A, and emerin might form stable tertiary complexes. Such complexes have the potential to stabilize lamin filaments at the nuclear envelope, in addition to anchoring and spacing emerin. Notably, both emerin and lamin A also bind G-actin in vitro (Sasseville and Langelier 1998; Fairley et al. 1999). Actin binds two regions in the lamin-A tail (Zastrow et al. 2004). Both α- and β-actin bind emerin in vitro, and emerin coimmunoprecipitates with actin from cell lysates (Fairley et al. 1999; Lattanzi et al. 2003). The significance of these findings was unclear, in part because nuclear actin has been both documented and debated for over 35 y (Pederson and Aebi 2002). However there is a growing consensus that nuclear actin is no artifact (Pederson and Aebi 2002; Bettinger et al. 2004). Both α- and β-actin have been shown, definitively, to reside in the nucleus (Scheer et al. 1984; Gonsior et al. 1999; Olave et al. 2002; Lattanzi et al. 2003) and to form short filaments in the nucleus (Clark and Rosenbaum 1979). Actin and actin-related proteins (Arps) are required for chromatin remodeling and transcription (Olave et al. 2002; Percipalle et al. 2003). Also interesting is that polymerase II–dependent mRNA transcription requires a nuclear-specific myosin I motor (nuclear myosin I; Nowak et al. 1997; Pestic-Dragovich et al. 2000). Thus, actin probably has a variety of roles in the nucleus. To test the hypothesis that emerin forms multiprotein complexes in vivo, we affinity-purified emerin-binding proteins from nuclear extracts of HeLa cells. We identified actin itself plus several actin-binding proteins as bona fide emerin-associated proteins, and we further discovered that emerin stimulates actin polymerization in vitro by binding and stabilizing the pointed end of growing filaments. These results suggest that emerin contributes to the formation of an actin cortical network at the nuclear inner membrane. Results We used affinity chromatography to purify emerin-binding complexes from HeLa nuclear extract; as the negative control, beads were conjugated to bovine serum albumin (BSA). Mass spectrometry (data not shown) and Western blotting identified β-actin as a major emerin-binding protein (Figure 1A). Six other proteins, including nuclear-enriched αII-spectrin, were also identified and will be reported in full elsewhere (J. M. H. and K. L. W., unpublished data). Consistent with previous reports (Fairley et al. 1999; Lattanzi et al. 2003), antibodies specific for emerin coprecipitated actin from HeLa cell nuclear lysates, as shown by Western blotting with immune serum (Figure 1B, Im). Only background levels of actin were precipitated by preimmune sera (Figure 1B, PI). These findings led us to hypothesize that emerin might bind filamentous actin (F-actin). Figure 1 Affinity Purification of Emerin-Associated Proteins (A) Immunoblot of HeLa nuclear lysate proteins (L), or proteins affinity-purified using either BSA beads or emerin beads (see Materials and Methods), probed with antibody against actin. (B) HeLa nuclear lysate proteins (L) were immunoprecipitated using either immune (Im) or preimmune (PI) serum 2999 against emerin, resolved by SDS-PAGE, and Western blotted using antibodies specific for actin (upper panel) or emerin (lower panel), in succession. (C) Cosedimentation assays using F-actin and purified, recombinant wild-type emerin (residues 1–222). G-actin (2 μM) was polymerized and then incubated in the absence or presence of 2 μM emerin. Emerin was incubated alone in polymerization buffer as a negative control. After 30 min samples were centrifuged 1 h at 100,000g, resolved by SDS-PAGE, and stained with Coomassie blue. L, load (100%); S, supernatant (100%); P, pellet (100%). (D) F-actin column was used to determine the affinity of F-actin for emerin. The Kd was 480 nM for the experiment shown; range was 300–500 nM, n = 8. (E) Binding of wild-type (WT) or mutant emerin protein to F-actin beads. Recombinant emerin proteins were incubated with F-actin beads, and bound emerins were eluted with SDS-PAGE sample buffer, resolved by SDS-PAGE, blotted, and probed with antibodies against emerin (“bound”; all emerin mutants are recognized by this antibody; Lee et al. 2001; Holaska et al. 2003). The input amounts (10%) of each emerin mutant (“load”) were visualized either by immunoblotting (top row, top panel) or Coomassie staining (top row, bottom panel). (F) Domains in emerin required for binding to BAF, lamin A, transcription repressor GCL, or actin (Lee et al. 2001; Holaska et al. 2003; present study). Asterisks indicate EDMD disease-causing mutations. Emerin Binds F-Actin with High Affinity Emerin was first tested for binding to F-actin in a cosedimentation assay. Actin filaments were incubated 30 min in the presence or absence of recombinant emerin (4 μM) and then pelleted at 100,000g. Approximately 75% of input emerin pelleted in the presence of F-actin, compared to 15% in the absence of F-actin (Figure 1C), demonstrating that emerin binds polymerized actin in vitro. The stoichiometry of this interaction was one emerin molecule per approximately 300 actin monomers, demonstrating that emerin binds actin filaments with an average length of 0.9 μm (data not shown). Emerin binds F-actin with high affinity, as determined by binding to an F-actin column (Kd = 480 nM, range = 300–500 nM, n = 8; Figure 1D). The F-actin columns were also used to screen selected emerin mutants for binding to F-actin. Wild-type emerin and EDMD disease-causing mutants S54F and P183H, and alanine substitution mutant m196 (Ser196Ser197 to Ala196Ala197; Holaska et al. 2003), bound efficiently to an F-actin column, whereas 12 other tested mutants, including EDMD disease-causing mutant Q133H, showed no significant binding to F-actin (Figure 1E). Similar results were seen in coimmunoprecipitation assays using antibodies against actin to immunoprecipitate F-actin in the presence of recombinant wild-type or mutant emerin proteins (data not shown). Fifteen additional emerin missense mutants, including LEM-domain mutants, were tested in blot overlay assays; mutants m11, m24, m30, m40, m207, m214, and m217 bound detectably to actin, whereas no significant binding was detected for mutants m45A, m45E, m61, m141, m145, m161, and m206 (data not shown; see Holaska et al. 2003 for details of mutations). Thus, three independent assays all showed that emerin binds F-actin. Furthermore, based on the positions of missense mutations that blocked binding to F-actin, this recognition involved almost the entire nucleoplasmic domain of emerin, with the notable exception of the LEM-domain (Figure 1F). The putative actin-binding domain in emerin overlaps with both the lamin- and repressor-binding (GCL) domains described previously (Holaska et al. 2003). Emerin Regulates Actin Polymerization The above results suggested that in vivo emerin might (a) use actin filaments as anchors, (b) stabilize F-actin networks, or (c) actively influence actin dynamics. To test these models, we first used reactions containing 5% pyrene-labeled actin (final actin concentration, 2 μM) to determine if emerin influenced actin polymerization in vitro. Results were graphed as the rate of emerin-induced polymerization (R) divided by the control rate (cR; rate of actin polymerization in the absence of emerin). At concentrations ranging from 0.1 to 4.4 μM, emerin increased the rate of pyrene–actin polymerization 4-fold (mean = 6.2 ± 2.2, n = 32; one experiment is shown in Figure 2A). These experiments also yielded an equilibrium affinity of 420 nM (Figure 2A), consistent with our previous results (480 nM; see Figure 1D). Figure 2 Emerin Stimulates Actin Polymerization (A) Graph of a representative experiment (n = 32) showing that emerin increases the rate of actin polymerization 4-fold. R, rate of polymerization in the presence of emerin; cR, control rate of polymerization (actin alone). These data also yielded an equilibrium binding affinity of emerin for actin of 420 nM. (B) Representative graph (n = 17) in which each recombinant emerin mutant protein (1.0 μM) was added to 2.0 μM G-actin, and polymerization rates were calculated. R, rate of polymerization in the presence of emerin; cR, control rate of polymerization (actin alone). Stars indicate EDMD disease-causing mutations. (C) Critical concentration assays were performed in the presence or absence of 625 nM emerin. Actin was polymerized in the absence (barbed-end growth) or presence of 5 nM gelsolin–actin seeds (pointed-end growth) for 16 h at room temperature. Barbed-end growth with (□) or without (▪) emerin. Pointed-end growth with (○) or without (•) emerin. Actin monomers (Δ). We next tested eight emerin mutants (1 μM) in the pyrene–actin polymerization assay (Figure 2B). Five mutants (Q133H, m151, m164, m192, and m198) that failed to bind actin in vitro did not stimulate actin polymerization; instead, they reduced the rate of actin polymerization slightly, by 5%–40% (Figure 2B). Mutant 196, which had wild-type binding to F- and G-actin in coimmunoprecipitation assays, stimulated actin polymerization approximately 50% as well as wild-type emerin (Figure 2B). The two disease-causing mutants with apparently normal binding to F-actin, S54F and P183H, enhanced the rate of actin polymerization at least as well as wild-type emerin (Figure 2B). Critical concentration assays were done to determine if emerin acted on the barbed or pointed end of growing actin filaments. Pointed-end growth was examined by capping filaments with gelsolin. Emerin had no significant effect on the critical concentration of barbed-end growth (Figure 2C, + emr/no emr), but it increased the critical concentration for pointed-end growth by 2.3- to 2.7-fold (Figure 2C, + gelsolin no emr/+ gelsolin + emr). We therefore hypothesized that emerin, like tropomodulin (Fowler et al. 2003), might stabilize growing filaments by capping the pointed end. Emerin Binds F-Actin at the Pointed End The vast majority of actin-binding proteins that influence subunit addition do so by binding the barbed end (dos Remedios et al. 2003). However, because emerin failed to influence the critical concentration for barbed-end growth (Figure 2C), we used gelsolin–actin seeds to test the hypothesis that emerin binds the pointed end. Gelsolin binds and caps the barbed end of actin filaments (Burtnick et al. 2001), thereby restricting subunit addition to the pointed end only. We measured the extension of gelsolin–actin dimers (10 nM) in the presence of 2 μM actin plus 0 to 2 μM wild-type emerin (Figure 3A). Emerin blocked actin polymerization in a concentration-dependent manner, supporting our model that emerin binds and caps the pointed end of actin filaments. Based on this assay, the affinity (Kd) of emerin for F-actin was 430 nM (range, 300–500 nM, n = 12; Figure 3A). Interestingly, the affinity determined by either direct binding (see Figure 1D) or activity measurements (see Figures 2A and 3A) differed by a maximum of 2-fold. We conclude that emerin binds F-actin with an affinity of 300–500 nM. Figure 3 Emerin Binds the Pointed End of Actin Filaments (A) Gelsolin–actin seeds were incubated with increasing concentrations of wild-type emerin residues 1–222. Emerin significantly reduced the rate of subunit addition at the pointed end, with an apparent Kd of 430 nM (range, 300–500 nM, n = 12). R, rate of polymerization in the presence of emerin; cR, control rate of polymerization (actin alone). (B) Emerin inhibits depolymerization of actin filaments (2 μM) preformed from gelsolin–actin seeds, with an apparent Kd of 380 nM (range, 350–450 nM, n = 6). R, rate of depolymerization in the presence of emerin; cR, control rate of depolymerization (actin alone). (C) Rhodamine–phalloidin-stabilized actin filaments were formed from 2 μM actin, then capped at the barbed end by the addition of 100 nM capping protein, and finally diluted 2-fold in the presence of buffer or 1 μM emerin, GST, or tropomodulin (Tmod). Samples were then incubated with actin (3.2 μM) and Alexa-488 phalloidin (3.2 μM) for 2 min, diluted 1:500, placed on polylysine-coated coverslips, and viewed by fluorescence microscopy. Bar is 1 μm and applies to all panels. (D) Actin (2 μM) was incubated with gelsolin–actin seeds (500 nM) in the presence of rhodamine–phalloidin (2 μM). These red filaments were diluted 10-fold and incubated with buffer alone or with 1 μM emerin or tropomodulin (Tmod) for 10 min, followed by incubation with actin (2 μM) and Alexa-488-labeled (green) phalloidin (2 μM) for 2 min. Samples were diluted 1:500, placed on polylysine-coated coverslips, and viewed by fluorescence microscopy. Bar is 1 μm and applies to all panels. (E–H) Alexa-488-labeled emerin (green) was incubated 30 min with actin filaments stabilized by Alexa-546 phalloidin (red) and centrifuged at 100,000g to recover filaments, which were diluted 1:500 for viewing. To independently confirm that emerin binds the pointed end, we tested the effect of emerin on actin depolymerization in two separate assays. First, gelsolin–actin seeds were incubated with 2 μM actin and grown in the absence of emerin. The resulting filaments were then diluted to 0.2 μM actin in the presence of increasing concentrations of emerin (0–2 μM), and assayed immediately. Preformed actin filaments depolymerized rapidly in the absence of emerin (Figure 3B, arrow), as expected. Supporting our model, depolymerization was slowed up to 8-fold by emerin (Figure 3B). To independently confirm that emerin blocked subunit addition at the pointed end, preformed actin filaments were capped at the barbed end with capping protein (CapZ), a high-affinity barbed-end binding protein (Cooper and Schafer 2000), then incubated in the presence or absence of emerin, and diluted into 0.2 μM actin; emerin slowed the rate of depolymerization by 10-fold (data not shown). Based on these three assays, we conclude that emerin binds and protects the pointed end of actin filaments in vitro, thereby stabilizing actin filaments. Fluorescent actin polymerization assays were done to demonstrate visually that emerin blocks pointed-end growth of single actin filaments. Rhodamine–phalloidin-stabilized actin filaments (red) were preformed from 2 μM actin, then capped on the barbed end with capping protein, and diluted 2-fold into a final concentration of 1 μM emerin. Pointed-end growth was then initiated by increasing actin to 3.2 μM in the presence of 3.2 μM Alexa-488 phalloidin (green) for 2 min. In the absence of emerin (Figure 3C, buffer or GST), actin filaments containing both red and green segments are seen (Figure 3C), demonstrating pointed-end growth. The average lengths of the growing filament segments (green) as measured for buffer and GST were 1.45 ± 0.3 μm and 1.47 ± 0.3 μm, respectively (n = 30). However, in the presence of either emerin or tropomodulin, a pointed-end binding protein, most red filaments lacked green segments (Figure 3C), consistent with capped pointed ends. In the presence of emerin or tropomodulin, the lengths of the green segments were 0.05 ± 0.09 μm (n = 60) and 0.09 ± 0.13 μm (n = 50), respectively. Single filament assays were also done using small red filaments formed from gelsolin–actin seeds (Figure 3D). Here, actin (2 μM) was incubated with gelsolin–actin seeds (500 nM) and rhodamine–phalloidin (2 μM). The resulting red filaments were diluted 10-fold and incubated with 1 μM emerin for 10 min, then incubated 2 min with actin (2 μM) and Alexa-488-labeled (green) phalloidin (2 μM). In the absence of emerin, single filaments contained both short red (gelsolin–actin seeds) and longer green (pointed-end growth) segments (Figure 3D). The average length of these growing filament segments was 2.1 ± 0.6 μm (n = 40). However, when emerin was present, the preformed filaments remained predominantly short and red, demonstrating that emerin blocks pointed-end growth (Figure 3D). Similar results were obtained in control reactions containing tropomodulin, the pointed-end binding protein (Figure 3D, Tmod). The average lengths of growing filaments incubated with emerin or tropomodulin were 0.1 ± 0.1 μm (n = 40) and 0.1 ± 0.11 μm (n = 40), respectively. These experiments also show that emerin does not stimulate branching (Figure 3D). To directly visualize emerin bound to actin filaments, green (Alexa-488-labeled) emerin was incubated with red (Alexa-546 phalloidin) actin filaments (Figure 3E–3H). Under these conditions 85% of labeled emerin molecules were bound to actin filaments; of these, 92% were localized at a filament end (n = 306). Interestingly, 10% of actin-associated emerin proteins localized to “aster-like” structures (Figure 3G and 3H), presumably due to the aggregation of emerin proteins on different actin filaments. Discussion This work shows for the first time that a nuclear membrane protein, emerin, is a pointed-end F-actin-binding protein. Similar to the activity of tropomodulin (Fowler 1997; Cooper and Schafer 2000; Fowler et al. 2003), emerin caps the pointed end, thereby stabilizing the growing filament. Only three other pointed-end binding proteins have been reported: the Arp2/3 complex (Mullins et al. 1998), tropomodulin, and mSWI/SNF, a component of a nuclear complex that remodels chromatin structure (Rando et al. 2002). The Arp2/3 complex initiates filament branching at the cell surface (Mullins et al. 1998; Mullins and Pollard 1999). We have no evidence that emerin initiates branching. Instead, emerin behaves most like tropomodulin, which binds the pointed end of F-actin with high affinity (Kd = 110 nM) and stimulates actin polymerization by stabilizing the actin filament (Fowler et al. 2003). Our analysis of 15 emerin missense mutants suggested that the actin-binding region in emerin overlaps with regions required for binding to lamin A (Lee et al. 2001), transcription factors GCL and YT521-B (Holaska et al. 2003; Wilkinson et al. 2003), and nesprin-1α (J. M. H. and K. L. W., unpublished data). However this overlap does not necessarily imply that actin competes with these other proteins. Indeed, despite similar overlap, GCL and lamin A can form stable ternary complexes with emerin in vitro (Holaska et al. 2003). Further work is needed to determine if F-actin cobinds or competes with lamin A, nesprin-1α, or other emerin-binding proteins. A Proposed Actin Network at the Nuclear Envelope We propose that emerin stabilizes and promotes the formation of a nuclear actin cortical network, analogous to the actin cortical network at the plasma membrane (Figure 4). Another LEM-domain protein, LAP2β, also an integral nuclear inner-membrane protein, was 20-fold less active than emerin in actin polymerization assays (data not shown), suggesting that LAP2β binds actin with an affinity 20-fold lower than that of emerin. Other LEM-domain proteins have not yet been tested for binding to actin. Whether emerin has specialized roles involving actin, or shares this function with other nuclear membrane proteins, are both interesting possibilities. An actin-based cortical network could help anchor emerin and possibly other nuclear membrane proteins and lamin filaments, contributing significantly to the structural integrity of the nuclear envelope and potentially reinforcing sites of chromatin attachment (Figure 4). Figure 4 Model in Which Emerin Binding to the Pointed End of F-Actin Stabilizes an Actin Cortical Network at the Nuclear Inner Membrane Our model is based on the actin cortical network at the cell surface of erythrocytes, except that lamin filaments also anchor to emerin-based junctional complexes. Spectrin heterodimers bind short actin filaments at the erythrocyte membrane; we therefore speculate that nuclear isoforms of αII-spectrin (J. M. H. and K. L. W., unpublished data) act similarly. Direct binding of emerin and αII-spectrin has not yet been tested. Nuclear isoforms of protein 4.1, which are essential for nuclear assembly (Krauss et al. 2002), have the potential to cross-link short actin filaments and spectrin filaments at the inner membrane (IM). Further work is necessary to test our model and identify other components of this proposed nuclear actin cortical network. OM, nuclear outer membrane. Since lamin A also binds G-actin in vitro (Sasseville and Langelier 1998), we are currently testing the actin-binding properties of lamin A. Because emerin forms stable complexes with lamin A in vitro (Clements et al. 2000; Lee et al. 2001), and because the nuclear envelope localization of emerin depends on lamins, we speculate that emerin might interlink multiple filament networks (actin, spectrin, and lamins) at the nuclear envelope. This model will be tested in future experiments by determining whether lamin A and actin compete for binding to emerin, or form trimeric complexes. Such complexes could significantly reinforce the mechanical properties of the nuclear envelope. Our nuclear actin cortical network model is further supported by the properties of the nesprin family of nuclear membrane proteins, which includes nesprin-1α (see Introduction) and NUANCE. Nesprin-1α binds directly to both emerin (Kd = 4 nM) and lamin A (affinity undetermined; Mislow et al. 2002a). NUANCE is a large (796 kd), alternatively spliced isoform of nesprin that localizes to the nuclear envelope and nucleoplasm and binds F-actin (Zhen et al. 2002). The organization of the membrane skeleton in erythrocytes (red blood cells) includes integral membrane proteins (e.g., Band 3), anchoring proteins (ankyrin), spectrin filaments, and “junctional complexes” (short actin filaments, protein 4.1, adducin, tropomodulin, and tropomyosin; Delaunay 2002). Tropomodulin and tropomyosin stabilize the junctional complex. Spectrin filaments (α/β-spectrin heterodimers) attach to junctional complexes through direct binding to protein 4.1, adducin, and actin. At the inner nuclear membrane, our working model is that emerin stabilizes junctional complexes (Figure 4), consisting of short actin filaments, nuclear-specific αII-spectrin (McMahon et al. 1999), and nuclear isoforms of protein 4.1 (Krauss et al. 2002). This model is the first step toward understanding the structural function of nuclear actin. Materials and Methods Antibodies and proteins A pan-actin antibody (Sigma, St. Louis, Missouri, United States; catalog #A-5060) was used at 1:1,000 for immunoblotting. An antibody specific for β-actin (Sigma; catalog #A-5316) was used at 1:10,000 for immunoblotting and 1:1,000 for immunoprecipitation. Our rabbit polyclonal emerin antibody (serum 2999), described previously (Lee et al. 2001), was used at 1:20,000 for immunoblotting and 1:2,000 for immunoprecipitation. Purified chicken actin was a kind gift of Doug Robinson (Johns Hopkins Medical School). Purified rabbit actin was purchased from Cytoskeleton. (Denver, Colorado, United States; catalog #AKL95 and #AKL99). Alexa-488 actin (#A12373), Alexa-594 actin (#A34050), Alexa-488 phalloidin (#A-12379), rhodamine–phalloidin (#R-415), and Alexa-546 phalloidin (#A-22283) were purchased from Molecular Probes (Eugene, Oregon, United States). Purified CapZ (capping protein) was a kind gift from John Cooper (Washington University, St. Louis). The full nucleoplasmic domain of wild-type emerin (residues 1–222) and corresponding mutants (detailed in Holaska et al. 2003) were expressed in bacteria and purified as described (Lee et al. 2001; Holaska et al. 2003). Emerin protein was labeled with Alexa-488 (Molecular Probes, catalog #A20000) per manufacturer's instructions. Affinity purification using emerin-conjugated beads Wild-type emerin residues 1–222 (comprising the entire nucleoplasmic domain of emerin and lacking the transmembrane domain) or BSA (as a negative control) were coupled to Affigel-15 beads (Bio-Rad, Hercules, California, United States) per manufacturer's instructions. Nuclear extracts were prepared by hypotonic lysis (Offterdinger et al. 2002) from 1010 HeLa-S3 cells, obtained as frozen cell pellets from the National Cell Culture Center. For each affinity purification, we incubated 50 mg of nuclear lysate proteins with 2 ml of either emerin beads (0.5 mg/ml) or BSA beads in binding buffer (50 mM HEPES, 250 mM NaCl, 0.1% Triton X-100) for 4 h at 4 °C. Beads were collected by centrifugation at 500g, washed five times with binding buffer, and eluted with SDS-PAGE sample buffer. Dr. Robert Cole at the Johns Hopkins Mass Spectrometry Facility performed MALDI-TOF. Actin and αII-spectrin were two of seven emerin-associated proteins identified unambiguously in this work, which will be reported separately (J. M. H. and K. L. W., unpublished data). F-actin-binding assays F-actin columns were assembled as described (Forero and Wasserman 2000). Equal amounts of purified recombinant wild-type and mutant emerin proteins (residues 1–222) were incubated with each column in PBS containing 0.1% Triton X-100 (PBST) for 1 h at 22 °C. After washing beads five times with PBST, bound proteins were eluted and resolved by SDS-PAGE, and detected either by Coomassie blue staining, or by immunoblotting with rabbit serum 2999 against emerin. Coimmunoprecipitation assays were performed as described (Lee et al. 2001). Briefly, equal masses (5 μg) of actin and either wild-type or mutant emerin were incubated 2 h, then incubated 4 h with protein-A Sepharose-coupled antibodies against emerin or actin. The beads were washed five times with buffer, and bound proteins were eluted with SDS-sample buffer, resolved by SDS-PAGE, then blotted and probed with antibodies specific for either actin or emerin. To measure emerin binding to single actin filaments, actin was polymerized by the addition of KMEI buffer (2 mM MgCl, 50 mM KCl, 10 mM imidazole [pH 7. 0], and 2 mM EGTA). After 30 min, the indicated form of emerin (4 μM, recombinant wild-type or mutant emerin residues 1–222, with or without conjugation to Alexa-488) was added to the filaments and incubated 30 min; we lastly added Alexa-546 phalloidin (final concentration, 0. 33 μM). These red F-actin polymers were then pelleted at 100,000g for 60 min. For experiments with unlabeled emerin, corresponding load, supernatant, and pellet fractions were resolved by SDS-PAGE and stained with Coomassie blue. For experiments with phalloidin-546-labeled F-actin, filaments were viewed using a Zeiss Axiovert 200 fluorescent microscope (Zeiss, Oberkochen, Germany) and images captured using a Quantix CCD camera (Photometrics, Huntington Beach, California, United States) attached to an Apple G4 computer using IPLab (version 3.6; Scanalytics, Fairfax, Virginia, United States) software. Actin polymerization and depolymerization assays Actin polymerization assays were performed per manufacturer's instructions (Cytoskeleton). Rabbit actin (2 μM; Cytoskeleton, catalog #AKL95) plus pyrene–actin (0.1 μM; Cytoskeleton, catalog #AP05) were used in all assays, unless otherwise stated. Actin polymerization was measured in a fluorimeter (Fluoromax 2; SPEX, Edison, New Jersey, United States), with excitation wavelength 365 nm and emission wavelength 407 nm, and plotted using DataMax-Std (version 2.2; SPEX, Edison, New Jersey, United States). Graphs were refined using Cricketgraph III (version 1.0, Computer Associates, Smithfield, Rhode Island, United States) and Kaleidagraph (version 3.5.1, Synergy Software, Reading, Pennsylvania, United States). Pyrene–actin was always present at 5% of total actin. Increasing concentrations of recombinant emerin were added just prior to initiating actin polymerization. The actin depolymerization assays were performed exactly as described (Mullins et al. 1998) with increasing amounts of recombinant emerin protein. Briefly, F-actin was polymerized by adding 2 μM G-actin to gelsolin–actin seeds (100 nM), then diluted 10-fold in the absence or presence of increasing concentrations of recombinant emerin (residues 1–222). Both gelsolin and actin were obtained from Cytoskeleton (catalog #HPG5 and #AKL95, respectively). Gelsolin–actin seeds were made exactly as described (Blanchoin et al. 2000). Alternatively, 2 μM G-actin was polymerized in the absence of gelsolin for 2 h. Polymerized filaments were then incubated with or without 100 nM CapZ. Subsequent polymerization and depolymerization assays were assayed as described above. Actin polymerization in the presence or absence of emerin was monitored by fluorescent microscopy, as described (Blanchoin et al. 2000; Amann and Pollard 2001). Samples were diluted 1:500–1:1000, viewed on a Nikon Eclipse E600W microscope (Nikon, Tokyo, Japan), and images were captured with a Q-imaging Retiga Exi CCD camera (Q Imaging, Burnaby, British Columbia, Canada) using IPLab (version 3.9.2) attached to an Apple G5 computer. Images were converted to TIFF images and lengths of filaments were measured in Photoshop version 7.0 (Adobe Systems, San Jose, California, United States). These studies were funded by the National Institutes of Health (F32 GM067397 and T32 HL07227 to JMH and R01 GM48646 to KLW) and the American Heart Association Scott B. Deutschman Memorial Research Award (KLW). We are grateful to Dyche Mullins, Tom Pollard, and Doug Robinson for advice. We thank the National Cell Culture Center for providing the HeLa cell pellets. Protein identification was done by the AB Mass Spectrometry/Proteomics Facility at Johns Hopkins School of Medicine (http://www.hopkinsmedicine.org/msf) with support from National Center for Research Resources shared instrumentation grant 1S10-RR14702, the Johns Hopkins Fund for Medical Discovery, and the Institute for Cell Engineering. Conflicts of interest. The authors have declared that no conflicts of interest exist. Author contributions. JMH conceived and designed the experiments. JMH performed the experiments and analyzed the data. AKK and KLW contributed reagents/materials/analysis tools. JMH and KLW wrote the paper. KLW was the principal investigator. Academic Editor: Marc W. Kirschner, Harvard University Citation: Holaska JM, Kowalski AK, Wilson KL (2004) Emerin caps the pointed end of actin filaments: Evidence for an actin cortical network at the nuclear inner membrane. PLoS Biol 2(9): e231. 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J Struct Biol 2002 140 3 9 12490148 Percipalle P Fomproix N Kylberg K Miralles F Bjorkroth B An actin-ribonucleoprotein interaction is involved in transcription by RNA polymerase II Proc Natl Acad Sci U S A 2003 100 6475 6480 12743363 Pestic-Dragovich L Stojiljkovic L Philimonenko AA Nowak G Ke Y A myosin I isoform in the nucleus Science 2000 290 337 341 11030652 Rando OJ Zhao K Janmey P Crabtree GR Phosphatidylinositol-dependent actin filament binding by the SWI/SNF-like BAF chromatin remodeling complex Proc Natl Acad Sci U S A 2002 99 2824 2829 11880634 Sakaki M Koike H Takahashi N Sasagawa N Tomioka S Interaction between emerin and nuclear lamins J Biochem (Tokyo) 2001 129 321 327 11173535 Sasseville AM Langelier Y In vitro interaction of the carboxy-terminal domain of lamin A with actin FEBS Lett 1998 425 485 489 9563518 Scheer U Hinssen H Franke WW Jockusch BM Microinjection of actin-binding proteins and actin antibodies demonstrates involvement of nuclear actin in transcription of lampbrush chromosomes Cell 1984 39 111 122 6386181 Segura-Totten M Wilson KL BAF: Roles in chromatin, nuclear structure and retrovirus integration Trends Cell Biol 2004 14 261 266 15130582 Segura-Totten M Kowalski AM Craigie R Wilson KL Barrier-to-autointegration factor: Major roles in chromatin decondensation and nuclear assembly J Cell Biol 2002 158 475 485 12163470 Wang X Xu S Rivolta C Li LY Peng G Barrier to autointegration factor interacts with the cone-rod homeobox and represses its transactivation function J Biol Chem 2002 277 43288 43300 12215455 Wilkinson FL Holaska JM Sharma A Malinal SB Holt I Emerin interacts in vitro with the splicing-associated factor, YT521-B Eur J Biochem 2003 270 2459 2466 12755701 Wilson KL The nuclear envelope, muscular dystrophy and gene expression Trends Cell Biol 2000 10 125 129 10740265 Zastrow MS Vlcek S Wilson KL Proteins that bind A-type lamins: Integrating isolated clues J Cell Sci 2004 117 979 989 14996929 Zhang Q Skepper JN Yang F Davies JD Hegyi L Nesprins: A novel family of spectrin-repeat-containing proteins that localize to the nuclear membrane in multiple tissues J Cell Sci 2001 114 4485 4498 11792814 Zhen YY Libotte T Munck M Noegel AA Korenbaum E NUANCE, a giant protein connecting the nucleus and actin cytoskeleton J Cell Sci 2002 115 3207 3222 12118075 Zheng R Ghirlando R Lee MS Mizuuchi K Krause M Barrier-to-autointegration factor (BAF) bridges DNA in a discrete, higher-order nucleoprotein complex Proc Natl Acad Sci U S A 2000 97 8997 9002 10908652

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020258Research ArticleGenetics/Genomics/Gene TherapyMolecular Biology/Structural BiologyPlantsArabidopsisInterdependency of Brassinosteroid and Auxin Signaling in Arabidopsis Integration of BR and Auxin SignalingNemhauser Jennifer L 1 Mockler Todd C 1 Chory Joanne chory@salk.edu 1 2 1Plant Biology Laboratory, Salk Institute for Biological StudiesLa Jolla, California, United States of America2Howard Hughes Medical Institute, La JollaCaliforniaUnited States of America9 2004 24 8 2004 24 8 2004 2 9 e2585 12 2003 9 6 2004 Copyright: © 2004 Nemhauser et al.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. Hormones Act in Concert to Direct Plant Growth Hormonal Regulation of Plant Growth and Development How growth regulators provoke context-specific signals is a fundamental question in developmental biology. In plants, both auxin and brassinosteroids (BRs) promote cell expansion, and it was thought that they activated this process through independent mechanisms. In this work, we describe a shared auxin:BR pathway required for seedling growth. Genetic, physiological, and genomic analyses demonstrate that response from one pathway requires the function of the other, and that this interdependence does not act at the level of hormone biosynthetic control. Increased auxin levels saturate the BR-stimulated growth response and greatly reduce BR effects on gene expression. Integration of these two pathways is downstream from BES1 and Aux/IAA proteins, the last known regulatory factors acting downstream of each hormone, and is likely to occur directly on the promoters of auxin:BR target genes. We have developed a new approach to identify potential regulatory elements acting in each hormone pathway, as well as in the shared auxin:BR pathway. We show that one element highly overrepresented in the promoters of auxin- and BR-induced genes is responsive to both hormones and requires BR biosynthesis for normal expression. This work fundamentally alters our view of BR and auxin signaling and describes a powerful new approach to identify regulatory elements required for response to specific stimuli. Although distinct sets of growth regulators - auxin and brassinosteroids - are required for cell expansion; rather than being independent signals, the response from each pathway requires the other ==== Body Introduction The continuous shaping of plant form is a marvel of signal integration. In early seedling development this is particularly clear, as environmental cues, such as light, profoundly alter the innate morphogenetic program. How diverse pathways merge to determine a discrete cellular growth response is largely unknown. Auxin, the first plant hormone identified, has been implicated in patterning or growth of virtually every plant tissue from earliest embryo to developing fruit (Liscum and Reed 2002). Brassinosteroids (BRs), the polyhydroxylated steroid hormones of plants, have been linked to many of these same processes, including photomorphogenesis (Clouse 2002). The nature of the relationship between these hormones has remained largely undefined. Many factors in the signal transduction pathways operating downstream from BRs and auxin have been identified. Brassinosteroid Insensitive-1 (BRI1), a plasma-membrane-localized receptor serine/threonine kinase, is essential for BR perception and accounts for most BR-binding activity in Arabidopsis (Wang et al. 2001). A Shaggy/GSK3-type kinase, Brassinosteroid Insensitive-2 (BIN2), acts as a negative regulator of the pathway downstream of BRI1 action (Li and Nam 2002). When BR levels are low, proteins in the BES1/BZR1 family are hyperphosphorylated by BIN2 and targeted for degradation by the proteasome (He et al. 2002; Yin et al. 2002a). Upon BR perception, BIN2 is inactivated by an unknown mechanism which allows hypophosphorylated BES1/BZR1 proteins to accumulate in the nucleus, where they presumably provoke changes in gene expression (He et al. 2002; Yin et al. 2002a). In contrast to BRs, no auxin receptor has been identified. However, exposure to auxin is known to promote rapid turnover of nuclear Aux/IAA proteins by ubiquitin-mediated targeting to the 26S proteasome (Gray et al. 2001). Aux/IAAs are direct negative regulators of the Auxin Response Factor (ARF) family of transcription factors and contain four highly conserved domains numbered I to IV (Abel et al. 1995). Domains III and IV are also found in most ARFs and facilitate dimerization within and between members of both families (Kim et al. 1997; Ulmasov et al. 1997b). ARF proteins bind to a conserved auxin-responsive element (AuxRE) found upstream of many auxin-regulated genes (Ulmasov et al. 1999). Previous studies have suggested that auxin and BRs may have a particularly close relationship among plant hormones. In a variety of bioassays representing diverse species, BRs have been shown to synergistically promote cell elongation when supplied with auxin (Mandava 1988). Clouse and colleagues examined the effect of the two hormones on gene transcription more than a decade ago, and found that while BRs could activate the expression of some auxin-responsive genes, others appeared to be auxin specific (Clouse et al. 1992; Zurek et al. 1994). They also noted that detectable BR effects required much longer treatments compared with the extremely rapid effects of auxin, and concluded that BR-mediated cell elongation effects were likely independent from the auxin signal transduction pathway. Microarray experiments, assaying approximately one-third of the Arabidopsis genome, rekindled interest in the interaction between auxin and BRs, as it was found that a significant percentage of the BR genomic response comprised genes annotated as auxin responsive (Goda et al. 2002; Mussig et al. 2002; Yin et al. 2002a). Recent work from Nakamura and colleagues has shown that three genes—IAA5, IAA19, and SAUR-AC1—are induced by both auxin and BRs and that induction requires BR biosynthesis (Nakamura et al. 2003a, 2003b). In this work, genetic, physiological, and genomic approaches were used to dissect the relationship between auxin and BRs in seedling growth. Together these techniques demonstrated that the relationship between these hormones is far more deeply intertwined than previously suspected. Auxin and BR effects on cell elongation were found to be interdependent, and this physiological interdependency was mirrored at the transcriptional level. In addition, growth and transcriptional effects of exogenous BR treatment could be largely superceded by overstimulation of the auxin pathway. Several lines of evidence suggested that auxin:BR synergism did not depend upon biosynthetic regulation of hormone levels; rather, the two response pathways are likely to converge at the promoters of shared target genes. New computational approaches detected a number of known transcription factor–binding motifs enriched in promoters induced by both hormones, as well as motifs which are overrepresented in promoters activated specifically by auxin or BRs. This multifaceted approach elucidates the mechanism of action of both auxin and BRs in cell expansion, and serves as a model for interrogating complex signaling networks. Results Auxin and BRs Interact Synergistically to Promote Hypocotyl Elongation Early studies of BR effects in a variety of bioassays suggested that there was a synergistic interaction between auxin and BRs (Mandava 1988). We confirmed and extended these studies to the reference plant Arabidopsis thaliana, using hypocotyl (primary stem) length as a quantitative measure of growth. Both hormones are known to induce cell elongation, and exogenous BR treatment has been shown to increase hypocotyl length (Nemhauser et al. 2003). In contrast, addition of auxin to media has only modest effects on seedling hypocotyl elongation, likely as a result of inefficient acropetal transport from root to shoot (Gray et al. 1998). However, increased temperature has been demonstrated previously to be an effective method of altering auxin levels in the shoot and leads to robust increases in hypocotyl length (Gray et al. 1998; Zhao et al. 2002). In our conditions, hypocotyls of plants grown at 29 °C were approximately 1.8 times longer than those of plants grown at 22 °C, consistent with what has been observed by others (Gray et al. 1998; Zhao et al. 2002). When exogenous brassinolide (BL), the most biologically active BR, was applied, hypocotyls of plants grown at elevated temperature exhibited a “kinked” morphology and agravitropic growth, typical of saturating BL conditions (data not shown). In order to examine the relationship between auxin and BRs, it was necessary to find conditions where auxin levels were increased but at subsaturating levels for the hypocotyl growth-promoting response. Plants grown at 26 °C versus 22 °C showed measurable increases in both hypocotyl elongation and levels of auxin intermediates (Zhao et al. 2002). Using these conditions, it was possible to observe that plants grown at higher temperatures were more sensitive to exogenous BR treatment, both in threshold levels for response as well as in terms of absolute growth (Figure 1A). Figure 1 BR and Auxin Pathways Are Interdependent, as Measured by Hypocotyl Elongation (A) Mild temperature elevation causes elongation of the hypocotyl and BR hypersensitivity in WT plants. Columbia ecotype is shown but results are similar for Wassilewskija. Hypocotyls of 3-d-old plants grown at either 26 °C (diamonds, dashed line) or 22 °C (circles, solid line) were measured. (B) det2-1 plants are defective in BR biosynthesis and are also insensitive to the temperature increase. As the det2 deficiency is rescued by exogenous BL, temperature sensitivity is restored. (C) Plants with the weak bri1-5 mutation are insensitive both to temperature and exogenous BR. (D–H) BR response depends upon auxin response. WT is shown in circles with a solid thin line and mutants are shown in squares with a thick dashed line. Known auxin response mutants axr2-1 (D), axr1-12 (E), tir1-1 (F), and axr3-1 (G) have decreased BR response. (F) tir1 has no hypocotyl elongation phenotype in the absence of exogenous hormone treatment and only very modest effects on BR sensitivity. Response is significantly reduced in tir1 mutants at 100 nM BL, as measured by Student's t-test (p = 0.03, using Bonferroni adjustment for multiple tests; Hochberg 1988). (H) yucca plants, which overproduce auxin, also show reduced BR response. Error bars represent standard error. Data in (F) and (G) were collected in a separate experiment from other panels, resulting in small differences in the values for WT hypocotyl length. BR- and auxin-mediated growth promotion required both pathways to be intact. As has been shown previously, hypocotyls of det2 mutants defective in BR biosynthesis (Li et al. 1996) fail to elongate with increased temperature (Gray et al. 1998; Zhao et al. 2002). Importantly, the hypersensitivity of det2 plants to exogenous BR was enhanced by increased temperature, suggesting that these two responses are tightly linked (Figure 1B). Weak bri1 mutants were also unresponsive to temperature, suggesting that auxin response was dependent on a functional BR signal transduction pathway (Figure 1C). The dramatic growth enhancement caused by overproduction of auxin in the yucca mutant (Zhao et al. 2001) requires functional BRI1, as yucca bri1 mutants are dwarfs (Figure 2). Conversely, BR response was dependent on a functional auxin signal transduction pathway as axr1 (Lincoln et al. 1990) and axr2 (Timpte et al. 1994) mutants with reduced auxin response showed significantly reduced sensitivity to BR treatment (see Figure 1D and 1E). The degree of BR insensitivity is correlated with the level of reduced auxin responsiveness, as tir1 mutants, which show only subtle phenotypes in the absence of exogenous auxin (Ruegger et al. 1998), exhibited only a modest reduction in BR response (see Figure 1F). axr3 mutants, which in many assays display a constitutive auxin response (Leyser et al. 1996), were insensitive to BRs (see Figure 1G). This suggests that the BR insensitivity observed in axr1 and axr2 mutants is not simply a block in cell elongation, and that regulated turnover of Aux/IAA proteins, such as those encoded by AXR2 and AXR3, is required for normal BR response. yucca mutants were also largely insensitive to exogenous BR and appeared saturated for the BR response (see Figure 1H). Figure 2 Enhanced Hypocotyl Elongation of yucca Mutants Requires Functional BRI1 (A) Average hypocotyl lengths of 3-d-old plants. Error bars represent standard error. (B) Ten-day-old WT, yucca, yucca bri1-116, and bri-116 seedlings. Auxin and BR Transcriptional Responses Substantially Overlap Previous studies have identified several auxin-responsive genes that are also regulated by BRs (Goda et al. 2002; Mussig et al. 2002; Yin et al. 2002a; Nakamura et al. 2003a, 2003b). To comprehensively compare the genomic effects of treatment with each hormone, Affymetrix oligonucleotide microarrays, representing approximately 22,000 genes, were hybridized with probes from two biological replicates following mock or BR treatment. Linear models were used to identify 342 transcripts whose levels were increased following BR treatment (Figure 3A; Tables S1 and S3). The levels of 296 transcripts were decreased in the same treatment (Figure 3A; Tables S2 and S4). Comparison with newly analyzed data from a similar experiment using auxin-treated seedlings (Zhao et al. 2003) showed that nearly a quarter of genes upregulated by either auxin or BR treatment were regulated by both hormones (Figure 3A and 3C; Tables S1–S6). This is a much larger overlap than that reported in the recent study by Goda and colleagues (2004), likely reflecting substantial differences in experimental design and analysis methods, including the use of different microarrays. In addition, at least 75% of the genes identified as BR inducible were late responders (only observed after 12 or 24 h of BR treatment) and therefore were not included in the analysis described here. Figure 3 BR and Auxin Have Shared Genomic Effects (A) Venn diagram showing relative proportion of BR- and auxin-responsive genes and the degree of overlap. (B) Functional categories of BR–auxin shared genes reveal a potential growth signature. (C and D) Effects of auxin on BR-regulated gene expression. Transcripts which show elevated levels are shown in orange, those with decreased levels are shown in blue, and those transcripts whose levels are not changed are shown in yellow. (C) Relative ratios were derived from the following comparisons (from left to right): BR versus mock treatment (WT plants; B), auxin versus mock treatment (WT plants; A), and yucca versus WT (Y). The three columns to the left are BR-upregulated genes and the three columns to the right are BR-downregulated genes. Among the BR-upregulated genes, there are a large number that are also induced by auxin treatment or in a yucca background. Few BR-repressed genes are repressed by auxin. nc, no change. (D) Effect of BR treatment in yucca background. Relative ratios represent BR versus mock treatment in WT plants (WT) or in yucca mutants (YB). Approximately two-thirds of BR-regulated genes were not affected by BR treatment of yucca plants. (E) Quantitative PCR shows that shared target genes are synergistically induced when treated with both auxin and BRs. At5g64770 encodes a protein with unknown function. At1g18400 encodes BEE1, a bHLH-containing protein known to be required for the BR response (Friedrichsen et al. 2002). At1g10550 and At4g30290 are putative endoxyloglucan transferases. Asterisks indicate response under an additive model. As much of the auxin response is transient, yucca plants which continuously experience high levels of auxin have a different profile of altered transcript levels than plants exposed to exogenous auxin for a short time period (Zhao et al. 2002). To produce a more complete list of auxin-responsive genes, RNA from yucca seedlings was isolated and used to probe additional microarrays. More than 20% of all BR-upregulated genes were also differentially regulated in a yucca background (Figure 3C; Tables S1 and S2). In combination, 40% of the BR-upregulated genes were altered either by auxin treatment or in yucca mutants (see Table S1). Members of all known auxin-responsive gene families were identified, as has been seen in previous microarray experiments representing a smaller fraction of the genome (Goda et al. 2002, 2004; Mussig et al. 2002; Yin et al. 2002a). While auxin treatment had no effect on ARF gene expression, transcripts of ARF4 (At4g30080) and ARF8 (At5g37020) were negatively regulated by BR treatment (see Tables S2 and S4). This is the first evidence of transcriptional regulation of ARF genes. In addition, BRs repressed the expression of several auxin transport–related transcripts, including PIN3 (At1g70940), PIN4 (At2g01420), PIN7 (At1g23080), and an AUX1-like gene (At1g77690). Auxin induced the expression of BRI1 and a close paralog, BRL3 (At3g13380), and repressed the expression of another BRI1-like gene, VH1/ BRL2 (At2g01950) (Clay and Nelson 2002; Yin et al. 2002b). It is possible that the genes identified here as auxin and BR responsive may represent a common growth signature regulated by many factors during seedling development. The majority of these genes do not have known functions; however, many of the rest are known or predicted to be involved in cell expansion, metabolism, and signal transduction (Figure 3B). Integration between Auxin and BR Signals Occurs in the Nucleus Many plant hormones directly regulate the levels of other hormones (Alonso and Ecker 2001). This complicates analysis of cross-talk, which is defined by shared signal transduction components. The interdependency between auxin and BRs does not function primarily through regulation of hormone levels. Auxin does not induce BR biosynthesis. det2 plants, which are hypersensitive to exogenous BR treatment, were insensitive to growth at elevated temperature (see Figure 1B). Auxin treatment does not affect the subcellular localization of BES1 (Yin et al. 2002a), and growth at elevated temperature does not alter BES1 levels or phosphorylation state (unpublished data). Conversely, BRs do not regulate auxin biosynthesis. Nakamura and colleagues (2003a) reported that det2 mutants make at least normal amounts of auxin and that BR treatments do not alter auxin levels. It was recently reported that the stability of an IAA1:luciferase fusion protein was unchanged following BR treatment, though the data were not shown (Zenser et al. 2003). Here, we used a heat shock–inducible β-glucuronidase (GUS) reporter fused to the N-terminal portion of AXR3 described by Gray and colleagues (2001). This construct was rapidly turned over in the presence of auxin but showed no change in stability following BR treatment (Figure 4D). Figure 4 Endogenous BR Levels Affect Expression of an Auxin-Responsive Reporter but Do Not Induce Aux/IAA Protein Turnover (A) WT, (B) det2, and (C) DW4FOX plants carrying the DR5::GUS transgene. (A) GUS staining is particularly strong in young leaves (yellow arrow). (B) det2 plants show no GUS staining in aerial tissues. (C) DWF4OX plants show increased intensity of staining, particularly at the tips of emerging leaves (yellow arrow) and in the hypocotyl (orange arrows). Inset shows hypocotyl-root junction. (D) Aux/IAA stability does not appear to be affected by treatment with BRs. Plants carrying a heat shock–inducible fusion of the N-terminal portion of AXR3 and GUS reporter were subjected to 2 h at 37 °C and then treated with mock or hormone treatments for the time periods listed. Together, these results suggested that the interaction between the auxin and BR pathways was likely at the promoters of shared target genes. To test whether the auxin:BR synergism was detectable at the level of gene transcription, transcript levels from four genes identified in the microarray studies were quantified in plants exposed to exogenous treatment of either hormone or both in combination (see Figure 3E). In all cases, levels of these transcripts were regulated nonadditively in the presence of both hormones. If, as suggested by these results, BR and auxin response pathways converge at the level of gene activation, we reasoned that yucca plants, which are largely insensitive to BR for growth promotion, might also show a reduced BR genomic response. RNA was isolated from yucca plants treated with BR and used to probe additional microarrays. Approximately two-thirds of genes showing BR responsiveness in wild-type (WT) plants were no longer affected by BR treatment in a yucca background (see Figure 3D; Tables S1 and S2). This result strongly suggests that auxin and BR treatment affect transcription of these target genes by a common mechanism. Promoters of Coordinately Regulated Genes Share Regulatory Motifs Computational analysis of coordinately regulated genes is an emerging tool for dissecting regulatory networks (e.g., DeRisi et al. 1997; Harmer et al. 2000; Tullai et al. 2004). To identify potential regulatory elements acting in these pathways, a list of all genes regulated by either auxin or BR was generated, and 500 bp upstream of each gene were identified. These promoters were split into three groups: those with increased transcript levels following treatment with BR only (B group; n = 258), those with increased transcript levels following auxin treatment only (A group; n = 254), and those genes whose transcripts were induced following treatment with either hormone (AB group; n = 82). Known plant promoter elements and their annotations were downloaded from PLACE (Higo et al. 1999) and used to screen each promoter list. The expected number of occurrences of each PLACE motif was estimated using 1,000 sets of n promoters randomly sampled from the genome, where n is equal to the number of promoters in each group (A, B, or AB). This approach offers a significant advantage over other background models used to assess enrichment. Permuted distributions reflect real expected frequencies and do not rely on assumptions about genome architecture. In addition, the normal distribution of site frequencies observed with large numbers of permutations allows for the use of powerful parametric statistical methods. Moreover, the ease of filtering based on relative probabilities makes this approach ideally suited to comparisons of promoters regulated in different conditions. In this study, matches were considered significant if a motif was overrepresented in a given set (p < 0.1) and present in at least 10% of group promoters. This analysis identified several motifs specifically enriched in a given group (Table 1), as well as several motifs found to be enriched in multiple groups (Table 2). Table 1 PLACE Motifs Enriched Specifically in AB, A, or B Promoters Motifs with related patterns are grouped together by color aTotal number of sites identified bExpected number of sites based on 1,000 randomly sampled groups of promoters cPercentage of promoters containing at least one site dTranscription factor family known to bind this element <, value is less than 0.001; SA, salicylic acid DOI:10.1371/journal.pbio.0020258.t001 Table 2 PLACE Motifs Enriched in Promoters of Multiple Groups See text and Table 1 caption for abbreviations DOI:10.1371/journal.pbio.0020258.t002 One of the sequences enriched in the B group was TGTCTC, previously identified as an auxin-responsive element (Ulmasov et al. 1995) termed ARFAT in the PLACE database. Surprisingly, this sequence was not significantly enriched in the A set (p = 0.78). However, the A, B, and AB groups showed significant enrichment of the core ARF-binding element TGTC in their promoters, perhaps reflecting some sequence divergence between Arabidopsis and soybean, where the element was first identified. A well-characterized synthetic element containing the ARFAT called DR5 (Ulmasov et al. 1997a) could be used to test the BR responsiveness of this element and was therefore introduced into plants with altered BR levels. In det2 plants with lower endogenous levels of BRs (Li et al. 1996), DR5 expression was greatly reduced, particularly in the shoot (Figure 4A versus 4C). Conversely, in plants with increased levels of BRs caused by overexpressing a BR biosynthetic gene, DWF4 (Wang et al. 2001), DR5 expression was increased (Figure 4A versus 4B). DR5 expression was also increased following transient BR treatment of WT plants carrying the DR5 reporter (unpublished data). Nakamura and colleagues (2003a) also recently demonstrated the BR inducibility of DR5::GUS and found no change in endogenous IAA levels following BR treatment, providing further evidence that BR transcriptional effects are direct. These data strongly suggest that the ARF-binding element requires both hormones for proper expression and should be considered a Brassinosteroid-Auxin Response Element. This finding raises questions about the utility of the DR5 element as a reporter of auxin response, as it likely reflects regions of regulatory overlap between the two pathways. Consensus binding sites for several families of transcription factors were identified as enriched in the AB set (see Table 1). The presence of a MYC consensus site in more than 80% of AB promoters was quite striking, especially in light of the BR and auxin inducibility of the bHLH-containing Brassinosteroid Enhanced Expression 1 (BEE1; At1g18400) gene, which is known to function in BR response (Friedrichsen et al. 2002). Many of the other AB consensus motif matches were implicated in regulation by light or abscisic acid (ABA), both of which have been linked previously to BR-mediated growth response by physiology and genetics (Nemhauser and Chory 2002). For the B set, there was widespread occurrence of a GT-1 consensus binding motif, as well as evidence for a MYB-binding site distinct from that found in the A set. Identification of several elements specific for the A set, including those known to bind WRKY-family members, suggests attractive targets for designing new reporters which may not be BR dependent. Several instances of light-regulated motifs are intriguing given the strong evidence for a close relationship between auxin and light responses (Tian and Reed 2001). Several of the promoter elements identified in the A, B, and AB promoters were found as multiple copies within promoters, including the core ARF-binding element TGTC. Recent studies have suggested that ARF dimerization is not required for activation of ARFAT-mediated transcription (Tiwari et al. 2003). Interestingly, a scan of AB promoters revealed that nearly half of all AB promoters contain at least one instance of multiple copies of the core TGTC element within a 50-bp window. Clustering of TGTC sites was also seen in the A set (42% of promoters contain at least one pair of sites within 50 bp) and somewhat less frequently in the B set (33%). This finding suggests that interactions between ARFs may be important for hormone responsiveness of natural promoters, in addition to enhancing auxin inducibility of synthetic multimerized ARFATs. As specific binding factors are not known for most of the other elements identified, exact nucleotides required for factor binding are not known. Therefore, this analysis is likely a conservative estimate for the number of true transcription factor–binding sites present in each promoter. Discussion With the notable exception of auxin, most plant hormones are produced and perceived throughout the plant body. Modulation of hormone response stems from regulation of hormone levels and/or signal transduction components, as well as from interactions with other signaling pathways. There are many examples of cross-talk between hormones in plant biology. In addition to auxin and BRs, gibberellins (GAs), ethylene, ABA, and cytokinin have all been shown to affect hypocotyl elongation (reviewed in Nemhauser and Chory 2002). As mentioned previously, some of these hormones interact through biosynthetic regulation. For example, auxin, ABA, and cytokinin stimulate ethylene biosynthesis, particularly when supplied at high levels (Yang and Hoffman 1984; Vogel et al. 1998; Ghassemian et al. 2000). Physiological and genetic evidence suggests that auxin, GAs, and ethylene promote hypocotyl growth by largely independent means (Gray et al. 1998; Collett et al. 2000). Similarly, BRs and GAs interact additively in most cell elongation bioassays (Mandava et al. 1981), and analysis of bri1 mutants suggests that the two hormones independently and antagonistically regulate transcription of some target genes (Bouquin et al. 2001). In contrast, auxin and BRs interact synergistically and interdependently to promote hypocotyl cell elongation, making their relationship unique among plant growth regulators. The nature of hormone interactions may be tissue specific. A recent study demonstrated that auxin acts primarily through GAs to promote root elongation, and proposed that the DELLA family of negative regulators was a point of convergence between the two pathways (Fu and Harberd 2003). One possible complication for this interpretation is that auxin is required for normal GA biosynthesis in pea (Ross et al. 2000) and thus, the effects of auxin on DELLA protein stability may be indirect. We have preliminary evidence that interactions between auxin and BRs may be different in aerial tissues than in roots. While auxin and BRs promote hypocotyl elongation, the hormones have opposite effects on root hair growth (J. L. Nemhauser and J. Chory, unpublished data). In addition, reduced BR levels or response may actually increase auxin effects on root pericycle proliferation (J. L. Nemhauser, N. Geldner, and J. Chory, unpublished data). While auxin and BRs stimulate elongation of the hypocotyl, light antagonizes this effect. The AB genes induced by auxin and BRs may be targets for repression by the light response. Plants with reduced BR levels or response show a light-grown phenotype even when grown in the dark, including a short hypocotyl, expansion of cotyledons, and production of leaves. Many mutants with stabilized Aux/IAA proteins also show this deetiolated phenotype (Tian and Reed 2001). Levels of BRs may be light regulated (Kang et al. 2001), and response to BRs is affected by light quality and intensity (Nemhauser et al. 2003). Interestingly, two photoreceptors, PHOT1 (At3g45780) and Phytochrome E (At4g18130), are both downregulated by BRs. Two potential negative regulators of the light response, PKS1-like (At5g04190) and DRT100 (At3g12610), are upregulated by both auxin and BRs. Differential regulation of target genes by auxin, BRs, and light may allow fine-tuning of the photomorphogenetic response. Bioinformatic Analysis of Signaling Networks The regulation of gene expression in eukaryotes is complex and is largely mediated by multiple transcription factors that bind within regulatory regions upstream of the coding sequence. In the simplest model, coexpressed genes exhibit similar expression characteristics because they are regulated by the same transcription factors. A number of algorithms have been developed to identify potential regulatory motifs overrepresented in the promoter sequences of coregulated genes (reviewed in Rombauts et al. 2003). Each algorithm requires a background model to calculate the expected frequency for each motif. The simplest background model estimates the expected frequency for a given motif based on the single nucleotide composition of the analyzed sequences (Bailey and Elkan 1995; Roth et al. 1998). Improvements on these methods use so-called higher-order models based on Markov chain statistics (Thijs et al. 2001, 2002; Marchal et al. 2003), building the background model by estimating the probability at each nucleotide position based on the previous bases in the sequence. Other approaches include enumerative methods that generate background models based on whole-genome motif counts from noncoding intergenic (van Helden et al. 1998) or randomly sampled (Marino-Ramirez et al. 2004) genomic sequences. Because biological sequences are inherently nonrandom, we chose another approach to build our background model. For each motif under consideration, we modeled the expected frequency distribution by randomly sampling sets of promoter sequences from among all the genes represented on the microarrays used in our study. Therefore, we could directly estimate the statistical significance for each motif from its Z score, which is the number of standard deviations by which the observed frequency exceeds the expected frequency based on the distribution observed in the permutation sampling. In contrast to other methods, our approach uses a background model based on a real distribution of motif counts derived from annotated promoter sequences, rather than estimating expected word frequencies from simulated or randomly selected genomic sequences or from models based on distribution functions. Thus, given any set of Arabidopsis genes clustered on the basis of similar expression, we could easily identify overrepresented known transcription factor–binding motifs or overrepresented novel presumptive promoter elements. For example, new experiments assaying genomic effects of different hormone treatments or environmental conditions could be used to define finer groupings of coregulated genes and could be readily integrated into our current analysis. A Model for Auxin:BR Synergy Auxin:BR synergism results from convergence of the two response pathways on a common mechanism for promoting cell elongation. The integration of these hormone signals occurs very late in signal transduction, likely at the promoters of more than 80 genes whose expression is induced by short treatments with either hormone. Several known regulatory elements have been identified in these common target genes. The well-characterized auxin-response element ARFAT is one crucial node of intersection between the BR and auxin pathways, as it is BR responsive and requires BR synthesis for normal expression. More than 20 ARFs have been identified in the Arabidopsis genome (Liscum and Reed 2002). Many have been shown to bind the ARFAT motif and promote auxin-inducible gene expression (Ulmasov et al. 1997b; Tiwari et al. 2003). Stabilization of Aux/IAA proteins, such as AXR2 and AXR3, completely blocks BR growth responses. We propose a model where auxin and BR pathways converge on regulation of ARF transcription factors (Figure 5). Figure 5 A Model of BR–Auxin Interaction Auxin and BR signals are likely integrated on promoters of shared target genes. The node(s) of intersection between auxin and BR pathways must be downstream of BES1 and Aux/IAAs and upstream of gene expression. One likely mechanism is via regulation of transcriptional complexes, such as those containing the ARFs. Cross-talk is a common feature of animal growth regulator pathways. For example, glucocorticoids synergistically enhance the effects of retinoic acid in mouse cells (Subramaniam et al. 2003). Upon ligand binding, the glucocorticoid receptor directly interacts with the homeodomain protein Pbx1 and activates transcription of Hoxb-1. In Xenopus, transcriptional activation of several genes, including twin, siamois, and nodal-related-3, requires stimulation of both TGFβ and WNT pathways. Similarly, two transcription factors, SOX10 and KROX20, have been recently reported to interdependently regulate expression of a neural crest–specific enhancer conserved among mouse, human, and chicken (Ghislain et al. 2003). This type of coregulation is also seen in plants. One example is the synergistic interaction between osmotic stress and ABA response, which is likely mediated by interaction between DREB and AREB transcription factors (Narusaka et al. 2003). In all of these cases, signal integration is achieved by formation of a complex containing transcription factors independently regulated by each pathway, often binding to composite regulatory elements. By integrating the inputs of multiple pathways, these mechanisms provide cellular or regional specificity for a given response. ARFAT was originally identified as part of a composite element (Ulmasov et al. 1995). However, DR5 has been characterized as a multimerized simple response element (Ulmasov et al. 1997b) and can be activated by either auxin or BRs. So, unlike in the systems described above, auxin and BR signals likely converge on the same family of transcription factors. Such a relationship has recently been described for ethylene and jasmonate in plant defense responses (Lorenzo et al. 2003). Both ethylene and jasmonate pathways are required to induce expression of the transcription factor ERF1, which in turn regulates the expression of a number of defense-related genes. Neither auxin nor BRs have large effects on ARF transcription, and several AB targets are early-response genes not requiring de novo protein synthesis for activation (Friedrichsen et al. 2002; Liscum and Reed 2002). Auxin and BRs likely regulate ARF complex activity posttranslationally rather than through transcriptional regulation. Auxin is already known to modulate ARF activity by regulating the stability of the interacting Aux/IAA repressor proteins (Gray et al. 2001; Tiwari et al. 2003). BR perception could increase ARF activity by leading to modification of the ARFs themselves or through interactions with a BR-regulated transcriptional coactivator. The additional transcriptional regulation of some ARFs by BRs, together with auxin and BR effects on a number of Aux/IAA genes, could favor formation of particular transcriptional complexes promoting growth. Five genes encoding proteins with DNA-binding motifs were induced by both hormones, including members of the MYC, EREBP, and leucine zipper families. Higher-order interactions among several transcription factor complexes, perhaps directly involving members of the BES1/BZR1 family, could provide additional control of the shared auxin:BR response pathway. A longstanding question in plant biology has been how a small number of hormones with overlapping functions can provoke a wide range of responses. Combinatorial control has long been suggested as one possible explanation (e.g., Singh 1998). The detailed analysis of BR and auxin pathways in this work suggests that hormone response is determined by the cellular milieu. Additional factors, including other hormones and environmental stimuli, can be incorporated into this model, leading ultimately to a detailed map of plant growth processes. Materials and Methods Hypocotyl measurements Seeds were sterilized for 15 min in 70% ethanol, 0.01% Triton X-100, followed by 10 min of 95% ethanol. After sterilization, seeds were suspended in 0.1% low-melting-point agarose and spotted on plates containing 0.5× Murashige Minimal Organics Medium (Gibco-BRL, San Diego, California, United States), 0.8% phytagar (Gibco-BRL), and one of five concentrations of BL (0, 1, 10, 100, or 1,000 nM). Seeds on plates were then stratified in the dark at 4 °C for 2 d. Plants were grown in approximately 35 μmol m−2s−1 white light with a red:far-red light ratio near 1. Plate position was changed every 24 h to minimize position effect. Hypocotyl lengths were measured from 10 to 14 3-d-old seedlings. Seedlings were removed from one plate at a time and scanned between two transparencies on a flatbed scanner. NIH Image 1.62 was used to perform length measurements. All dose-response experiments were performed in duplicate. bri1-5 is a weak allele in a Wassilewskija background. All other mutants used in this work are in a Columbia background. GUS staining GUS staining protocol was as described in Sessions et al. (1999). Induction of AXR3-NT-GUS lines was as described in Gray et al. (2001). Microarray studies Nine-day-old, light-grown Arabidopsis seedlings were immersed in 1 μM BL in 0.5× Murashige Minimal Organics Medium (Invitrogen, Carlsbad, California, United States) or medium alone for 2.5 h before they were harvested for total RNA preparation. Total RNA from the treated seedlings was used for preparing probes for the microarray experiments, which were carried out according to the protocols provided by the gene chip manufacturer Affymetrix (Santa Clara, California, United States). All experiments used two independent biological replicates. Details of the auxin experiment have been described previously (Zhao et al. 2003). Data analysis was performed in R (Ihaka and Gentleman 1996). Genes were normalized using rma in the Bioconductor affy package (http://www.bioconductor.org; Irizarry et al. 2003) and subsequently analyzed using linear models and Empirical Bayes analysis (limma package; Smyth 2004). To be considered differentially expressed, genes were required to have a false discovery rate adjusted p value of less than 10% and an empirical Bayes log odds of differential expression (B) greater than 0. Data are available at Gene Expression Omnibus; see Supporting Information for accession numbers. Quantitative PCR Plants were treated with hormones as above using treatments of either 1 μM BL, 1 μM indole-3-acetic-acid (auxin), both hormones, or a mock treatment. Total RNA was extracted using a Qiagen (Valencia, California, United States) RNAeasy kit and first-strand cDNA was synthesized using an Invitrogen Superscript First-Strand cDNA Synthesis kit. cDNAs were diluted 20-fold and combined with SYBR master mix (PE Biosystems, Wellesley, California, United States) for PCR. Primers were as follows: At5g64770 (5′-CTTCTCATACTCTTCATTTCCTCTCCTACT-3′, 5′-TTCTCGTAAGCTTCGTGCTTGA-3′), At1g18400 (5′-CTAGCGGCGTCTCCGATAAT-3′, 5′-AAGAACCTGTTTCAGTGGCAATAAC-3′), At1g10550 (5′-AAGCTTCCCGCTGGATTTG-3′, 5′-TTGATAAATAGAAAGCAACCACAACAC-3′), and At4g30290 (5′-TCCCTGGTAACTCTGCTGGAA-3′, 5′-CCGGAGATTTAAGATAGAATGTTGTGA-3′). At5g15400 (ubiquitin) was used to normalize all values (5′-TGCGCTGCCAGATAATACACTATT-3′, 5′-TGCTGCCCAACATCAGGTT-3′). PCR reactions were performed in triplicate and analyzed using an ABI PRISMA 7700. A standard curve was constructed for each primer using an equal mixture of all cDNAs. Sequences for promoter analysis We used a Perl script to extract the 500 bp of sequence preceding the 5′ end of each annotated transcription unit in the AGI pseudomolecules annotation (14-May-2003) downloaded from NCBI. These putative promoter sequences begin immediately upstream of the 5′ UTR for transcription units with an annotated 5′ UTR, and upstream of the annotated translational start for the remainder. Promoter analysis and significance calculations We analyzed putative promoter regions upstream of auxin- and BR-regulated genes to identify overrepresented promoter elements. One thousand surrogates of each promoter set were created by randomly shuffling the list of genes represented on the Affymetrix ATH1 arrays and then sampling n genes and extracting 500-bp promoter sequences for the sampled set of genes. Known plant promoter elements and their annotation were downloaded from PLACE (Higo et al. 1999). For each set of n promoters, the null distribution for each PLACE motif was modeled by counting the number of occurrences for each word within each of the 1,000 surrogate sets of n promoters. Using this approach we could then ask how well the observed frequency of a certain motif in a set of n promoters matched the frequency that would be expected for a random set of n promoters. We estimated the one-tailed p value for each motif based on the Z score of the difference of the actual word count of the promoter set (Ctrue) minus the mean count from the 1,000 surrogates (Csurr) relative to the SD from the 1,000 surrogates (SDsurr) [i.e., Z = (Ctrue − Csurr)/SDsurr]. Thus for each motif the p value we calculated was the probability to the right of the observed count calculated on the null distribution derived from sampling promoters randomly from the genome. We considered a motif to be significantly overrepresented if this probability was less than 0.1. These calculations were implemented using Perl scripts and a relational database (MySQL). Supporting Information Table S1 Fold Change of BL-Upregulated Genes following Exposure to BL or IAA (Auxin) Treatment Effects of increased auxin levels in the yucca mutant are shown as compared to WT and following BL treatments. The comparisons from left to right are WT BL- versus mock-treated, WT IAA- versus mock-treated, yucca mock-treated versus WT mock-treated, and yucca BL- versus mock-treated. nc, no change. (160 KB XLS). Click here for additional data file. Table S2 Fold Change of BL-Downregulated Genes following Exposure to BL or IAA (Auxin) Treatment Effects of increased auxin levels in the yucca mutant are shown as compared to WT and following BL treatments. The comparisons from left to right are WT BL- versus mock-treated, WT IAA- versus mock-treated, yucca mock-treated versus WT mock-treated, and yucca BL- versus mock-treated. nc, no change. (169 KB XLS). Click here for additional data file. Table S3 Normalized Values of BL-Upregulated Genes ave, average; se, standard error. (64 KB XLS). Click here for additional data file. Table S4 Normalized Values of BL-Downregulated Genes ave, average; se, standard error. (64 KB XLS). Click here for additional data file. Table S5 Values of IAA-Upregulated Genes ave, average; se, standard error. (63 KB XLS). Click here for additional data file. Table S6 Normalized Values of IAA-Downregulated Genes ave, average; se, standard error. (26 KB XLS). Click here for additional data file. Accession Numbers The Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/) accession numbers for the genes and gene products discussed in this paper are WTBR1 (GSM13423), WTBR2 (GSM13424), WTmock1 (GSM13420), WTmock2 (GSM13421), wtzm1 (GSM13430), wtzm2 (GSM13432), wtzmIAA1 (GSM13433), wtzmIAA2 (GSM13434) and, yuccaBR1 (GSM13428), yuccaBR2 (GSM13429), yuccamock1 (GSM13426), and yuccamock2 (GSM13427).The associated experimental descriptions are available at accession numbers GSE862 (BR effects on WT and yucca seedlings) and GSE863 (auxin effects on seedlings). We thank J. Ecker, J. Long, J. Umen, and M. Offenbacher for careful reading of the manuscript, Y. Huang and J. Borevitz for invaluable assistance with and insights into microarray analysis, Y. Zhao and B. Burger for stimulating discussions, and M. Estelle and O. Leyser for providing seeds. The BR microarray experiments were done in collaboration with S. Mora-Garcia and Y. Yin. This work was supported by grants from the National Institutes of Health (NIH) (GM52413), United States Department of Agriculture, and National Science Foundation (MCB-0315845) to JC. JLN and TCM are NIH postdoctoral fellows (F32 GM20742 and F32 GM69090); TCM was also supported by the Bechtel Foundation. JC is an investigator of the Howard Hughes Medical Institute. Conflicts of interest. The authors have declared that no conflicts of interest exist. Author contributions. JLN and JC conceived and designed the experiments. JLN performed the experiments. JLN and TCM analyzed the data. TCM wrote scripts and performed bioinformatic analysis. JLN, TCM, and JC wrote the paper. Academic Editor: Jeffrey Dangl, University of North Carolina Citation: Nemhauser JL, Mockler TC, Chory J (2004) Interdependency of brassinosteroid and auxin signaling in Arabidopsis. PLoS Biol 2(9): e258. 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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020264Research ArticleBiophysicsNeuroscienceCatAmplification of Trial-to-Trial Response Variability by Neurons in Visual Cortex Response Variability in Visual CortexCarandini Matteo matteo@ski.org 1 1Smith-Kettlewell Eye Research Institute, San FranciscoCaliforniaUnited States of America9 2004 24 8 2004 24 8 2004 2 9 e26420 2 2004 10 6 2004 Copyright: © 2004 Matteo Carandini.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. The Case of the Noisy Neurons The visual cortex responds to repeated presentations of the same stimulus with high variability. Because the firing mechanism is remarkably noiseless, the source of this variability is thought to lie in the membrane potential fluctuations that result from summated synaptic input. Here this hypothesis is tested through measurements of membrane potential during visual stimulation. Surprisingly, trial-to-trial variability of membrane potential is found to be low. The ratio of variance to mean is much lower for membrane potential than for firing rate. The high variability of firing rate is explained by the threshold present in the function that converts inputs into firing rates. Given an input with small, constant noise, this function produces a firing rate with a large variance that grows with the mean. This model is validated on responses recorded both intracellularly and extracellularly. In neurons of visual cortex, thus, a simple deterministic mechanism amplifies the low variability of summated synaptic inputs into the large variability of firing rate. The computational advantages provided by this amplification are not known. A simple model accounts for the high variability of firing rates observed in responses of cortical neurons to visual stimuli ==== Body Introduction In the primary visual cortex (V1), different trials of presentation of an identical stimulus yield highly variable firing rates (Heggelund and Albus 1978). This trial-to-trial variability is not inherited from subcortical inputs, as these respond in a much more consistent fashion (Kara et al. 2000). Instead, variability has been related to spontaneous variations in cortical state (Arieli et al. 1996; Buracas et al. 1998; Tsodyks et al. 1999; Kenet et al. 2003). These variations may reflect the perceptual effects associated with a stimulus, rather than the presence of the stimulus itself (Ress and Heeger 2003). A key property of trial-to-trial variability is that it depends on the strength of the stimulus: Response variance across trials is approximately proportional to response mean (Tolhurst et al. 1981). An example of this effect can be seen in the responses of a cell in cat V1 to drifting gratings (Figure 1A–1C). Different trials of an identical stimulus elicit firing rates that vary greatly (Figure 1A). As a result, the standard deviation of the firing rates is roughly comparable to their mean amplitude (Figure 1B and 1C). The ratio of variance to mean is close to the value predicted for a Poisson process (Figure 2A, dashed line). For a Poisson process, the variance of the spike counts is equal to the mean. Once spike counts are converted to firing rate by binning in 10-ms windows (i.e., at 100 Hz), the ratio of variance to mean becomes 100. The Poisson-like behavior of firing rates is well known, although reports differ on the exact value of the ratio of variance to mean (Tolhurst et al. 1981; Bradley et al. 1987; Vogels et al. 1989; Geisler and Albrecht 1997; Gur et al. 1997; Reich et al. 1997; Buracas et al. 1998; Kara et al. 2000). Figure 1 Variability in the Responses of a Simple Cell (A) Firing rate in response to a cycle of an optimal drifting grating. Three trials are shown. (B) Firing rate averaged over seven trials. Shaded area indicates 2 s.d. (C) Same, for three other stimuli: a grating drifting in the orthogonal direction (top), a grating drifting in the opposite direction (middle), and a blank stimulus (bottom). (D) Membrane potential trace measured for the first cycle. Dashed line is resting potential Vrest. Dotted line is firing threshold Vthresh (from [H]). (E–G) As in (A–C), for coarse potential. (H) Relation between firing rate and coarse potential. Curve is fit of rectification equation. (I–K) As in (A–C), for predictions of rectification model. Figure 2 Relation between Response Variance and Mean for Three Cells (A) Variance versus mean for firing rate of the simple cell in Figure 1 measured with 13 stimuli (the four in Figure 1 plus nine additional orientations). Line is linear regression. Diagonal line is prediction for a Poisson process. (B) Variance versus mean for coarse potential. Error bars are 2 s.d. Curve is linear fit to standard deviation versus mean. Dashed line is resting potential Vrest. Dotted line is firing threshold Vthresh. (C) Variance versus mean for firing rate predicted by the rectification model. Details as in (A). (D–F) As in (A–C) for a complex cell. (G–I) As in (A–C) for a third neuron, whose behavior is intermediate between those of simple cells and complex cells. Because the production of firing rates within a neuron introduces remarkably little noise (Calvin and Stevens 1968; Mainen and Sejnowski 1995; Carandini et al. 1996), trial-to-trial variability is thought to arise from the membrane potential fluctuations that result from summated synaptic input (Calvin and Stevens 1968; Stevens and Zador 1998). I have tested this hypothesis by considering membrane potential responses recorded intracellularly in vivo. Results From traces of membrane potential obtained at high temporal resolution (Figure 1D), I obtained an estimate of overall synaptic drive by removing the action potentials and low-pass filtering the resulting traces (Carandini and Ferster 2000; Volgushev et al. 2000). The outcome of this procedure (Figure 1E) is a coarse potential (or “generator potential”; Lankheet et al. 1989) that approximates the synaptic current (Anderson et al. 2000a). This technique allows one to estimate synaptic currents while concurrently recording firing rates. Variability of Coarse Potential during Visual Stimulation We can now consider the mean and variance across trials for coarse potential. The mean, Vmean, is the “signal” reflecting the stimulus-driven synaptic input to the neuron (Figure 1F and 1G, traces). The variance, instead, is the “noise” reflecting the synaptic input's trial-to-trial variability (Figure 1F and 1G, shaded areas). The variability of potential depended only slightly on stimulus strength. Variance was slightly higher when the stimuli depolarized the cell than when they hyperpolarized it (Figure 1F and 1G). For the example simple cell in Figure 1, standard deviation of potential was 2.8 ± 1.2 mV (s.d.) for Vmean between –70 and –65 mV, and 4.0 ± 1.7 mV for Vmean between –55 and –50 mV. The relation between standard deviation of potential and Vmean can be described by a regression line (r = 0.27 ± 0.04, s.d., bootstrap) whose slope is 0.08 ± 0.01 and whose intercept at Vrest = −60.4 mV is 3.3 ± 0.1 mV. Similar values were obtained in the rest of the population (e.g., Figure 2E and 2H): correlation coefficient was r = 0.40 ± 0.19 (s.d., N = 22), intercept at Vrest was 3.3 ± 1.4 mV, and mean slope was a shallow 0.14 ± 0.09. In occasional cells (such as that of Figure 2H), the standard deviation of potential did not grow monotonically with Vmean. The ratios of variance to mean seen in membrane potentials were negligible when compared to those seen in firing rate. For the example simple cell, over the entire range of mean potentials the variance of potential grew by less than a factor of four (Figure 2B). By contrast, over the entire range of firing rates the variance of firing rate grew by a factor of almost 100 (Figure 2A). Similar results were obtained in the remaining cells, such as the complex cell of Figure 2D and 2E and the intermediate cell of Figure 2G and 2H. In the last cell, the difference between potential and firing rate was particularly striking, as the former shows a downward slope that is clearly absent in the latter. These differences in variability are meaningful because potential and firing rate were recorded from the same responses to the same set of stimuli. They are not simply due to differences in time scale (Buracas et al. 1998; Kara et al. 2000) because firing rate and potential were sampled at the same resolution (100 Hz). Accounting for the Variability of Firing Rate The origin of the large variability in firing rate lies not in an unforeseen source of noise, but rather in a deterministic mechanism, the nonlinear transformation of potentials into firing rates. This transformation (Figure 1H) can be fitted by a simple rectification model (Granit et al. 1963) describing how firing rate R grows with potential V once this potential is above a threshold Vthresh. As expected (Anderson et al. 2000b; Carandini and Ferster 2000), this rectification model captures the relation between potential and firing rate (Figure 1H, curve) and can be used to predict the rough features of firing rate both in individual trials (compare Figure 1A and 1I) and in averages across trials (compare curves in Figure 1B and 1C with those in Figure 1J and 1K). Of course, rectification is not a full account of the transformation between synaptic inputs and firing rates. Indeed, the relationship between firing rate and potential exhibits substantial error bars (Figure 1H). These error bars do not denote noise involved in generating spikes, which is negligible (Calvin and Stevens 1968; Mainen and Sejnowski 1995; Carandini et al. 1996). They simply indicate that (as evident in the Hodgkin–Huxley equations) instantaneous potential is only one of the determinants of firing rate; additional determinants include the membrane potential's recent history (Azouz and Gray 1999) and frequency content (Carandini et al. 1996; Volgushev et al. 2002). Despite its simplicity, the rectification model is sufficient to predict the large variability of firing rate, and the increase of firing-rate variance with firing-rate mean. The predicted standard deviation resembles the measured one both in amplitude and in time course (compare shaded areas in Figure 1B and 1C with those in Figure 1J and 1K). Indeed, a plot of variance versus mean for the predicted firing rate (Figure 2C) indicates almost as much variability as that seen for the actual firing rate (Figure 2A). Similar results were obtained in the other example cells (compare Figure 2D to 2F, and 2G to 2I) and in the rest of the population (Figure 3A and 3B). While the rectification model often underestimated the vertical intercept of the line relating mean and variance (Figure 3A), it generally captured the line's slope (Figure 3B). The model, therefore, accounts for the growth of firing-rate variance with the mean. Figure 3 Performance of the Rectification and Gaussian–Rectification Models in Predicting Firing-Rate Variability Distributions of firing-rate variance versus firing-rate mean were fitted with a line in logarithmic scale, corresponding to the equation variance = a meanb, where a is the intercept of the line and b is the slope of the line. Fitting was performed on the measured distributions (e.g., Figure 2A), on the distributions predicted by the rectification model (e.g., Figure 2C), and on those predicted by the Gaussian–rectification model (e.g., Figure 6B). Dashed lines indicate predictions for a Poisson process. (A) Comparison of measured intercept versus predicted intercept. Diagonal line indicates equality between measured and predicted values. (B) Same, for the slope. (C and D) Same as in (A) and (B), for the predictions of the Gaussian–rectification model. The reason why the rectification model explains the large variability of firing rate is rather intuitive. Trial-to-trial fluctuations in potential are critical to obtain spikes, because many visual stimuli (such as the 210° grating in Figure 1) elicit a mean potential that barely reaches the firing threshold (Anderson et al. 2000b). Therefore, small fluctuations in membrane potential make the difference between a trial with few or no spikes and one with plenty of spikes. In other words, the firing threshold amplifies small fluctuations in potential into large fluctuations in firing rate. Perhaps less intuitive is the reason why the rectification model explains the growth of firing-rate variance with firing-rate mean. One may think that a necessary condition for this effect is the growth in potential variance observed with increasing mean potential (Figure 2B). This is not the case: The variance of potential could stay constant or even decrease (as it does for the cell in Figure 2H), and the variance of firing rate would still grow with the mean (Figure 2G). Predicting the Variability of Firing Rate An intuition and a quantitative account for these properties can be obtained by applying the rectification model to an idealized random distribution of potentials, which we take to be Gaussian. Such a Gaussian–rectification model has been used to explain the dependence of mean firing rate on mean synaptic input (Anderson et al. 2000b; Hansel and van Vreeswijk 2002; Miller and Troyer 2002). It resembles a model proposed by Abeles (1982, 1991) to study neuronal integration time. In the Gaussian–rectification model, the stimulus determines the mean of the Gaussian (Figure 4B), and the portion of Gaussian that crosses threshold determines the distribution of firing rates (Figure 4A). The mean of the Gaussian is the average potential Vmean evoked by the stimulus at that instant (Figure 4B). The rectification function (Figure 1H) operates on this distribution and determines the distribution of firing rates (Figure 4A): Each potential contributes a firing rate given by the rectification function, with a probability given by the value of the Gaussian at that potential. When mean potential Vmean is low, the Gaussian lies mostly below the threshold Vthresh, so the predicted firing rate is mostly zero (Figure 4A, a). When Vmean is higher, however, the tail of the Gaussian that lies above threshold becomes substantially larger, and the distribution of firing rates reaches higher rates (Figure 4A, e). The large peak at 0 spikes/s corresponds to the area of the Gaussian that lies below Vthresh. Figure 4 The Gaussian–Rectification Model (A and B) Distributions across trials of model potential V (B) and of model firing rate R (A) for five values of the mean potential Vmean. Firing rate is obtained from potential by applying the rectification model (Figure 1H). The value for R = 0 is shown at 1/3 of veridical height. (C and D) Mean (data points) and standard deviation (error bars) for the distributions in (A) and (B) as a function of mean potential Vmean. Curve and shaded area indicate model predictions for the full range of mean potentials. Arrows indicate the five mean potentials (± 2 mV) used in (A) and (B). Throughout, dashed lines indicate resting potential Vrest and dotted lines indicate firing threshold Vthresh. Such a simple model is sufficient to predict that the variance of firing rate should increase with mean firing rate. As mean potential Vmean increases, the distribution of firing rate becomes broader (Figure 4A), increasing not only in mean but also in standard deviation (Figure 4C). This phenomenon occurs even though in the model the standard deviation of potential is the same at all mean potentials (Figure 4D). The main assumption of the model, that of a Gaussian distribution of potentials, is generally borne out by the data. In most cells, the distribution of potential is close to a Gaussian, especially at the lowest values of mean potential, where spiking seldom occurs (Figure 5B). For the example simple cell, the distribution of z-scores (the difference between potential and mean potential, normalized by the standard deviation at that potential) appears remarkably Gaussian (Figure 6A). Similar results were obtained in the other cells (e.g., Figure 6C and 6E), although in some cells the tails of the distributions exceeded those of a Gaussian, and a large skewness clearly favored the more depolarized tails (not shown). A Gaussian distribution of potentials is commonly predicted in the theoretical literature (e.g., Svirskis and Rinzel 2000; Amemori and Ishii 2001; Rudolph and Destexhe 2003). It would be expected in a passive membrane summating many independent, high-rate presynaptic spike trains (Rice 1944; Tuckwell 1988). Figure 5 Application of the Gaussian–Rectification Model to the Data from the Example Simple Cell (A and B) Distributions across trials of potential V (B) and of firing rate R (A) for five values of the mean potential Vmean. Curves are best-fitting Gaussians (B) and predicted distributions of firing rate (A). Bin for R = 0 is shown at 1/3 of veridical height (and is three times wider than the others so that area is veridical). (C and D) Mean (data points) and standard deviation (error bars) for the distributions in (A) and (B), as a function of mean potential Vmean. Curve and shaded area indicate model predictions for the full range of mean potentials. Arrows indicate the five mean potentials (± 2 mV) used in (A) and (B). Even a reduced model with constant standard deviation of potential (D, shaded area) predicts a growing standard deviation (A, shaded area). Figure 6 Variability of Potential and Predictions of the Gaussian–Rectification Model for Three Cells (A) Distribution of normalized deviations from the mean (z-scores) for the potential of the simple cell in Figure 1 and Figure 2A–2C. These were computed by subtracting from each potential the corresponding mean potential Vmean (the abscissa in Figure 2B) and dividing by the standard deviation (the square root of the ordinate in Figure 2B). The results were cumulated. The curve is a normal Gaussian. (B) Variance versus mean for firing rate for the same cell and its prediction by the Gaussian–rectification model. Data points are same as Figure 2A. Red curve: prediction of Gaussian–rectification model Shaded area: region where the Gaussian–rectification model predicts the occurrence of 75% of the points. Line is linear regression. (C and D) Same as (A) and (B) for the complex cell in Figure 2D–2F. (E and F) Same, for the intermediate cell in Figure 2G–2I. The Gaussian–rectification model has four parameters. Three of these parameters describe the rectification stage and are thus fully constrained by the measured relationship between potential and firing rate (Figure 1H). The remaining parameter, the standard deviation of the Gaussian, σ, was obtained from maximum likelihood estimation, i.e., by searching for the standard deviation that maximized the probability of observing the distributions of firing rate (Figure 5A). The result, σ = 4.6 mV, slightly overestimates the standard deviation observed for low mean potentials, but correctly estimates it at higher mean potentials (Figure 5D, compare shaded area to error bars). The model predicts the main features of the distributions of firing rate (Figure 5A). It predicts that when mean potential is low (e.g., Vmean = −64 mV; Figure 5A, a), the firing rate is always zero, whereas larger mean potentials yield a distribution of firing rates that spans values from 0 to 300 spikes/s (e.g., Vmean = −54 mV; Figure 5A, d). Deviations from the predictions are largest where they are least significant, i.e., at high firing rates for the high values of Vmean (e.g., Vmean = −50 mV; Figure 5A, e). These high values were achieved seldom; for example, only 21 data points were obtained at Vmean = −50 mV (Figure 5A, e), compared to 273 at Vmean = −54 mV (Figure 5A, d) and 1,575 at Vmean = −64 mV (Figure 5A, a). In fact, the model closely predicts both the firing rate's mean and standard deviation (Figure 5C). It predicts the two key effects of increasing mean potential: (1) an increase in the firing rate's mean (as a power law; Anderson et al. 2000b; Hansel and van Vreeswijk 2002; Miller and Troyer 2002), and (2) an increase in the firing rate's standard deviation. Crucially, the model closely predicts how firing-rate variance depends on firing-rate mean (Figure 6B, red curve). Because of noise in the estimation of variance from a limited number of measurements (in this experiment, seven trials), the data are not expected to fall exactly on the model's prediction; Monte Carlo simulations with a matched number of trials determined the area in which 75% of the observations are predicted to fall (Figure 6B, gray area). Similar results were obtained in the remaining cells of the population, except that the model has a mild tendency to underestimate the intercept and overestimate the slope of the relation between variance and mean (Figure 3C and 3D). Overall, the Gaussian–rectification model applied to the trace of mean potential performed as well as the rectification model applied to the individual traces of potential. Both models underestimated the intercept of the lines fitted to the relationship between firing-rate variance and mean: the rectification model by 25 ± 42% (Figure 3A), and the Gaussian–rectification model by 44 ± 26% (Figure 3B). Both models correctly estimated the slope of the line (the growth in variance with increasing mean), with insignificant errors of 0.10 ± 0.25 for the rectification model (Figure 3C), and −0.01 ± 0.22 for the Gaussian–rectification model (Figure 3D). This performance is remarkable, given that the Gaussian–rectification model replaces detailed knowledge of potential in individual trials with just one free parameter, the standard deviation σ of potential. These results illustrate how the key element in producing the steep growth in firing-rate variance observed with growing stimulus strength is the nonlinear transformation between potential and firing rate (Figure 1H). Indeed, the model was intentionally implemented with the constraint that the standard deviation of potential, σ, be constant. This constraint serves to demonstrate that a mild growth in variance of potential (Figure 5D, error bars) is not necessary to produce the steep growth in firing-rate variance (Figure 5C, error bars). Variability of Responses to Current Injection The predictions of the Gaussian–rectification model apply to any neuron that meets minimal criteria: a relationship between synaptic input and firing rate that is monotonic and includes a threshold, and noise in the input that has a Gaussian distribution. As an example, let us consider a neuron that is closer to biological reality than the Gaussian–rectification model, one that receives currents (not potentials) in its input and produces individual spikes (not continuous firing rates). In particular, consider an enhanced integrate-and-fire neuron, where each spike is accompanied by a temporary increase in spike threshold and by the entry of calcium, which in turn determines an after-hyperpolarization potassium current (see Materials and Methods). To ensure realism, I fitted the model parameters to responses to injected currents of a regular spiking neuron. This neuron was recorded in vitro in the visual cortex of the guinea pig, in the near absence of synaptic inputs (Carandini et al. 1996). The injected currents include sinusoids (Figure 7A, top four panels) and approximately Gaussian-distributed noise (Figure 7A, bottom panels). Once its parameters are appropriately tailored, the enhanced integrate-and-fire model accurately predicts the cell's responses, both in the subthreshold membrane potential waveforms and in the timing of individual spikes (Figure 7B and 7C). Figure 7 Responses of a Regular-Spiking Neuron in the Visual Cortex to Current Injection, and Predictions by an Enhanced Integrate-and-Fire Model Neuron (A) Injected currents were sinusoids or noise waveforms. Noise was obtained by summing eight sinusoids with incommensurate frequencies. (B) Membrane potential responses of a regular-spiking neuron (cell 19s2, experiment 4) recorded with sharp electrodes in a study of guinea pig visual cortex in vitro (Carandini et al. 1996). (C) Predictions of an enhanced integrate-and-fire neuron model fine-tuned to resemble the responses of the cell. Just as predicted, this spiking neuron responds to noisy injected currents with a firing rate whose variance grows with the mean (Figure 8). To simulate the synaptic drive to a simple cell recorded in vivo (Figure 1A–1D) I injected sinusoidal currents, to which I added Gaussian noise. The model responses (Figure 8A–8D) resemble those seen in vivo (Figure 1A–1D). The firing rate is highly variable (Figure 8B), with a standard deviation that is roughly comparable to the mean (Figure 8C and 8D), even though the standard deviation of the injected current is constant (Figure 8H and 8I). In fact, for firing rate the variance grows proportionally to the mean (Figure 8E), even though for injected current the variance is constant (Figure 8J). Figure 8 Variability in the Responses of the Spiking Model Neuron (A) Response of the model neuron to a 0.6-nA sinusoidal current in the presence of Gaussian noise (s.d. 0.25 nA). (B) Corresponding firing rate. Three trials are shown. (C) Firing rate averaged over 16 trials. Shaded area indicates 2 s.d. (D) Same, for three other stimuli: a 0.4-nA sinusoid (top), a 0.2-nA sinusoid (middle), and noise alone (bottom). (E) Variance versus mean for firing rate. Diagonal line is prediction for a Poisson process. Red curve: prediction of Gaussian–rectification model, with no parameters allowed to vary to fit the data. Shaded area: region where the Gaussian–rectification model predicts the occurrence of 75% of the points. (F) Relation between firing rate and injected current. Curve is fit of rectification equation. (G–I) As in (B–D), for injected current. (J) Variance versus mean for injected current. The Gaussian–rectification model captures the essence of this behavior. Once it is given the standard deviation of the noise and the relationship between injected current and firing rate (Figure 8F), the Gaussian–rectification model makes a parameter-free prediction of the relationship between variance and mean (Figure 8E, curve). This prediction is not perfect (it consistently underestimates firing-rate variance), but it does capture the most important behavior: that variance grows with the mean for firing rate (Figure 8E, curve) but not for injected current (Figure 8J, horizontal line). Similar results were obtained when the stimulus parameters were changed to simulate synaptic inputs to a complex cell, or when the parameters of the spiking neuron were changed to simulate other cells measured in vitro, or even chosen randomly within reasonable bounds. As predicted, as long as the relationship between synaptic input and firing rate involved a threshold and the input noise was Gaussian, the variance grew with the mean for firing rate but not for injected current. Role of Firing-Rate Encoder Having validated the Gaussian–rectification model, we can now investigate the role of its parameters in determining the curves relating firing-rate variance and mean (Figure 9). The model has four parameters (see Materials and Methods): (1) the standard deviation σ of potential, (2) the firing threshold, Vthresh, (3) the gain k of the relationship between firing rate and potential above threshold, and (4) the exponent n of this relationship. For the purpose of studying the model, we can assume, without loss of generality, that potential is unitless and has standard deviation σ = 1. Then, because Vthresh can only determine the range of firing rates that is achieved, only k and n control the shape of the variance versus mean curves (Figure 9). Figure 9 Role of Parameters of Gaussian–Rectification Model The standard deviation of potential was set to σ = 1, so that the shape of the curves relating firing-rate variance to firing-rate mean depends entirely on the gain k and the exponent n of the curves relating firing rate to membrane potential. The effects of these two parameters are explored: varying n (columns) and varying k (rows). Red curves: predictions of the Gaussian–rectification model; shaded areas: regions where the model predicts the occurrence of 75% of the points. Insets illustrate the corresponding curves relating firing rate to membrane potential. The gain k controls curve position, and the exponent n controls curve shape (Figure 9). Increasing the gain k lifts the curves upward by twice as much as it shifts them rightward (Figure 9, rows). These shifts occur because variance grows with k 2 and mean grows with k. Decreasing the exponent n causes the curves to saturate (Figure 9, columns): The variance saturates to a plateau if n = 1 (Figure 9, middle), and it reaches a maximal value and then decreases if n < 1 (as in Figure 9, left). Saturation occurs because when potential goes well above threshold, increases in mean potential cease to reveal ever larger portions of the Gaussian. If the curves relating firing rate to potential saturate (n < 1), variations in potential are compressed into proportionally ever smaller variations in firing rate; the opposite occurs if the curves expand (n > 1). This analysis predicts that it should be fairly common for the firing-rate variance to saturate at high firing rates, possibly showing a plateau or even a decrease. Indeed, in the sample of V1 neurons recorded intracellularly, exponents are typically close to unity (n = 1.1 ± 0.6). Accordingly, a mild form of saturation is common in the plots of firing-rate variance and mean (Figure 6B). To quantify the saturation, however, one needs reliable estimates of firing-rate variance. These estimates are not very reliable in the intracellular sample, which typically involves only a few hundred spikes per cell, leading to large clouds of points in the scatters of variance versus mean (Figure 6B). Variability of Extracellularly Recorded Firing Rates To test the model's prediction rigorously, I considered a set of V1 responses obtained with extracellular recordings. Thanks to the large number of spikes (commonly >4,000 per cell), measurements in this dataset yield more precise estimates of firing-rate variance over a wider range of firing rates than are available in the intracellular sample. An analysis of firing-rate variance versus mean for these extracellularly recorded cells supports the predictions of the model (Figure 10). Extracellular data do not afford independent estimates of gain k and exponent n of the transformation of potential into firing rate. I thus first computed the model predictions for a variety of combinations of k and n (such as those shown in Figure 9). I then made Bayesian estimations of the values of k and n that maximize the likelihood of the data, while imposing a broad prior for n = 1.1, the median value measured intracellularly. The quality of these two-parameter fits was excellent (Figure 10), of higher quality than could be obtained by fitting a line, the two-parameter “model” commonly used to describe data of this kind (Figure 2A). Moreover, a number of cells exhibited the saturation in variance predicted by the model. The eight representative cells shown in Figure 10 are arranged in order of increasing exponent n. The first three (n = 0.9 to 1.0) show evident saturation in firing-rate variance as mean firing rate increases. The remaining five show a milder saturation, as expected from their higher exponents (n = 1.1 to 1.2). Saturation was common, as the median n was 1.06, with n < 1 in 13/37 cells. Yet to my knowledge, except for an anecdotal account (Mechler 1997), this common property had not been previously reported. It constitutes further support for the usefulness of the Gaussian–rectification model. Figure 10 Relationship between Variance and Mean for Eight Cells Recorded Extracellularly in Cat V1, and Fits by the Gaussian–Rectification Model For each mean firing rate, data point and error bars indicate mean ± 1 s.d. of the observed variance. Red curves and shaded areas are predictions of the model. Values of exponent n and gain k are reported next to each graph. Cells are arranged in order of increasing exponent n. Discussion We have seen that a large amplification takes place between the trial-to-trial variability of synaptic input and that of firing rate: The variance of synaptic input is small compared to the dynamic range, and it is roughly constant. The amplification of variability arises from the threshold in the transformation of synaptic input into firing rate. A Gaussian–rectification model attributes this amplification to very simple causes: approximately constant Gaussian noise in the input, and rectification due to threshold in the output. It indicates that firing-rate variance would grow with the mean even if the variance of synaptic input were constant. Both of the assumptions of the model, constant Gaussian noise and rectification, are borne out by the data. These assumptions are rather minimal, so they are naturally satisfied by more realistic models. For example, a realistic integrate-and-fire model behaves as predicted: Once it is given constant Gaussian noise in the input, it produces a firing-rate variance that grows with the firing-rate mean. Further support for the Gaussian–rectification model comes from its novel, and correct, prediction that firing-rate variance should saturate at high firing rates. In confirming this prediction I showed that the model can be used to account for variability in firing rate without knowledge of cellular properties. The extension to extracellular data is important because extracellular methods constitute the norm in visual neurophysiology, especially in awake animals, and are the ones used in previous studies of firing-rate variability. These results further lengthen a list of properties of V1 neurons that are simply explained by the firing threshold. In addition to the amplification of trial-to-trial variability demonstrated here, these include the sharpening of tuning for stimulus direction and orientation (Jagadeesh et al. 1993; Carandini and Ferster 2000; Volgushev et al. 2000), the power-law behavior of firing rate at low contrast (Heeger 1992; Anderson et al. 2000b; Hansel and van Vreeswijk 2002; Miller and Troyer 2002), and even the establishment of the dichotomy between simple and complex cells (Carandini and Ferster 2000; Mechler and Ringach 2002; Priebe et al. 2004). It is remarkable that a mechanism as simple as the firing threshold can determine phenomena that might prima facie require more complex explanations at the level of the network. Limitations of the Approach One limitation of this study lies in the use of coarse potential. Coarse potential is not completely independent of firing rate: Even when spikes are removed and the traces smoothed, there is still a likely contribution of active conductances that has not been removed. Fortunately, this limitation strengthens my observation that coarse potential is not nearly as variable as firing rate: Any unwanted remaining echo of the spikes would make coarse potential more similar to firing rate and, thus, more variable. Therefore, in reality the variance of the actual synaptic input might be even less dependent on the mean than appears, for example, in Figure 2B, 2E, and 2H. A partial control for these effects would be to perform some of the measurements while blocking spikes. However, blocking spikes would prevent the key measurements of this study, which require concurrent measurement of firing rate and estimation of synaptic input. Another limitation of the approach is that I have mostly considered firing rates, not individual spikes. Unlike firing rates, individual spikes can occur only in integer numbers and are separated by refractory periods. These properties can become relevant to response variability, for example, if firing rates become so high that refractory period becomes a limiting factor (Kara et al. 2000). Such concerns are assuaged by the realistic integrate-and-fire model (Figure 7), which shows an increase of firing-rate variance with the mean similar to that predicted by the Gaussian–rectification model. As to the saturation in firing-rate variance that was observed in some neurons, it invariably occurred at firing rates much lower than predicted from the refractory period. A more serious limitation of coarse potentials and firing rates is that they make sense only in a limited range of time windows. The windows should be long enough to be able to contain more than one spike, and short enough that mean potential is approximately constant within the window. An informal analysis of the effect of time window indicates that a range of 5–20 ms is satisfactory. This range, however, might be appropriate only for V1 neurons; further investigations are required before applying these methods elsewhere. Finally, a broader limitation of this work is that it concentrates on variability across trials, with little bearing on another form of variability, the one observed within trials in the irregularity of spike trains (Softky and Koch 1993; de Ruyter van Steveninck et al. 1997; Reich et al. 1997; Troyer and Miller 1997; Buracas et al. 1998; Shadlen and Newsome 1998; Stevens and Zador 1998). Thanks to recent advances, however, the cellular origins of this form of variability have been largely explained (Reich et al. 1997; Stevens and Zador 1998). In particular, it is now clear that high variability within trials is to be expected if neurons receive synaptic inputs with slow temporal correlation (Svirskis and Rinzel 2000). In fact, variability within trials is most evident with visual stimuli that provide a roughly stationary response, being greatly diminished with richer stimuli, which elicit highly precise responses (Bair and Koch 1996; Reich et al. 1997; Buracas et al. 1998). Conversely, trial-to-trial variability is endemic, being present regardless of type of visual stimulus (Reich et al. 1997; Buracas et al. 1998). Implications for Cortical Processing What computational advantage might cortical neurons derive by amplifying the variability that they receive in their input? Why reduce the signal/noise ratio? To answer these questions, it might help to clarify the sources of “signal” and “noise.” The main source of variability in synaptic inputs to a V1 neuron is likely to be intracortical because thalamic responses are half as variable (Kara et al. 2000). Variability thus results largely from ongoing cortical activity (Arieli et al. 1996; Buracas et al. 1998; Tsodyks et al. 1999; Kenet et al. 2003). It appears to us as noise simply because it is not synchronized with stimulus onset. By contrast, the mean across trials of potential or firing rate constitutes a signal that is driven entirely by the stimulus. The results of this study suggest that threshold affects the interaction between stimulus-driven activity and ongoing activity, turning it from additive to multiplicative. At the level of firing rates, this interaction is largely multiplicative because the variance of firing rate grows proportionally to the stimulus-driven mean firing rate. At the level of synaptic inputs, instead, this interaction is nearly additive because the variance of potential barely depends on the stimulus-driven mean potential. Indeed, additivity has been seen between local field potentials and ongoing voltage-sensitive dye signals (Arieli et al. 1996). We have seen that the rectification due to firing threshold is single-handedly responsible for the variability of firing rate and is, thus, responsible for turning a largely additive interaction into a multiplicative interaction. It is thus conceivable that the computational role of firing threshold is to multiply stimulus-driven responses by ongoing cortical activity, i.e., to multiply what we call “signal” by what we call “noise.” What may appear as lowering the signal/noise ratio can in fact be seen as a useful process, one that progressively amplifies the ongoing activity that ultimately guides our actions. Materials and Methods Data acquisition in vivo Measurements in vivo were obtained in paralyzed, anesthetized cats. Methods for animal preparation and maintenance have appeared elsewhere (Carandini and Ferster 2000) and were approved by the Animal Care and Use Committees at Northwestern University and at the Smith-Kettlewell Eye Research Institute. The 22 cells recorded intracellularly belong to a sample that has been analyzed in two previous studies by Carandini and Ferster (2000) and by Anderson et al. (2000a). These studies describe in detail the recording methods, which involved the whole-cell patch technique. The electrical noise associated with this technique is commonly <0.1 mV (as judged from records obtained after losing the patch). From the sample I excluded a few cells that produced less than ten spikes per block of stimuli, or that failed to satisfy other minimal requirements (firing rate >2 spikes/s, spike height >10 mV). Stimuli were optimal gratings drifting in 12 directions in 30° intervals, and a blank screen of uniform gray. The resting potential Vrest was taken as the mean potential measured with the blank screen. Coarse potential traces were obtained from traces of membrane potential sampled at 4 kHz by removing spikes (Lankheet et al. 1989) and by applying a low-pass filter with a cutoff of 50 Hz (Carandini and Ferster 2000; Volgushev et al. 2000). The same low-pass filter was applied to spike trains sampled at 4 kHz to yield firing rate. Both coarse potential and firing rate were subsampled at 100 Hz. The 37 neurons recorded extracellularly are part of a study of the organization of receptive fields and suppressive surrounds in area V1 (Bonin et al. 2003). This dataset was chosen because it involved lengthy experiments that yielded many thousands of spikes per cell at a variety of firing rates. Recordings were made with quartz-coated platinum/tungsten microelectrodes; methods for data acquisition and animal maintenance have been described by Freeman et al. (2002). Stimuli were drifting gratings presented at the optimal orientation, spatial frequency, and temporal frequency, and enclosed in one of 66 possible windows. The windows were stationary square gratings with variable period and orientation. Stimuli typically lasted 2 s, and each block of stimuli was typically repeated three to six times. Firing rates were extracted from the spike train by low-pass filtering at 50 Hz and were subsampled at 100 Hz. Data acquisition in vitro Measurements in vitro were made with sharp intracellular electrodes from slices of guinea pig visual cortex. Methods for this preparation were approved by the Animal Care and Use Committee at New York University. The cells are part of the dataset presented by Carandini et al. (1996); the cell in Figure 7 is the one whose responses are extensively illustrated in that study (cell 19s2). Rectification model The relation between potential V and firing rate R (e.g., Figure 1H) was fitted with an extension of the rectification model (Mechler and Ringach 2002), where R(V) = k[V−Vthresh]n+ , with [.]+ indicating rectification, k a proportionality factor, and n an exponent. Fitted parameters were Vthresh = −55.3 mV, k = 16.7, and n = 1.2 for the simple cell in Figure 1, and Vthresh = −46.6 ± 10.5 mV, k = 12.4 ± 7.9, and n = 1.1 ± 0.6 for the whole intracellular population (N = 22). The distance between Vthresh and Vrest was 5.1 mV for the simple cell in Figure 1, and 8.0 ± 4.2 mV for the population. Gaussian–rectification model The mean potential V mean in response to a stimulus was defined as the mean across trials of coarse potential. In the Gaussian–rectification model, the probability of observing a firing rate r (Figure 4A) given a mean potential Vmean is where R(V) is the relation between firing rate and potential V (Figure 1H), and N[Vmean, σ] is the probability distribution of potential (Figure 5B), a Gaussian with mean Vmean and standard deviation σ. The value of p(r) depends on whether r is zero or positive: for r > 0, and for r = 0. The first expression is simply the value of the Gaussian for V = R−1(r). The second expression is the area of the portion of Gaussian that is below threshold (erf is the error function). These expressions allow maximum likelihood estimation of model parameters from measured firing rates. When parameters of the relation between firing rate and potential R(V) are obtained independently (in intracellular recordings; Figure 1H), the only free parameter was the standard deviation σ of potential. Across the intracellular population, the average value of σ obtained by the fits was 5.4 ± 2.0 mV (s.d., N = 22). The required σ was always larger (by 2.1 ± 1.5 mV) than the standard deviations observed when Vmean = Vrest, but it was comparable (larger by only 0.9 ± 1.6 mV) to the standard deviations observed when Vmean = Vthresh. Statistics Let V mean(t) be the mean potential at time t from stimulus onset. Because the sample rate is 100 Hz, each time sample corresponds to a 10-ms interval. Of course, Vmean(t) depends on the stimulus. To simplify the notation, however, consider the case of a single stimulus. Distributions for potential at a given mean potential (Figure 5B) were computed as follows: (1) Select a value of interest, v (e.g., v = −55 mV; Figure 5B, a); (2) find the times (tk) when the mean potential Vmean(tk) is within 2 mV of v; (3) pooling across trials j, look at the distribution of potential [Vj(tk)] (e.g., Figure 5B, a). Distributions for z-scores (normalized deviations from the mean) of potential (Figure 6A, 6C, and 6E) were computed as follows: (1) Divide the range of values of Vmean in 1-mV intervals, with centers (vi); (2) for each interval i, find the set of times (tik) when the mean potential is in the i-th bin; (3) pooling across trials j, compute σi, the standard deviation of Vj(tik); (4) transform each Vj(tik) into a z-score: zijk= [Vj(tik) − vi]/σi; (5) look at the distribution of (zijk) (e.g., Figure 6A). Enhanced integrate-and-fire model The enhanced integrate-and-fire model was derived in collaboration with Davide Boino (2000) by simplifying a model by Wang (1998). The model neuron has a single compartment with membrane equation where the currents are: with tspike the time of the last spike. Ca(t) is the (unitless) calcium concentration: where the sum extends over all spikes with tspike < t. Spikes result from stereotyped conductances gNa(t) and gK(t) derived from Hodgkin–Huxley equations and are scaled to approximate the spikes from the recorded neuron. They occur when Vm exceeds a threshold, which depends on the time since the last spike: The reversal potentials for sodium and potassium were set to Vk = −80 mV and VNa = 55 mV. Passive parameters of the membrane (Cm = 120 pF, gleak = 12.4 nS, Vleak = −60.3 mV) were obtained by fitting the membrane potential responses to sinusoids. The remaining parameters (gAHP = 23.0 nS, Ca50 = 10, τCa = 200 ms, Vthresh = −43.5 mV, τthresh = 36 ms) were obtained by a search algorithm aimed at maximizing the quality of the predictions for firing rate. Thanks to Jeffrey Anderson and David Ferster for participating in intracellular experiments (supported by National Eye Institute grant NEI-EY04726 to David Ferster), to Vincent Bonin and Valerio Mante for participating in extracellular experiments, and to Davide Boino for help with the integrate-and-fire model (supported by the Swiss National Science Foundation). This work has benefited from comments by Michael Shadlen, Massimo Scanziani, Moshe Gur, Nicholas Priebe, and David Ferster, by the members of my laboratory, and by attendees of a meeting of the Sloan-Swartz Centers for Theoretical Neurobiology (La Jolla, California, July 2003), whom I thank collectively. Supported by the James S. McDonnell Foundation 21st Century Research Award in Bridging Brain, Mind and Behavior. Conflicts of interest. The author has declared that no conflicts of interest exist. Author contributions. MC participated in the experiments, analyzed the data, and wrote the paper. Academic Editor: Charles Stevens, Salk Institute for Biological Studies Citation: Carandini M (2004) Amplification of trial-to-trial response variability by neurons in visual cortex. PLoS Biol 2(9): e264. Abbreviation V1primary visual cortex ==== Refs References Abeles M Role of the cortical neuron: Integrator or coincidence detector? Isr J Med Sci 1982 18 83 92 6279540 Abeles M Corticonics: Neural circuits of the cerebral cortex 1991 Cambridge, UK Cambridge University Press 280 p Amemori KI Ishii S Gaussian process approach to spiking neurons for inhomogeneous Poisson inputs Neural Comput 2001 13 2763 2797 11705410 Anderson J Carandini M Ferster D Orientation tuning of input conductance, excitation and inhibition in cat primary visual cortex J Neurophysiol 2000a 84 909 931 10938316 Anderson JS Lampl I Gillespie DC Ferster D The contribution of noise to contrast invariance of orientation tuning in cat visual cortex Science 2000b 290 1968 1972 11110664 Arieli A Sterkin A Grinvald A Aertsen A Dynamics of ongoing activity: Explanation of the large variability in evoked cortical responses Science 1996 273 1868 1871 8791593 Azouz R Gray CM Cellular mechanisms contributing to response variability of cortical neurons in vivo J Neurosci 1999 19 2209 2223 10066274 Bair W Koch C Temporal precision of spike trains in extrastriate cortex of the behaving macaque monkey Neural Comput 1996 8 1185 1202 8768391 Boino D Modello delle risposte dei neuroni corticali in vitro [Laurea (thesis)] 2000 Turin (Italy) University of Turin 97 Bonin V Mante V Carandini M Predicting signal and noise in LGN and V1. Program No. 229.5. In: Society for Neuroscience 2003 abstract viewer. Available: http://sfn.scholarone.com/itin2003/ via the Internet 2003 Accessed 19 July 2004 Bradley A Scottun BC Ohzawa I Sclar G Freeman RD Visual orientation and spatial frequency discrimination: A comparison of single cells and behavior J Neurophysiol 1987 57 755 772 3559700 Buracas GT Zador AM DeWeese MR Albright TD Efficient discrimination of temporal patterns by motion-sensitive neurons in primate visual cortex Neuron 1998 20 959 969 9620700 Calvin WH Stevens CF Synaptic noise and other sources of randomness in motoneuron interspike intervals J Neurophysiol 1968 31 574 587 5709873 Carandini M Ferster D Membrane potential and firing rate in cat primary visual cortex J Neurosci 2000 20 470 484 10627623 Carandini M Mechler F Leonard CS Movshon JA Spike train encoding in regular-spiking cells of the visual cortex J Neurophysiol 1996 76 3425 3441 8930283 de Ruyter van Steveninck RR Lewen GD Strong SP Koberle R Bialek W Reproducibility and variability in neural spike trains Science 1997 275 1805 1808 9065407 Freeman TCB Durand S Kiper DC Carandini M Suppression without inhibition in visual cortex Neuron 2002 35 759 771 12194874 Geisler WS Albrecht DG Visual cortex neurons in monkeys and cats: Detection, discrimination, and identification Vis Neurosci 1997 14 897 919 9364727 Granit R Kernell D Shortess GK Quantitative aspects of repetitive firing of mammalian motoneurons, caused by injected currents J Physiol (Lond) 1963 168 911 931 14072865 Gur M Beylin A Snodderly M Response variability of neurons in primary visual cortex (V1) of alert monkeys J Neurosci 1997 17 2914 2920 9092612 Hansel D van Vreeswijk C How noise contributes to contrast invariance of orientation tuning in cat visual cortex J Neurosci 2002 22 5118 5128 12077207 Heeger DJ Half-squaring in responses of cat simple cells Vis Neurosci 1992 9 427 443 1450099 Heggelund P Albus K Response variability and orientation discrimination of single cells in striate cortex of cat Exp Brain Res 1978 32 197 211 680039 Jagadeesh B Wheat HS Ferster D Linearity of summation of synaptic potentials underlying direction selectivity in simple cells of the cat visual cortex Science 1993 262 1901 1904 8266083 Kara P Reinagel P Reid RC Low response variability in simultaneously recorded retinal, thalamic, and cortical neurons Neuron 2000 27 635 646 11055444 Kenet T Bibitchkov D Tsodyks M Grinvald A Arieli A Spontaneously emerging cortical representations of visual attributes Nature 2003 425 954 956 14586468 Lankheet MJ Molenaar J van de Grind WA The spike generating mechanism of cat retinal ganglion cells Vision Res 1989 29 505 517 2603388 Mainen ZF Sejnowski TJ Reliability of spike timing in neocortical neurons Science 1995 268 1503 1506 7770778 Mechler F Neuronal response variability in the primary visual cortex [dissertation] 1997 New York New York University 153 Mechler F Ringach DL On the classification of simple and complex cells Vision Res 2002 42 1017 1033 11934453 Miller KD Troyer TW Neural noise can explain expansive, power-law nonlinearities in neural response functions J Neurophysiol 2002 87 653 659 11826034 Priebe NJ Ferster D Carandini M Mechler F The spike threshold nonlinearity gives rise to the dichotomy between V1 simple and complex cells Nat Neurosci 2004 In press Reich DS Victor JD Knight BW Ozaki T Kaplan E Response variability and timing precision of neuronal spike trains in vivo J Neurophysiol 1997 77 2836 2841 9163398 Ress D Heeger DJ Neuronal correlates of perception in early visual cortex Nat Neurosci 2003 6 414 420 12627164 Rice SO Mathematical analysis of random noise AT&T Tech J 1944 23 282 332 Rudolph M Destexhe A Characterization of subthreshold voltage fluctuations in neuronal membranes Neural Comput 2003 15 2577 2618 14577855 Shadlen MN Newsome WT The variable discharge of cortical neurons: Implications for connectivity, computation, and information coding J Neurosci 1998 18 3870 3896 9570816 Softky WR Koch C The highly irregular firing of cortical cells is inconsistent with temporal integration of random EPSPs J Neurosci 1993 13 334 350 8423479 Stevens CF Zador AM Input synchrony and the irregular firing of cortical neurons Nat Neurosci 1998 1 210 217 10195145 Svirskis G Rinzel J Influence of temporal correlation of synaptic input on the rate and variability of firing in neurons Biophys J 2000 79 629 637 10919997 Tolhurst DJ Movshon JA Thompson ID The dependence of response amplitude and variance of cat visual cortical neurons on stimulus contrast Exp Brain Res 1981 41 414 419 7215502 Troyer TW Miller KD Physiological gain leads to high ISI variability in a simple model of a cortical regular spiking cell Neural Comput 1997 9 971 983 9188190 Tsodyks M Kenet T Grinvald A Arieli A Linking spontaneous activity of single cortical neurons and the underlying functional architecture Science 1999 286 1943 1946 10583955 Tuckwell HC Nonlinear and stochastic theories. Volume 2, Introduction to theoretical neurobiology 1988 Cambridge (United Kingdom) Cambridge University Press 288 Vogels R Spileers W Orban GA The response variability of striate cortical neurons in the behaving monkey Exp Brain Res 1989 77 432 436 2792290 Volgushev M Pernberg J Eysel UT Comparison of the selectivity of postsynaptic potentials and spike responses in cat visual cortex Eur J Neurosci 2000 12 257 263 10651880 Volgushev M Pernberg J Eysel UT A novel mechanism of response selectivity of neurons in cat visual cortex J Physiol 2002 540 307 320 11927689 Wang XJ Calcium coding and adaptive temporal computation in cortical pyramidal neurons J Neurophysiol 1998 79 1549 1566 9497431

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020274Research ArticleMolecular Biology/Structural BiologyHomo (Human)Recognition and Accommodation at the Androgen Receptor Coactivator Binding Interface Recognition of AR Coactivator MotifsHur Eugene 1 Pfaff Samuel J 1 Payne E. Sturgis 2 Grøn Hanne 2 Buehrer Benjamin M 2 Fletterick Robert J flett@msg.ucsf.edu 3 1Graduate Group in Biophysics, University of CaliforniaSan Francisco, California, United States of America2Karo Bio, DurhamNorth Carolina, United States of America3Department of Biochemistry and Biophysics, University of CaliforniaSan Francisco, CaliforniaUnited States of America9 2004 24 8 2004 24 8 2004 2 9 e27426 3 2004 16 6 2004 Copyright: © 2004 Hur et al.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. The Structural Basis of a Prostate Cancer Protein's Unique Selectivity Prostate cancer is a leading killer of men in the industrialized world. Underlying this disease is the aberrant action of the androgen receptor (AR). AR is distinguished from other nuclear receptors in that after hormone binding, it preferentially responds to a specialized set of coactivators bearing aromatic-rich motifs, while responding poorly to coactivators bearing the leucine-rich “NR box” motifs favored by other nuclear receptors. Under normal conditions, interactions with these AR-specific coactivators through aromatic-rich motifs underlie targeted gene transcription. However, during prostate cancer, abnormal association with such coactivators, as well as with coactivators containing canonical leucine-rich motifs, promotes disease progression. To understand the paradox of this unusual selectivity, we have derived a complete set of peptide motifs that interact with AR using phage display. Binding affinities were measured for a selected set of these peptides and their interactions with AR determined by X-ray crystallography. Structures of AR in complex with FxxLF, LxxLL, FxxLW, WxxLF, WxxVW, FxxFF, and FxxYF motifs reveal a changing surface of the AR coactivator binding interface that permits accommodation of both AR-specific aromatic-rich motifs and canonical leucine-rich motifs. Induced fit provides perfect mating of the motifs representing the known family of AR coactivators and suggests a framework for the design of AR coactivator antagonists. A structural study of the androgen receptor shows how it interacts with coactivator proteins. The results also provide a possible framework for the development of new receptor antagonists ==== Body Introduction The androgen receptor (AR) is the cellular mediator of the actions of the hormone 5-α dihydrotestosterone (DHT). Androgen binding to AR leads to activation of genes involved in the development and maintenance of the male reproductive system and other tissues such as bone and muscle. However, it is the pivotal role of AR in the development and progression of prostate cancer that has led to increasing interest in this nuclear receptor. Presently, hormone-dependent prostate cancer is treated with a combination of strategies that reduce circulating levels of androgens, such as the administration of antiandrogens that compete for the androgen-binding pocket in the core of the C-terminal ligand-binding domain (LBD). The benefits of these treatments are typically transient, with later tumor growth associated with increases in expression levels of AR or its cofactors, or mutations that render AR resistant to antiandrogens (Gregory et al. 2001; Culig et al. 2002; Lee and Chang 2003). Alternative approaches to inhibiting AR transcriptional activity may therefore lie in disrupting critical protein associations the receptor needs for full function. The precise details of how AR binds the dozens of coregulator proteins reported to associate with different regions of AR in vivo remain poorly understood (Lee and Chang 2003). Many nuclear receptors activate transcription by binding short leucine-rich sequences conforming to the sequence LxxLL (where “x” is any amino acid), termed nuclear receptor (NR) boxes, which are found within a variety of NR coactivators including the p160 family. Hormone binding to the LBD stabilizes the C-terminal helix of the receptor, helix 12, in a conformation that completes a binding surface for these LxxLL motifs (Darimont et al. 1998; Nolte et al. 1998; Shiau et al. 1998; Bledsoe et al. 2002). The structural elements composing this binding interface, consisting of helices 3, 4, 5, and 12 of the receptor, are synonymous with a previously defined hormone-dependent activation function that lies within the LBD termed activation function (AF)–2. Association of p160 coactivators allows the recruitment and assembly of a number of other cofactors that together modulate the state of chromatin and interactions with components of the basal transcription machinery to initiate transcription (Glass and Rosenfeld 2000). AR, however, utilizes multiple mechanisms to activate gene transcription. Generally, AR activity is dependent on contributions from multiple transactivation functions that lie within the N-terminal domain (NTD) collectively called AF-1. Although the AR AF-2 can bind to a restricted set of LxxLL motifs (Ding et al. 1998; He et al. 1999; Needham et al. 2000) and is relatively potent (Wang et al. 2001), it usually displays weak independent activity at typical androgen-regulated genes, with significant activity observed only in the presence of high levels of p160 coactivators, as detected in some prostate cancers (He et al. 1999; Gregory et al. 2001). Instead, the AR AF-2 exhibits a distinct preference among NRs for phenylalanine-rich motifs conforming to the sequence FxxLF (He et al. 2000; He and Wilson 2003). Such motifs have been identified in the AR NTD and in an AR cognate family of coactivators that includes AR-associated protein (ARA) 54, ARA55, and ARA70 (He et al. 2000, 2002b; Lee and Chang 2003). The NTD FxxLF motif (residues 23–27) mediates a direct, interdomain, ligand-dependent interaction between the NTD and LBD (N/C interaction) that is thought to facilitate dimerization, stabilize androgen binding, and possibly regulate AF-1 and AF-2 activity (Langley et al. 1998; He et al. 2000). In addition, the NTD also contains a related hydrophobic motif, WxxLF (residues 433–437), that nucleates formation of an alternative N/C interaction that may serve to inhibit AR activity (He et al. 2000, 2002a; Hsu et al. 2003). Presently, how the AR AF-2 surface can accommodate residues with bulky aromatic side chains and distinguish FxxLF motifs from LxxLL motifs is not known. To understand the structural basis of this unusual coactivator recognition preference, we characterized the full repertoire of interacting sequences using phage display to define amino acids preferred at the AR coactivator binding interface. Crystal structures of the AR LBD in complex with several phage display–derived peptides reveal the structural basis of FxxLF motif specificity and an induced fit of the receptor that allows accommodation of other related hydrophobic motifs. Comparisons of the structures suggest strategies for the design of AR coactivator antagonists. Results AR Preference for Aromatic Groups in Coregulator Recognition Phage display has been used to study coactivator recognition specificity and to identify coactivator motif sequence variants preferred by the estrogen receptor (ER), thyroid hormone receptor (TR) β, and most recently AR (Chang et al. 1999; Norris et al. 1999; Paige et al. 1999; Northrop et al. 2000; Hsu et al. 2003). Using phage display, we screened more than 2 × 1010 randomized peptides against DHT-bound AR LBD. Selections identified sequences containing hydrophobic motifs that were primarily aromatic in character, consistent with another recent study (Hsu et al. 2003) (Figure 1). Of these aromatic motifs, FxxLF and related motifs with substitutions of phenylalanine or tryptophan for leucine at positions +1, +5, or both, dominated the selections. (Peptide residues are numbered in reference to the first hydrophobic residue of the core motif, which is numbered +1. Residues preceding the first hydrophobic residue are numbered negatively in descending order starting with −1.) Substitutions of tyrosine at the +5 position were also observed, but to a much lesser extent (unpublished data). At the +4 position, valines, methionines, and even the aromatic residues phenylalanine and tyrosine were observed (Figure 1; unpublished data). In general, LxxLL motifs were not selected. The LxxLL motif shown in Figure 1 was derived from prior phage selections with ER and subsequently demonstrated to bind AR in FRET-based screens in vitro (unpublished data). Figure 1 AR LBD–Interacting Peptides Selected by Phage Display Hydrophobic residues of the core motif are highlighted in yellow. Residues in bold were ordered in electron density maps. Preliminary characterization of the subset of AR-interacting peptides shown in Figure 1 confirmed that each competed for binding of in vitro translated AR cofactors to bacterially expressed AR LBD in pulldown assays, and generally did so with modestly improved efficiency relative to the native FxxLF motif from the AR NTD and significantly greater efficiency than a native LxxLL motif from glucocorticoid receptor-interacting protein 1 (GRIP1) NR box 3 (P. Webb, personal communication). The equilibrium dissociation constants (Kd) were directly determined for the interaction between the AR LBD and FxxLF and LxxLL peptides and one variant tryptophan-containing peptide, FxxLW, using surface plasmon resonance (Table 1). The Kd for FxxLF was 1.1 μM, similar to the affinities of physiologically derived FxxLF motifs determined previously by isothermal titration calorimetry (He and Wilson 2003). The affinity of LxxLL was less than 2-fold weaker, with a Kd of 1.8 μM, but more than three times stronger than the tightest binding p160-derived LxxLL motif, NR box 3 of transcriptional intermediary factor 2 (TIF2) (He and Wilson 2003). Surprisingly, the affinity of FxxLW, with a Kd of 920 nM, was slightly better than FxxLF, in spite of the presence of the tryptophan residue at the +5 position. Together, our results are consistent with the notion that the phage display peptides interact with the same AR surface that binds FxxLF and LxxLL motifs in native cofactors, and that they do so with similar or improved affinities relative to their natural counterparts. Table 1 Rate and Dissociation Constants for the Interaction between the AR LBD and Selected Peptides Surface plasmon resonance data were best fit using the two-state conformational change model (Warnmark et al. 2001, 2002). Dissociation constants were calculated from rate constants as described previously (Warnmark et al. 2001) One Site Fits All To understand the binding mode of different AR coactivators, we determined the crystal structures of DHT-bound AR LBD without peptide and in complex with each of the seven peptides listed in Figure 1. All complexes crystallized in the space group P212121 with one molecule per asymmetric unit and unit cell dimensions similar to those observed in previous AR LBD crystal structures (Matias et al. 2000; Sack et al. 2001). Overall structural features of the complexes are shown in Figure 2. Peptides assumed short α helical conformations centered on the core hydrophobic motif and bound in a solvent channel relatively free of crystal contacts on a groove formed by helices 3, 4, 5, and 12 of the receptor (Figure 2A). Detailed data collection and refinement statistics, as well as buried surface areas for each complex, are listed in Table 2. The structures confirm previous suggestions that AR utilizes a single binding interface for LxxLL and noncanonical aromatic-rich motifs (He et al. 2000, 2002a). Only side chains move to accommodate the array of peptides, sometimes considerably, with the unbranched side chains of Lys720, Met734, and Met894 making the largest conformational changes upon binding of peptide (Figure 2B). Figure 2 A Structural Profile of the AR Coactivator Binding Interface AR–peptide complexes are colored as follows: FxxLF, yellow; FxxLW, orange; WxxLF, wheat; WxxVW, purple; FxxYF, green; FxxFF, blue; LxxLL, pink; unbound, grey. (A) Cα trace of the peptides superimposed onto the AF-2. For clarity only the LBD of AR–FxxLF is shown. (B) Superposition of the LBD of the AR–peptide complexes in the region of the coactivator interface. Backbone atoms are shown as a Cα trace. Side chains of residues composing the interface are shown as sticks. (C) Hydrophobic side chains of the core motif superimposed as in (B). Table 2 Summary of Structures and Crystallographic Statistics aNumbers in parenthesis denote values for the highest resolution shell b R sym = Σ|I − <I>| / Σ (I) c R cryst = Σ |F o − F c| / Σ |F o|, where F o and F c are observed and calculated structure factors, respectively; R free was calculated similarly with a randomly selected set of reflections consisting of 5% of total reflections that were excluded from refinement dValues for side chain atoms only FxxLF The mechanisms that permit AR to accommodate motifs with bulky phenylalanine residues were assessed in a crystal structure of the AR LBD in complex with the FxxLF peptide. The FxxLF peptide recapitulates the binding mode of p160-derived LxxLL motifs to other nuclear receptors (Darimont et al. 1998; Nolte et al. 1998; Shiau et al. 1998; Bledsoe et al. 2002). The peptide forms a short α helix whose hydrophobic face, composed of Phe+1, Leu+4, and Phe+5, binds an L-shaped groove formed by helices 3, 4, 5, and 12 of the LBD that is composed of three subsites that accommodate each hydrophobic residue (Figures 2A and 3A). The conserved charged residues at either end of the cleft, Lys720 and Glu897, the so-called charge clamp residues, make electrostatic interactions with the main chain atoms at the ends of the peptide helix: Lys720 with the carbonyl group of Phe+5, and Glu897 with the amide nitrogens of Phe+1 and Arg−1 (Figure 3C). Glu897 also interacts with the side chain of Arg−1. The two interior residues of the motif, Glu+2 and Ser+3, are solvent exposed and do not interact with the receptor. Figure 3 Interactions of FxxLF and LxxLL with the AR LBD (A and B) FxxLF (A) and LxxLL (B) bound to the AR AF-2 interface. FxxLF and LxxLL are shown as yellow and pink Cα coils, respectively. Helices 3, 4, and 5 of the LBD are shown as blue ribbons; Helix 12 is shown in green. LBD residues interacting with peptides are depicted as white sticks. For clarity only peptide side chains making significant interactions with the LBD are shown. (C and D) Hydrogen-bonding interactions between backbone atoms of FxxLF (C) and LxxLL (D) with Glu897 of the LBD. Peptide alpha carbons are labeled. Comparison of AR alone and AR in complex with FxxLF (and other aromatic-rich peptides described below) reveals that the AF-2 cleft reorganizes to accommodate the bulky peptide side chains (see Figures 2B and 4). The unbranched side chains of Lys720 and Met734 move from an extended conformation over the +5 pocket to one almost perpendicular to the surface of the protein. The pockets for Phe+1 and Phe+5 are arranged in a line, forming a deep, extended cleft on the LBD spanning the length of the two side chains on the face of the peptide helix (see Figures 3A and 4B). Phe+1, almost entirely solvent inaccessible, binds face down at the base of this groove, making hydrophobic contacts with Leu712, Val716, Met734, Gln738, Met894, and Ile898, which define the +1 pocket. The top of the groove, composed of Val716, Lys720, Phe725, Ile737, Val730, Gln733, and Met734, narrows to form the +5 pocket. Met734 and the aliphatic portion of Lys720 constrict this subsite, forming van der Waals interactions with opposite faces of the Phe+5 benzyl ring. Together, the +1 and +5 residues are almost entirely solvent inaccessible. In contrast, Leu+4 binds in a shallow hydrophobic patch consisting of Leu712 and Val716 lined at the ridges by Val713 and Met894 and is largely solvent exposed. Figure 4 Induced Fit of the AR AF-2 Interface Surface representations of the AR AF-2 interface. The unbound structure is shown in (A), the FxxLF bound in (B), and the LxxLL bound in (C). Side chains of the hydrophobic residues of the core motifs of FxxLF and LxxLL are shown as spheres. LxxLL The preference of AR for motifs with aromatic groups over leucine-rich motifs was assessed with a crystal structure of the AR LBD in complex with the LxxLL peptide. The structure reveals similarities between the binding modes of the LxxLL and FxxLF motifs to AR, and other LxxLL motifs to other nuclear receptors. The LxxLL motif adopts a helical conformation, and interactions of the motif with the AF-2 cleft are predominantly hydrophobic, with the three leucine residues of the motif contributing most of the interactions. However, significant differences can be seen between the binding mode of the LxxLL motif to AR and that of p160-derived LxxLL motifs to other nuclear receptors. First, flanking residues were largely disordered, with only two N-terminal flanking residues and one C-terminal residue visible in electron density maps (see Figures 1 and 3B). This contrasts with extended structures seen in the p160-derived LxxLL motifs in complex with their cognate receptors (Darimont et al. 1998; Nolte et al. 1998; Shiau et al. 1998; Bledsoe et al. 2002). Second, the LxxLL peptide backbone forms hydrogen bonds with only one of the two conserved charge clamp residues, Lys720. A shift in the position of the LxxLL peptide helix precludes direct interactions with Glu897 (see Figures 2A and 3D). This shift results from changes in the geometry of the +1 and +5 subsites mediated by Met734, which moves 2.5Å toward the +1 pocket (see Figures 2B and 4C) and enables binding of a leucine at the +5 subsite by a simultaneous widening and shallowing of the pocket. This movement of Met734 causes displacement of the +1 residue, resulting in a rotation of the peptide helix away from helix 12, toward helix 3. A slight translation of the peptide helix also occurs away from helix 12 because of the shorter side chain length of leucine (see Figure 2A). Side chains of residues flanking the first leucine of the motif make additional hydrophobic interactions with the AR surface (see Figure 3B). Trp+2 reaches over Met734, clamping the methionine in between itself and Leu+1. Leu−1 extends over Met894, abutted against Glu893. These interactions likely explain the moderate affinity of AR for this particular LxxLL motif despite suboptimal complimentarity with the residues of the core motif (as discussed below) and the loss of main chain interactions with Glu897. WxxLF, FxxLW, and WxxVW To understand how the AR AF-2 accommodates tryptophan residues, structures of AR in complex with peptides containing tryptophan substitutions at the +1 or +5 position, or both, were determined (Figure 5). Surprisingly, WxxLF, analogous to the only tryptophan-containing motif known in vivo, WHTLF in the AR NTD, was relatively disordered, with the peptide displaying the highest B-factor and least well defined density, suggesting that it binds with the lowest affinity (Table 2). Nonetheless, each of the tryptophan peptides adopted similar helical conformations. As described above for the LxxLL motif, substitutions at the +1 and +5 positions for non-phenylalanine residues result in shifts of the peptide helix (see Figure 2A). Consequently, backbone interactions with Lys720 are maintained, but interactions with the other charge clamp residue, Glu897, are lost. Once again, however, flanking residues within the peptide make additional contacts with the AR surface, and, unlike the LxxLL peptide, these contacts include Glu897. In FxxLW and WxxVW, the −2 serine (Figure 6) forms a bidentate hydrogen-bonding interaction, making hydrogen bonds to both Glu897 and the backbone amide group of the +2 residue. Ser−2 of WxxLF similarly interacts with Glu897, but is too distant for helical-capping interactions with the +2 amide group. Instead, Glu893, in a more typical interaction with the +1 amide nitrogen, caps the WxxLF helix (Figure 6B). Thus, tryptophan substitutions are tolerated, but they induce a shift in the peptide backbone that precludes interactions with one of the charge clamp residues. This suboptimal interaction is compensated partially by interactions of flanking residues with the AR surface. Figure 5 Interactions of the Tryptophan Motifs with the AR LBD FxxLW (A), WxxLF (B), and WxxVW (C) bound to the AR AF-2 interface. FxxLW, WxxLF, and WxxVW are shown as orange, beige, and purple Cα coils, respectively. The LBD is depicted as in Figure 3. Figure 6 Interactions of Ser−2 with Glu897 Interactions between Ser−2 of the peptides (A) FxxLW, (B) WxxLF, (C) WxxVW, and (D) FxxFF and Glu897 of the LBD. Peptide alpha carbons are labeled. FxxFF and FxxYF Finally, effects of substitutions at the +4 position were assessed in structures of AR in complex with peptides containing FxxFF and FxxYF motifs (Figure 7). Surprisingly, the binding mode of FxxFF to AR resembled that of the tryptophan peptides more closely than the binding mode of FxxLF (see Figures 2A and 7B). Like the tryptophan peptides, interactions with Glu897 are mediated by Ser−2 instead of the peptide backbone (see Figure 6D). Deviations from ideal helical geometry allow Phe+4 to bind facedown in the +4 pocket with the benzyl ring stacked against Val713. Figure 7 Interactions of FxxYF and FxxFF with the AR LBD FxxYF (A) and FxxFF (B) bound to the AR AF-2 interface. FxxYF and FxxFF are shown as yellow and orange Cα coils, respectively. The LBD is depicted as in Figure 3. By contrast, the conformation of FxxYF was the closest to FxxLF (see Figure 2A). Other than FxxLF, only FxxYF makes direct backbone interactions with Glu897. Unlike the facedown orientation of Phe+4 observed in the FxxFF peptide, Tyr+4 is bound edgewise into the shallow +4 pocket, making interactions with Val713, Val716, and the aliphatic portion of Lys717. FxxYF was the most ordered of all the peptides, with 12 out of 15 residues observed in the electron density (see Figures 1 and 7A). Significant interactions were observed involving residues other than hydrophobic residues of the motif. Lys+2 and Met+6 are predominantly solvent exposed, extending out over the protein surface. Met+6 is bound on top of Phe+5, while Lys+2 makes a water-mediated hydrogen bond with Asp731. Thr−3 of the peptide defines a new subsite, with the hydroxyl group forming a hydrogen bond to Gln738 and the methyl group making hydrophobic contacts in a pocket formed by Glu897, Ile898, and Val901. Similar interactions were observed in the glucocorticoid receptor (GR)–TIF2 complex involving the −3 glutamine of the TIF2 NR box 3 motif (Bledsoe et al. 2002). However a valine to asparagine substitution at the residue corresponding to 901 in AR creates a pocket with a more polar character in GR (Figure 8). Figure 8 Sequence Alignment of the AF-2 Region of NRs Residues composing the coactivator interface of AR are highlighted in yellow. The absolutely conserved glutamate and lysine composing the charge clamp are highlighted in pink and blue, respectively. Residue numbering is that of AR. Restrictions of the Three Subsites Together, the structures described above permit an assessment of the way that individual subsites of the AR AF-2 cleft accommodate hydrophobic groups. The indole rings of tryptophan and the phenyl rings of phenylalanine fit into their pockets analogously with the +1 and +5 residues bound facedown and edgewise, respectively, into the AF-2 cleft. On the other hand, the position of the +4 residue is variable, with binding in this shallow pocket largely dictated by the position of the peptide backbone caused by the bound conformations of the +1 and +5 residues (see Figure 2C). Small shifts in the position of the N-terminal of helix 12 can be seen, which reposition Met894 for more optimal contacts with +4 residues bound at that subsite (see Figure 2B). The binding mode detected in the +1 pocket is the most conserved of the three hydrophobic subsites (see Figure 2C). The benzyl moiety of the indole side chains superimpose with the corresponding benzyl side chains of the phenylalanine-rich motifs, effectively mimicking interactions of a phenylalanine residue. However, the presence of a hydrogen-bonding partner on the indole side chain enables an additional polar interaction not seen in the phenylalanine-rich motifs between the indole nitrogen and Gln738 (see Figure 5B). Unexpectedly, this additional interaction in the +1 pocket does not occur with Trp+1 of WxxVW (see Figure 5C). While similarly distanced to make the same interaction, the plane of the indole ring is rotated about 20° relative to that of WxxLF, causing it to be at a poor angle for strong hydrogen bonding to Gln738. Binding of tryptophans in the +5 pocket is slightly more variable (see Figure 2C). Trp+5 of WxxVW is bound similarly to phenylalanine residues at the same position. Only the six-membered ring of the indole group is fully buried in the pocket. The five-membered ring of the indole side chain sticks out, solvent exposed. In contrast, the +5 indole group of FxxLW is rotated almost 90°, resulting in burial of both rings of the indole group, as well as the formation of a strong hydrogen bond between the indole nitrogen and Gln730 (see Figure 5A). Binding in this orientation appears to be highly favorable, as the FxxLW peptide deviates from helical geometry at the +5 position to do so. Discussion The crystal structures reported here reveal how AR binds coactivator motifs with bulky aromatic hydrophobic groups and permit construction of a profile of the AR coregulator interface (see Figure 2). In some ways, this interface resembles those of other nuclear receptors: it is an L-shaped hydrophobic cleft comprised of three distinct subsites that bind hydrophobic groups at the +1, +4, and +5 positions in cognate peptides. Moreover, the so-called charge clamp residues (Lys720 and Glu897) bracket the cleft. Nonetheless, the AR coregulator recognition site is unique in that it rearranges upon motif binding to form a long, deep, and narrow groove that accommodates aromatic residues at the +1 and +5 positions (Figure 9). Sequence alignments of AR with other NRs suggest that a unique combination of substitutions at Val730, Met734, and Ile737 combine to permit the formation of a smoother, flatter interaction surface that displays a higher complimentarily to aromatic substituents than to branched aliphatic (see Figure 8). Of these, methionine, the only unbranched hydrophobic amino acid and the most accommodating, at a key position between the +1 and +5 sites, allows the AR AF-2 interface to vary the size and shape of its pockets to associate with a more diverse set of coregulators. GR also contains a methionine residue at this position, raising the possibility that it may also employ induced fit to broaden motif recognition. While naturally occurring mutations in AR have yet to be observed at Met734, it is interesting to note that mutations at Val730 and Ile737 have been reported in patients with prostate cancer and androgen insensitivity, respectively (Newmark et al. 1992; Quigley et al. 1995; Gottlieb et al. 1998). Figure 9 Surface Complimentarity of Hydrophobic Motifs in the AR, ERα, and GR AF-2 Clefts (A) AR–FxxLF, (B)AR–LxxLL, (C) ERα–GRIP1 (LxxLL) (Shiau et al. 1998), and (D) GR-TIF2 (LxxLL) (Bledsoe et al. 2002). The inside surfaces of the AF-2 cleft in AR, ERα, and GR are depicted. The LBD is additionally shown as a Cα trace with key side chains shown as white sticks. Phenylalanines and leucines of the FxxLF and LxxLL motifs are shown as spheres. The same characteristics that make the AR AF-2 ideal for binding of longer, aromatic side chains also make it less well suited for binding of shorter, branched side chains. Although changes in the position of Met734 widen the groove towards the +5 subsite to permit binding of leucine residues, the gross features of the groove remain largely the same (see Figure 9B). As a result, the +1 and +5 leucines bind in a smooth, elongated groove and interactions between the +1 and +5 residues on the face of the peptide helix, or with a hydrophobic “bump” present in other receptors caused by a isoleucine to leucine substitution between the +1 and +5 subsites, are absent. Thus, a smaller proportion of the available surface area is available for van der Waals interactions. Unlike the conserved interaction modes of aromatic residues with the +1 and +5 sites, binding interactions at the +4 site are variable and characterized by nonspecific interactions. This finding agrees with the relatively high conservation of residues at the +1 and +5 positions of AR-interacting motifs and suggests that these residues drive peptide interaction with the LBD, whereas the +4 site is less critical. Indeed, the +4 pocket is shallow, surface exposed, and relatively featureless, explaining the assortment of residues selected at the +4 position. It is likely that any hydrophobic residue that does not clash with surrounding residues would be suitable at this subsite. While peptide motif recognition is governed by hydrophobic interactions, polar interactions from backbone atoms and residues outside the core motif also contribute. With the exception of FxxFF, motifs containing phenylalanines at the +1 and +5 positions present canonical main chain interactions with both charge clamp residues, Lys720 and Glu897. This finding stands in contrast to predictions of previous studies (Alen et al. 1999; He et al. 1999; Slagsvold et al. 2000; He and Wilson 2003), which concluded that Lys720 was dispensable for FxxLF binding and that Glu897 was required for binding to FxxLF and LxxLL motifs. Lys720 comprises a significant portion of the +5 subsite, making important van der Waals interactions with the Phe+5 benzyl group in addition to hydrogen bonds to the motif backbone. These results suggest that Lys720 is required for binding of FxxLF motifs. However, it may be that enough binding energy is provided by the other residues of the +5 subsite (i.e., Met734), as well as by the other subsites themselves, such that removal of Lys720 would have little effect on binding. Observations that Lys720 plays a greater role in LxxLL motif binding are likely due to the fact that there is less surface area contributing to van der Waals contacts in LxxLL motifs. Disrupting binding contributions from Lys720 would thus have a more detrimental effect on binding. On the other hand, Glu897 interacts with the FxxLF peptide backbone, but is disengaged from the LxxLL peptide backbone. One possible explanation for the apparent requirement for Glu897 in LxxLL binding is that it might interact with residues outside of the core motif. The corresponding glutamate of GR, Glu 755, forms hydrogen bonds with the −3 asparagine of TIF2 NR box 3 (Bledsoe et al. 2002), and Glu897 of AR participates in noncanonical interactions with the hydroxyl group of a Ser−2 residue that was selected in all of our tryptophan-containing peptides. This is especially intriguing given that the only WxxLF motif known in vivo, located in the AR NTD, also possesses a Ser−2 residue. WxxLF also makes backbone interactions with an alternate charge clamp residue, Glu893, pointing towards adaptability in AR AF-2 charge clamp formation. Sequence alignment of NR coactivator sequences shows that positively charged residues are favored N-terminal to the core hydrophobic motif while negatively charged residues are favored C-terminal to the motif (He and Wilson 2003). Our phage-selected peptides are consistent with this trend. Arginines and lysines were observed at the N-terminal −1 position in all peptides, except for LxxLL, in which Arg was present at the −3 position. Moreover, four out of seven peptides contained negatively charged aspartate or glutamate residues C-terminal to the core motif. While previous studies have shown that complementary interactions between charged residues flanking coactivator signature motifs of coactivators and charged residues surrounding the AF-2 cleft modulated binding to the receptor (He and Wilson 2003), we find that the flanking charged residues are typically disordered in the electron density, with only Arg−1 of FxxLF interacting with Glu897, and Lys+2 of FxxYF forming a water-mediated hydrogen bond to Asp731. Thus, if charge–charge interactions between flanking peptide residues and the AR surface occur, they are too weak to be detected crystallographically. Finally, the AR AF-2 surface is an attractive target for pharmaceutical design. Selective peptide inhibitors that bind the AF-2 surface of liganded ERα, ERβ, and TRβ have been developed (Geistlinger and Guy 2003), and similar α-helix–mediated protein–protein interfaces have successfully been targeted with tight binding small molecule inhibitors (Asada et al. 2003; Vassilev et al. 2004). Drugs that directly interfere with coactivator binding or formation of the AR N/C interaction would likely inhibit AR activity, perhaps even in androgen-resistant prostate cancers in which conventional therapies have failed. Strategies for designing AR coactivator antagonists are revealed in spite of the changes to the structure at the interface. Together the +1, +4, and +5 subsites contribute the majority of buried surface area of the peptide–LBD interaction (Table 2). Inhibitors may be designed by varying hydrophobic constituents at these hotspots. The +1 and +5 subsites of AR have a unique preference for aromatic side chains and provide the most viable starting points for designing AR-specific inhibitors. Aromatic groups, possibly with polar constituents to exploit hydrogen bonding interactions with Gln733 and Gln738 in the +1 and +5 subsites, respectively, may provide promising leads. Indeed, initial screens have yielded compounds that bind to the +1 subsite in such a manner (E. Estébanez-Perpiñá, personal communication). Poorly conserved binding and a lack of strong structural features at the +4 subsite suggest that this site may be incorporated for achieving other characteristics important for inhibitors besides fit. Synthetic strategies that link together groups that bind with moderate affinity to the +1, +5, and possibly +4 subsites may yield tight binding inhibitors of AR coactivator association. Materials and Methods Protein purification Expression and purification of the AR LBD for crystallization were performed essentially as described (Matias et al. 2000). The cDNA encoding the chimp AR LBD (residues 663–919—human numbering), which displays 100% identity to the human form in protein sequence, was cloned into a modified pGEX-2T vector (Amersham Biosciences, Piscataway, New Jersey, United States) and expressed as glutathione S-transferase (GST) fusion protein in the E. coli strain BL21 (DE3) STAR in the presence of 10 μM DHT. Induction was carried out with 30 μM IPTG at 17 °C for 16–18 h. E. coli cells were lysed in buffer (10 mM Tris, [pH 8.0], 150 mM NaCl, 10% glycerol, 1 mM TCEP, 0.2 mM PMSF) supplemented with 0.5 μg/ml lysozyme, 5 U/ml benzonase, 0.5% CHAPS, and 10 μM DHT. All buffers for further purification steps contained 1 μM DHT. Soluble cell lysate was adsorbed to Glutathione Sepharose 4 Fast Flow resin (Amersham Biosciences), washed with buffer containing 0.1% n-octyl β-glucoside, and eluted with 15 mM glutathione. After cleavage of the GST moiety with thrombin, final purification of the AR LBD was carried out using a HiTrap SP cation exchange column (Amersham Biosciences). Eluted AR LBD was dialyzed overnight at 4 °C against buffer containing 50 mM HEPES (pH 7.2), 10% glycerol, 0.2 mM TCEP, 20 μM DHT, 150 mM Li2SO4, and 0.1% n-octyl β-glucoside, then concentrated to greater than 4 mg/ml for crystallization. Purification of AR LBD for use in phage affinity selection was carried out as above without the final dialysis and concentration steps. The expression construct contained the AR LBD as an inframe fusion with GST in a modified pGEX-2T vector containing both a flexible region and an AviTag sequence (Avidity, Denver, Colorado, United States) allowing in vivo biotinylation. The GST–AR LBD fusion expression plasmid was cotransformed with a plasmid-encoding E. coli biotin ligase (Avidity) into BL21 (DE3) STAR cells. Protein expression was carried out as above but with induction supplemented with 50 μM biotin to ensure quantitative biotinylation of AR LBD. Phage affinity selections and peptide identification Phage affinity selections were performed essentially as described (Paige et al. 1999). Biotinylated AR LBD (10 pmol/well) was incubated in streptavidin-coated Immulon 4 96-well plates (Dynatech International, Edgewood, New Jersey, United States) in TBST (10 mM Tris-HCl [pH 8.0], 150 mM NaCl, 0.05% Tween 20) with 1 μM DHT for 1 h at 4 °C. Affinity selections were performed in TBST containing 1 μM DHT. M13 phage distributed among 24 libraries displaying a total of greater than 2 × 1010 different random or biased amino acid sequences were added to the wells containing immobilized AR LBD and incubated for 3 h at 4 °C. After washing, bound phage were eluted using pH 2 glycine. Enrichment of phage displaying target-specific peptides was monitored after each round of affinity selection using an anti-M13 antibody conjugated to horseradish peroxidase in an ELISA–type assay. Synthetic peptides corresponding to the deduced amino acid sequences from receptor-specific phage were tested for their ability to interact with purified AR LBD using a FRET–based assay format. Peptides were synthesized according to the deduced amino acid sequence displayed on phage with an additional C-terminal amino acid sequence consisting of SGSGK to allow the attachment of a biotin tag (Anaspec, San Jose, California, United States). Flourophor conjugates were prepared by incubating either biotinylated peptides with streptavidin-cryptate (Cis Bio International, Bagnols Sur Ceze Cedex, France), or biotinylated AR LBD with streptavidin-XL665 (Cis Bio). Interaction between peptide and AR LBD was monitored by the ratio of energy transfer by excitation at 320 nm and emission at 625 nm and 665 nm. Surface plasmon resonance Affinities of peptides to the AR LBD were determined with a Biacore (Piscataway, New Jersey, United States) 2000 instrument. A peptide derived from silencing mediator for RXR and TR 2 (SMRT2) served as a negative control. 1 mM peptide stock solutions in DMSO were diluted into HBS-P buffer (10 mM HEPES [pH 7.4], 150 mM NaCl, 0.005% Surfactant P20) to generate 10 μM working solutions. HBS-P buffer was flowed through the cells to achieve a stable baseline prior to immobilization of the biotinylated peptides. To achieve the binding of approximately 250 RU of peptides to individual cells, working solutions of peptides were diluted to 100 nM in HBS-P buffer. Unbound streptavidin sites were blocked by injection of a 1 mM biotin solution at a rate of 10 μl/min. Purified AR LBD was diluted into HBS-P buffer to a concentration of 10 μM and injected into all four Flowcells using the Kinject protocol at a flow rate of 10 μl/min (contact time 360 s, dissociation time 360 s). Following the dissociation phase, the surface of the chip was regenerated to remove residual AR LBD by QuickInject of buffer containing 10 mM HEPES and 50% ethylene glycol (pH 11). Following the establishment of a stable baseline, the same procedure was repeated using a series of AR LBD dilutions (5 μM, 1 μM, and 300 nM) in an iterative manner. Analysis of the data was performed using BIAevaluation 3.0 software (Biacore). The SMRT2 signals were subtracted as background from the three remaining peptide signals. Data were best fit using the two-state conformational change model (Warnmark et al. 2001, 2002). Crystallization, data collection, and refinement Purified, concentrated AR LBD was combined with 3x to 6x molar excess of peptide and incubated 1 h at room temperature before crystallization trials. Complexes were crystallized using the hanging drop vapor diffusion method. Protein–peptide solution was combined in a 1:1 ratio with a well solution consisting of 0.6–0.8 M sodium citrate and 100 mM Tris or HEPES buffer (pH 7–8). Crystals typically appeared after 1–2 d, with maximal size attained within 2 wk. For data collection, crystals were swiped into a cryo-protectant solution consisting of well solution plus 10% glycerol before flash freezing in liquid nitrogen. The addition of ethylene glycol to a well concentration of 10%–20% was later found to both improve crystal quality and enable the freezing of crystals directly out of the drop. Datasets were collected at 100K at the Advanced Light Source (Lawrence Berkeley Laboratory, Berkeley, California, United States), beamline 8.3.1, with either a ADSC Quantum 315 or Quantum 210 CCD detector. Data were processed using Denzo and Scalepack (Otwinowski and Minor 1997). Molecular replacement searches were performed with rotation and translation functions from CNS (Brunger et al. 1998). Initial searches for AR–FxxLF were performed using the structure of AR–R1881 (PDB: 1E3G) with R1881 omitted from the search model. Subsequent searches for all other complexes were performed using the refined LBD structure from the AR–FxxLF complex. To minimize the possibility of model bias, FxxLF peptide and DHT were omitted from all molecular replacement searches. Protein models were built by iterative rounds of simulated annealing, conjugate gradient minimization, and individual B-factor refinement in CNS followed by manual rebuilding in Quanta 2000 (Accelrys, San Diego, California, United States) using σA-weighted 2F o − F c, F o − F c, and simulated annealing composite omit maps. Superposition of structures was performed with LSQMAN (Kleywegt 1996). Buried surface area calculations were performed with CNS. All figures were generated with PyMOL (DeLano 2002). Coordinates and structure factors for all complexes have been deposited in the Protein Data Bank. Accession numbers are listed in Table 2. Supporting Information Accession Numbers The Swiss-Prot (http://www.ebi.ac.uk/swissprot) accession numbers for the gene products discussed in this paper are AR (P10275), ARA54 (Q9UBS8), ARA55 (Q9Y2V5), ARA70 (Q13772), ER (P03372, Q92731), glucocorticoid receptor-interacting protein 1 NR box 3 (Q61026 ), GR (P04150), NR box 3 of TIF2 (Q15596), and TR β (P10828). The Protein Data Bank (http://www.rcsb.org/pdb) accession numbers for the structures used in this paper are FxxFF (1T73), FxxLF (1T7R), FxxLW (1T79), FxxYF (1T7M), LxxLL (1T7F), unbound (1T7T), WxxLF (1T74), and WxxVW (1T76). We would like to thank Erin Anderson-Chisenhall for assistance in protein purification, James Holton and the staff at ALS beamline 8.3.1 for assistance in data collection, and Paul Webb for critical review of the manuscript. This work was supported by funds from the Prostate Cancer Foundation and National Institutes of Health grant R21 CA95324 to RJF. Conflicts of interest. The authors have declared that no conflicts of interest exist. Author contributions. EH, BB, and RF conceived and designed the experiments. EH, SP, ESP, HG, and BB performed the experiments. EH, SP, ESP, HG, BB, and RF analyzed the data. BB and RF contributed reagents/materials/analysis tools. EH, BB, and RF wrote the paper. Academic Editor: Ueli Schibler, University of Geneva Citation: Hur E, Pfaff SJ, Payne ES, Gron H, Buehrer BM, et al. (2004) Recognition and accommodation at the androgen receptor coactivator binding interface. PLoS Biol 2(9): e274. Abbreviations AFactivation function ARandrogen receptor ARAandrogen receptor-associated protein DHT5-α dihydrotestosterone ERestrogen receptor FxxFFphenylalanine-x-x-phenylalanine-phenylalanine FxxLFphenylalanine-x-x-leucine-phenylalanine FxxLWphenylalanine-x-x-leucine-tryptophan FxxYFphenylalanine-x-x-tyrosine-phenylalanine GRglucocorticoid receptor GRIP1glucocorticoid receptor-interacting protein 1 GSTglutathione S-transferase Kdequilibrium dissociation constant LBDligand-binding domain LxxLLleucine-x-x-leucine-leucine N/C interactioninteraction between the N-terminal domain and the ligand-binding domain NRnuclear receptor NTDN-terminal domain SMRT2silencing mediator for RXR and TR 2 TIF2transcriptional intermediary factor 2 TRthyroid hormone receptor WxxLFtryptophan-x-x-leucine-phenylalanine WxxVWtryptophan-x-x-valine-tryptophan ==== Refs References Alen P Claessens F Verhoeven G Rombauts W Peeters B The androgen receptor amino-terminal domain plays a key role in p160 coactivator-stimulated gene transcription Mol Cell Biol 1999 19 6085 6097 10454556 Asada S Choi Y Uesugi M A gene-expression inhibitor that targets an alpha-helix-mediated protein interaction J Am Chem Soc 2003 125 4992 4993 12708845 Bledsoe RK Montana VG Stanley TB Delves CJ Apolito CJ Crystal structure of the glucocorticoid receptor ligand binding domain reveals a novel mode of receptor dimerization and coactivator recognition Cell 2002 110 93 105 12151000 Brunger AT Adams PD Clore GM DeLano WL Gros P Crystallography & NMR system: A new software suite for macromolecular structure determination Acta Crystallogr D Biol Crystallogr 1998 54 905 921 9757107 Chang C Norris JD Gron H Paige LA Hamilton PT Dissection of the LXXLL nuclear receptor-coactivator interaction motif using combinatorial peptide libraries: Discovery of peptide antagonists of estrogen receptors alpha and beta Mol Cell Biol 1999 19 8226 8239 10567548 Culig Z Klocker H Bartsch G Hobisch A Androgen receptors in prostate cancer Endocr Relat Cancer 2002 9 155 170 12237244 Darimont BD Wagner RL Apriletti JW Stallcup MR Kushner PJ Structure and specificity of nuclear receptor-coactivator interactions Genes Dev 1998 12 3343 3356 9808622 DeLano WL The PyMOL molecular graphics system. 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Implications for pathogenic gene mutations J Biol Chem 2000 275 26164 26171 10840043 Needham M Raines S McPheat J Stacey C Ellston J Differential interaction of steroid hormone receptors with LXXLL motifs in SRC-1a depends on residues flanking the motif J Steroid Biochem Mol Biol 2000 72 35 46 10731636 Newmark JR Hardy DO Tonb DC Carter BS Epstein JI Androgen receptor gene mutations in human prostate cancer Proc Natl Acad Sci U S A 1992 89 6319 6323 1631125 Nolte RT Wisely GB Westin S Cobb JE Lambert MH Ligand binding and co-activator assembly of the peroxisome proliferator-activated receptor-gamma Nature 1998 395 137 143 9744270 Norris JD Paige LA Christensen DJ Chang CY Huacani MR Peptide antagonists of the human estrogen receptor Science 1999 285 744 746 10426998 Northrop JP Nguyen D Piplani S Olivan SE Kwan ST Selection of estrogen receptor beta- and thyroid hormone receptor beta-specific coactivator-mimetic peptides using recombinant peptide libraries Mol Endocrinol 2000 14 605 622 10809226 Otwinowski Z Minor W Processing of X-ray diffraction data collected in oscillation mode. 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Methods in enzymology: Macromolecular crystallography, Part A 1997 New York Academic Press 307 326 Paige LA Christensen DJ Gron H Norris JD Gottlin EB Estrogen receptor (ER) modulators each induce distinct conformational changes in ER alpha and ER beta Proc Natl Acad Sci U S A 1999 96 3999 4004 10097152 Quigley CA De Bellis A Marschke KB el-Awady MK Wilson EM Androgen receptor defects: Historical, clinical, and molecular perspectives Endocr Rev 1995 16 271 321 7671849 Sack JS Kish KF Wang C Attar RM Kiefer SE Crystallographic structures of the ligand-binding domains of the androgen receptor and its T877A mutant complexed with the natural agonist dihydrotestosterone Proc Natl Acad Sci U S A 2001 98 4904 4909 11320241 Shiau AK Barstad D Loria PM Cheng L Kushner PJ The structural basis of estrogen receptor/coactivator recognition and the antagonism of this interaction by tamoxifen Cell 1998 95 927 937 9875847 Slagsvold T Kraus I Bentzen T Palvimo J Saatcioglu F Mutational analysis of the androgen receptor AF-2 (activation function 2) core domain reveals functional and mechanistic differences of conserved residues compared with other nuclear receptors Mol Endocrinol 2000 14 1603 1617 11043576 Vassilev LT Vu BT Graves B Carvajal D Podlaski F In vivo activation of the p53 pathway by small-molecule antagonists of MDM2 Science 2004 303 844 848 14704432 Wang Q Lu J Yong EL Ligand- and coactivator-mediated transactivation function (AF2) of the androgen receptor ligand-binding domain is inhibited by the cognate hinge region J Biol Chem 2001 276 7493 7499 11102454 Warnmark A Almlof T Leers J Gustafsson JA Treuter E Differential recruitment of the mammalian mediator subunit TRAP220 by estrogen receptors ERalpha and ERbeta J Biol Chem 2001 276 23397 23404 11303023 Warnmark A Treuter E Gustafsson JA Hubbard RE Brzozowski AM Interaction of transcriptional intermediary factor 2 nuclear receptor box peptides with the coactivator binding site of estrogen receptor alpha J Biol Chem 2002 277 21862 21868 11937504

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020294Research ArticleBioengineeringBiotechnologyCell BiologyDevelopmentMolecular Biology/Structural BiologyPhysiologyMus (Mouse)Regulation of Muscle Fiber Type and Running Endurance by PPARδ PPARδ Regulates Muscle Fiber and EnduranceWang Yong-Xu 1 Zhang Chun-Li 1 Yu Ruth T 1 Cho Helen K 1 Nelson Michael C 1 2 Bayuga-Ocampo Corinne R 1 Ham Jungyeob 3 Kang Heonjoong 3 Evans Ronald M evans@salk.edu 1 2 1Gene Expression Laboratory, Salk InstituteLa Jolla, CaliforniaUnited States of America2Howard Hughes Medical InstituteLa Jolla, CaliforniaUnited States of America3Marine Biotechnology Laboratory, School of Earth and Environmental SciencesSeoul National University, SeoulKorea10 2004 24 8 2004 24 8 2004 2 10 e29422 3 2004 6 7 2004 Copyright: © 2004 Wang et al.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. Gene Targeting Turns Mice into Long-Distance Runners Skeletal Muscle Fiber Type: Influence on Contractile and Metabolic Properties Endurance exercise training can promote an adaptive muscle fiber transformation and an increase of mitochondrial biogenesis by triggering scripted changes in gene expression. However, no transcription factor has yet been identified that can direct this process. We describe the engineering of a mouse capable of continuous running of up to twice the distance of a wild-type littermate. This was achieved by targeted expression of an activated form of peroxisome proliferator-activated receptor δ (PPARδ) in skeletal muscle, which induces a switch to form increased numbers of type I muscle fibers. Treatment of wild-type mice with PPARδ agonist elicits a similar type I fiber gene expression profile in muscle. Moreover, these genetically generated fibers confer resistance to obesity with improved metabolic profiles, even in the absence of exercise. These results demonstrate that complex physiologic properties such as fatigue, endurance, and running capacity can be molecularly analyzed and manipulated. Engineered expression of the peroxisome proliferator-activated receptor δ in skeletal muscle increases type I muscle fibers allowing the modified mice to run twice the distance of wild-type littermates ==== Body Introduction Skeletal muscle fibers are generally classified as type I (oxidative/slow) or type II (glycolytic/fast) fibers. They display marked differences in respect to contraction, metabolism, and susceptibility to fatigue. Type I fibers are mitochondria-rich and mainly use oxidative metabolism for energy production, which provides a stable and long-lasting supply of ATP, and thus are fatigue-resistant. Type II fibers comprise three subtypes, IIa, IIx, and IIb. Type IIb fibers have the lowest levels of mitochondrial content and oxidative enzymes, rely on glycolytic metabolism as a major energy source, and are susceptible to fatigue, while the oxidative and contraction functions of type IIa and IIx lie between type I and IIb (Booth and Thomason 1991; Berchtold et al. 2000; Olson and Williams 2000). Adult skeletal muscle shows plasticity and can undergo conversion between different fiber types in response to exercise training or modulation of motoneuron activity (Booth and Thomason 1991, Jarvis et al. 1996; Pette 1998; Olson and Williams 2000; Hood 2001). This conversion of muscle fiber from type IIb to type IIa and type I is likely to be mediated by a calcium signaling pathway that involves calcineurin, calmodulin-dependent kinase, and the transcriptional cofactor Peroxisome proliferator-activated receptor-gamma coactivator 1α (PGC-1α) (Naya et al. 2000; Olson and Williams 2000; Lin et al. 2002; Wu et al. 2002). However, the targeted transcriptional factors directly responsible for reprogramming the fiber-specific contractile and metabolic genes remain to be identified. Muscle fiber specification appears to be associated with obesity and diabetes. For instance, rodents that gain the most weight on high-fat diets possess fewer type I fibers (Abou et al. 1992). In obese patients, skeletal muscle has been observed to have reduced oxidative capacity, increased glycolytic capacity, and a decreased percentage of type I fibers (Hickey et al. 1995; Tanner et al. 2002). Similar observations have been made in type 2 diabetic patients (Lillioja et al. 1987; Hickey et al. 1995). Recently, it has been shown that increasing oxidative fibers can lead to improved insulin action and reduced adipocyte size (Luquet et al. 2003; Ryder et al. 2003). We have previously established that peroxisome proliferator-activated receptor (PPAR) δ is a major transcriptional regulator of fat burning in adipose tissue through activation of enzymes associated with long-chain fatty-acid β-oxidation (Wang et al. 2003). Although PPARδ is the predominant PPAR isoform present in skeletal muscle, its in vivo function has not been determined. Our current study uncovers PPARδ as the first transcription factor able to drive the formation of functional type I muscle fibers, whose activation entrains complex pathways both enhancing physical performance and creating a state of obesity resistance. Results Activation of PPARδ Leads to Muscle Fiber Transformation A role of PPARδ in muscle fiber was suggested by its enhanced expression—at levels 10-fold and 50-fold greater than PPARα and γ isoforms, respectively (unpublished data). An examination of PPARδ in different muscle fibers reveals a significantly higher level in type I muscle (soleus) relative to type II–rich muscle (extensor digitorum longus) or type I and type II mixed muscle (gastrocnemius) (Figure 1A); this expression pattern closely resembles that of PGC-1α (Lin et al. 2002). A similar pattern but with more pronounced differences was found at the protein level (Figure 1B). Figure 1 Expression of Endogenous PPARδ and VP16-PPARδ Transgene in Muscle (A) Pooled RNA isolated from various muscles of five wild-type male C57B6 mice was hybridized with indicated probes. EDL, extensor digitorum longus; Gastro, gastrocnemius. (B) Pooled nuclear proteins (15 μg/lane) isolated from muscles of five wild-type male C57B6 were probed with anti-PPARδ antibody. RNA polymerase II (Pol II) is shown as a loading control. (C) Expression of the VP16-PPARδ transgene in various tissues. 10 μg of total RNA from each tissue was hybridized with a VP16 cDNA probe. Gastrocnemius muscle was used here. (D) Nuclear proteins (15 μg/lane) isolated from gastrocnemius muscle of the transgenic mice (TG) and the wild-type littermates (WT) were probed with indicated antibodies. The upper, nonspecific band that cross-reacted with the anti-PPARδ antibody serves a loading control. To directly assess the role of activation of PPARδ in control of muscle fiber plasticity and mitochondrial biogenesis, we generated mice expressing a transgene in which the 78-amino-acid VP16 activation domain was fused to the N-terminus of full-length PPARδ, under control of the 2.2-kb human α-skeletal actin promoter. In agreement with the previous characterization of this promoter (Brennan and Hardeman 1993; Clapham et al. 2000), the VP16-PPARδ transgene was selectively expressed in skeletal muscle, with 10-fold less in the heart (Figure 1C). Among different types of muscle fibers, the levels of VP16-PPARδ expression appeared to be similar (unpublished data). As shown in Figure 1D for gastrocnemius muscle, VP16-PPARδ fusion protein was produced at a level similar to that of endogenous PPARδ in wild-type littermates. Interestingly, the level of endogenous muscle PPARδ protein in the transgenic mice was much higher than in the control littermates. The substantial increase of endogenous PPARδ may have been caused by a switch to type I fiber (see below), which intrinsically expresses higher levels of PPARδ (Figure 1A and 1B). Type I muscle can be readily distinguished from type II or mixed muscle by its red color, because of its high concentration of myoglobin, a protein typically expressed in oxidative muscle fibers. We found that muscles in the transgenic mice appeared redder (Figure 2A), which is particularly evident in the mixed type I/II fibers of the hindlimb (Figure 2B). Indeed, metachromatic staining revealed a substantial muscle fiber transformation (Figure 2C). In gastrocnemius muscle, we estimated that there was a 2-fold increase of type I fibers. A diagnostic component of oxidative fibers is their high myoglobin and mitochondrial content, which is supported by the mRNA analysis shown in Figure 3A. In addition to myoglobin, mitochondrial components for electron transfer (cytochrome c and cytochrome c oxidase [COX] II and IV) and fatty-acid β-oxidation enzymes were elevated (Figure 3A; unpublished data). These effects appear to be direct consequences of PPARδ activation, as levels of PGC-1α, a coactivator involved in muscle fiber switch and mitochondrial biogenesis (Wu et al. 1999; Lehman et al. 2000; Lin et al. 2002), remained unchanged. Southern blot analysis detected a substantially higher copy number of the mitochondrial genome–encoded COXII DNA in the transgenic mice (Figure 3B). Mitochondrial DNA was increased 2.3-fold in gastrocnemius muscle of the transgenic mice (Figure 3C). These results reveal a marked stimulation of mitochondrial biogenesis and further support the idea that there is a muscle fiber switch. This conclusion was also confirmed by Western blot analysis. As shown in Figure 3D, the characteristic type I fiber proteins, such as myoglobin and cytochrome c and b, were significantly increased. More importantly, the specialized contraction protein troponin I (slow) of type I fiber was robustly induced; this was accompanied by a marked reduction of the specialized contraction protein troponin I (fast) of type II fiber, indicating a high degree of fiber transformation. We next examined whether acute activation of endogenous PPARδ would induce similar target genes. In agreement with the chronic effects in the transgenic mice, we found that, after treatment of wild-type C57B6J mice with the PPARδ-specific agonist GW501516 for only 10 d, genes for slow fiber contractile proteins, mitochondrial biogenesis, and β-oxidation were all upregulated (Figure 3E). This indicates that rapid, systematic, and coordinated changes of muscle fiber properties toward type I can be achieved by activation of the endogenous PPARδ pathway. Figure 2 Increased Oxidative Type I Fibers in the Transgenic Mice (A and B) Muscles in transgenic mice (TG) are redder than those in wild-type mice (WT). (C) Metachromatic staining of the type II plantaris muscle. Type I fibers are stained dark blue. Figure 3 Activation of PPARδ Induces Genes Typical for Type I Fibers and Promotes Mitochondrial Biogenesis (A) Total RNA (10 μg/lane) prepared from gastrocnemius muscle of transgenic (TG) and wild-type (WT) littermates was probed with indicated probes. The fold increase of induction of each gene is shown. (B) Total genomic DNA (10 μg/lane) prepared from gastrocnemius muscle was digested with Nco1 and subjected to Southern analysis with COXII (mitochondrial genome–encoded) and MCIP1 (nuclear genome–encoded) DNA probes. (C) Equal amounts of gastrocnemius muscle were collected from both transgenic mice and control littermates. Total mitochondrial DNA was isolated and separated on 1% agarose gel. The relative abundance of mitochondrial DNA in transgenic and wild-type mice is presented. (D) Western blot analysis of muscle fiber markers and mitochondrial components. Each lane was loaded with 80 μg of total gastrocnemius muscle extracts. (E) Wild-type C57B6 mice were treated with vehicle or PPARδ agonist GW501516 for 10 d. Total RNA (10 μg/lane) prepared from the gastrocnemius muscle was probed with indicated probes. Muscle Fiber Switch by PPARδ Protects Against Obesity A number of previous studies have shown that obese individuals have fewer oxidative fibers, implying that the presence of oxidative fibers alone may play a part in obesity resistance. To test this possibility, we fed the transgenic mice and their wild-type littermates with a high-fat diet for 97 d. Although the initial body weights of the two groups were very similar, the transgenic mice had gained less than 50% at day 47, and only one-third at day 97, of the weight gained by the wild-type animals (Figure 4A). The transgenic mice displayed significantly higher oxygen consumption on the high-fat diet than the control littermates (unpublished data). By the end of this experiment, the control littermates became obese, whereas the transgenic mice still maintained a normal body weight and fat mass composition (Figure 4A). A histological analysis of inguinal fat pad revealed a much smaller cell size in the transgenic mice (Figure 4B), due to the increased muscle oxidative capacity. While there was no significant difference in intramuscular glycogen content, the triglyceride content was much less in the transgenic mice (Figure 4C and 4D), which may explain their improved glucose tolerance (Figure 4E). We also placed wild-type C57BJ6 mice on the high-fat diet and treated them with either vehicle or the PPARδ agonist GW501516 for 2 mo. GW501516 produced a sustained induction of genes for type I muscle fibers; this, at least in part, resulted in an only 30% gain in body weight, a dramatically reduced fat mass accumulation, and improved glucose tolerance, compared to the vehicle-treated group (Figure 5). Thus, muscle fiber conversion by stimulation with the PPARδ agonist or the activated transgene has a protective role against obesity. Figure 4 Resistance to High-Fat-Induced Obesity in the Transgenic Mice (A) Seven-week-old transgenic (TG) and wild-type (WT) littermates (n = 5–6 for each group) were fed with a high-fat diet for 97 d. Left panel shows net body weight gain, which was calculated for individual mice and then averaged. Right panel shows the body weights before (Day 0) and after (Day 97) high-fat feeding. (B) Histology of inguinal fat pad in the transgenic and wild-type littermates under a high-fat diet for 2 mo. (C and D) Intramuscular glycogen content (C) and triglyceride content (D) of mice in (A) after high-fat feeding (n = 6). (E) Glucose tolerance test. Mice in (A) after high-fat feeding were fasted for 6 h and then injected with glucose at a concentration of 1g/kg body weight. Then blood glucose levels were measured periodically over 2 h (n = 6). Figure 5 PPARδ Agonists Counteract Obesity Induced by High-Fat Diet (A) Eleven-week-old wild-type C57B6 mice were fed a high-fat diet in combination with vehicle or GW501516 for 57 d. Total RNA (10 μg/lane) prepared from the gastrocnemius muscle was probed with indicated probes. (B) Net body weight gain for mice in (A) after treatment was calculated for individual mice and averaged. Initial body weights were 28.54 ± 1.04 g for vehicle group (n = 5) and 28.86 ± 0.80 g for GW501516 group (n = 5). (C) Various tissue weights for mice in (A) after treatment. ifat, inguinal fat; rdfat, reproductive fat; retrofat, retroperitoneal fat. (D) Glucose tolerance test. Mice in (A) after treatment were fasted for 6 h and then injected with glucose at a concentration of 1g/kg body weight. Blood glucose levels were then measured periodically over 2 h. Activation of PPARδ Enhances Physical Performance Muscle oxidative capacity is a crucial factor for determining endurance and fatigue. Indeed, type I fibers adaptively generated through exercise training are considered to be fatigue resistant. However, whether the type I fibers generated molecularly via PPARδ expression can contribute to enhanced performance in the absence of previous training is unclear. In fact, the consequence of genetically induced fiber switch on running capacity has to our knowledge never been evaluated. We thus compared exercise performance between untrained, body-weight-matched transgenic and wild-type littermates. Mice were run on oxygen-infused, enclosed treadmills until exhaustion. Strikingly, the running time and distance the transgenic mice were able to sustain were increased by 67% and 92%, respectively (Figure 6A; also see Videos S1 and S2). The transgenic mice ran about 1 h longer than the controls, which translates to nearly a kilometer further. No significant differences in muscle mass (unpublished data) and daily activity (total counts of activity per hour: 1618 ± 209 for transgenic versus 1987 ± 301 for wild-type, p > 0.35, n = 4) were observed between the transgenic and control mice. Thus, the remarkable increase in endurance is the physiologic manifestation of muscle fiber transformation. This suggests that genetically directed muscle fiber switch is physiologically and functionally relevant. In addition, we looked at what effect the absence of PPARδ function has on exercise endurance. In the treadmill test, the PPARδ-null mice could sustain only 38% of the running time and 34% of the distance of their age- and weight-matched wild-type counterparts (Figure 6B). These results further support a role for PPARδ in enhancement of physical performance. Figure 6 PPARδ Regulates Exercise Endurance (A) Enhanced exercise performance in the transgenic mice. Fourteen-week-old male transgenic and wild-type littermates with similar body weights (n = 4 for each group) were subjected to a forced treadmill exercise test. (B) Compromised exercise performance in PPARδ-null mice. Two-month-old male PPARδ-null mice and wild-type controls with similar body weights (n = 6 for each group) were subjected to a forced treadmill exercise test. (C) Functions of PPARδ in skeletal muscle. Discussion Our data reveal that a PPARδ-mediated transcriptional pathway can regulate muscle fiber specification, enabling the generation of a strain of mice with a “long-distance running” phenotype. We show that targeted expression of an activated form of PPARδ produces profound and coordinated increases in oxidation enzymes, mitochondrial biogenesis, and production of specialized type I fiber contractile proteins—the three hallmarks for muscle fiber type switching (Figure 6C). While induction of muscle oxidation enzymes by PPARδ has been seen both in vivo and in vitro (Muoio et al. 2002; Dressel et al. 2003; Luquet et al. 2003; Tanaka et al. 2003; Wang et al. 2003), its effects shown here on muscle fiber switching are unexpected. These progressive changes in oxidative capacity in conjunction with eventual changes in type I muscle fiber lead to a dramatically improved exercise profile and protection against obesity. This does not solely depend on achieving a directed muscle fiber type switch but also requires all the associated changes in neural innervation, motor neuron function, and peripheral metabolic adaptation to enable a new integrated physiological response. Accordingly, activation of muscle PPARδ essentially recapitulates the effects of exercise training even in the absence of training itself. To our knowledge, this has not been directly described for any other transcriptional factor. The muscle phenotypes described here are remarkably similar to those of transgenic mice expressing either calcineurin, calmodulin-dependent kinase, or PGC-1α (Naya et al. 2000; Lin et al. 2002; Wu et al. 2002), indicating that PPARδ could be one of the hypothetical downstream transcription factors of these pathways. It is important to note that, from our ligand and gain-of-function transgenic studies, PPARδ needs to be activated in order to direct the muscle fiber switch. Indeed, in a recent report by Luquet et al. (2003), simple overexpression of wild-type PPARδ in muscle was found not to be sufficient to promote a fiber switch or obesity resistance, although certain oxidation enzymes were increased. This supports the model in Figure 6C that the activating signal or ligand, but not the receptor, is limiting. Thus, PPARδ activation, rather than merely an increase of PPARδ levels, is an essential element for fiber switching and its associated functional manifestations. How might endogenous PPARδ become activated naturally by exercise training? First, it is possible that exercise generates or increases endogenous ligands for PPARδ as tissues are undergoing substantial increases in fatty-acid internalization and burning. Fatty acids and their metabolites can activate PPARδ. A second model is that exercise may induce expression of PGC-1α (Goto et al. 2000) and thereby activate PPARδ. This is consistent with previous work in which we have shown that PGC-1α physically associates with PPARδ in muscle tissue and can powerfully activate it even in the absence of ligands (Wang et al. 2003). Alternatively, PPARδ may be activated by a distal upstream signaling component such as a kinase cascade. Further dissecting the interactions between PPARδ and its regulatory components will be necessary to fully understand the molecular basis of muscle fiber determination pertinent to exercise training. Skeletal muscle is a major site to regulate whole-body fatty-acid and glucose metabolism. We show that mice with increased oxidative fibers are resistant to high-fat-induced obesity and glucose intolerance. Moreover, ligand studies provide compelling evidence that activation of endogenous PPARδ can produce similar effects. Might PPARδ have any beneficial effects on glucose metabolism in the lean condition? This has not been explored; however, insulin resistance in the elderly is confined mostly to skeletal muscle and may be due to reduction of mitochondrial number and/or function (Petersen et al. 2003). The ability of PPARδ to stimulate mitochondrial biogenesis and oxidative function suggests that PPARδ could be important for control of insulin resistance during normal aging. Together, these data indicate that PPARδ and its ligands comprise a key molecular switch to regulate muscle fiber specification, obesity resistance, insulin sensitivity, and, most surprisingly, physical endurance. This work demonstrates that complex physiologic properties such as fatigue, endurance, and running capacity can be genetically manipulated. Materials and Methods Animals. The transactivation domain (78 amino acid residues, corresponding to residues 413–490) of VP16 was fused in frame with the N-terminus of mouse PPARδ. The VP16-PPARδ fusion cDNA was placed downstream of the human α-skeletal actin promoter (Brennan and Hardeman 1993), and upstream of the SV40 intron/poly(A) sequence. The transgene was purified and injected into C57BL/6J × CBA F1 zygotes. Transgenic mice were backcrossed with C57BL/6J for two generations. Wild-type littermates were used as controls throughout the study. On normal chow diet, the transgenic mice and control littermates used here had similar body weights. PPARδ-null mice were previously generated (Barak et al. 2002). Mice were fed either a standard chow with 4% (w/w) fat content (Harlan Teklad, Harlan, Indianapolis, Indiana, United States) or a high-fat diet containing 35% (w/w) fat content (product F3282, Bioserv, Frenchtown, New Jersey, United States) as indicated. For ligand experiments, we synthesized the GW501516 compound and mice were orally gavaged daily (10 mg/kg or vehicle alone). Gene expression analysis and physiological studies Mouse EST clones were obtained from ATCC (Manassas, Virginia, United States), verified by sequencing, and used as Northern probes. Antibodies were obtained from Santa Cruz Biotechnology (Santa Cruz, California, United States). Total muscle protein extracts (Lin et al. 2002) and nuclear proteins (Wang et al. 2003) were prepared as described. Prior to the exercise performance test, the mice were accustomed to the treadmill (Columbus Instruments, Columbus, Ohio, United States) with a 5-min run at 7 m/min once per day for 2 d. The exercise test regimen was 10 m/min for the first 60 min, followed by 1 m/min increment increases at 15-min intervals. Exhaustion was defined when mice were unable to avoid repetitive electrical shocks. Muscle fiber typing and mitochondrial DNA isolation Muscle fiber typing was essentially performed using metachromatic dye–ATPase methods as described (Ogilvie and Feeback 1990). Muscle mitochondria were isolated (Scholte et al. 1997). Mitochondrial DNA was prepared and analyzed on 1% agarose gel. Statistical analysis Number of mice for each group used in experiments is indicated in figure legends. Values are presented as mean ± SEM. A two-tailed Student's t test was used to calculate p-values. Supporting Information Video S1 Beginning of Running Test This video shows the exercise performance of a representative of the transgenic mice (right chamber) and a representative of wild-type control littermates (left chamber) on the treadmill 15 min into the exercise challenge. (52.4 MB MOV). Click here for additional data file. Video S2 Running Test 90 Min Later This video shows the exercise performance of a representative of the transgenic mice (right chamber) and a representative of wild-type control littermates (left chamber) on the treadmill 90 min into the exercise challenge. (41.7 MB MOV). Click here for additional data file. We thank Dr. M. Downes for providing the α-skeletal actin promoter; Dr. G. D. Barish for comments on the manuscript; M.A. Lawrence for histology; Dr. S. Pfaff for the use of microscopes and photographic equipment; M. Lieberman and K.L. Schnoeker for photography; J.M. Shelton for advice on fiber staining; and E. Stevens and E. Ong for administrative assistance. YXW was supported by a postdoctoral fellowship from California Tobacco-Related Disease Research Program. JH was supported by the BK21 program, Ministry of Education, Korea. HK was supported by grant M1–0311-00–0145 from the Molecular and Cellular BioDiscovery Research Program, Ministry of Science and Technology, Korea. RME is an Investigator of the Howard Hughes Medical Institute at the Salk Institute for Biological Studies and March of Dimes Chair in Molecular and Developmental Biology. This work was supported by the Howard Hughes Medical Institute and the Hillblom Foundation. Conflicts of interest. The authors have declared that no conflicts of interest exist. Author contributions. YXW and RME conceived and designed the experiments. YXW, CLZ, RTY, MCN, and CRBO performed the experiments. YXW, CLZ, and RME analyzed the data. HKC, JH, and HK contributed reagents/materials/analysis tools. YXW and RME wrote the paper. Academic Editor: Steve O'Rahilly, University of Cambridge Citation: Wang YX, Zhang CL, Yu RT, Cho HK, Nelson MC, et al. (2004) Regulation of muscle fiber type and running endurance by PPARδ. PLoS Biol 2(10): e294. Abbreviations COXcytochrome c oxidase mCPT1muscle carnitine palmitoyltransferase-1 PGC-1αPeroxisome proliferator-activated receptor-gamma coactivator 1α PPARperoxisome proliferator-activated receptor UCPuncoupling protein ==== Refs References Abou MJ Yakubu F Lin D Peters JC Atkinson JB Skeletal muscle composition in dietary obesity-susceptible and dietary obesity-resistant rats Am J Physiol 1992 262 R684 R688 1566936 Barak Y Liao D He W Ong ES Nelson MC Effects of peroxisome proliferator-activated receptor δ on placentation, adiposity, and colorectal cancer Proc Natl Acad Sci U S A 2002 99 303 308 11756685 Berchtold MW Brinkmeier H Muntener M Calcium ion in skeletal muscle: Its crucial role for muscle function, plasticity, and disease Physiol Rev 2000 80 1215 1265 10893434 Booth FW Thomason DB Molecular and cellular adaptation of muscle in response to exercise: Perspectives of various models Physiol Rev 1991 71 541 585 2006222 Brennan KJ Hardeman EC Quantitative analysis of the human alpha-skeletal actin gene in transgenic mice J Biol Chem 1993 268 719 725 7678010 Clapham JC Arch JR Chapman H Haynes A Lister C Mice overexpressing human uncoupling protein-3 in skeletal muscle are hyperphagic and lean Nature 2000 406 415 418 10935638 Dressel U Allen TL Pippal JB Rohde PR Lau P The peroxisome proliferator-activated receptor beta/delta agonist, GW501516, regulates the expression of genes involved in lipid catabolism and energy uncoupling in skeletal muscle cells Mol Endocrinol 2003 17 2477 2493 14525954 Goto M Terada S Kato M Katoh M Yokozeki T cDNA cloning and mRNA analysis of PGC-1 in epitrochlearis muscle in swimming-exercised rats Biochem Biophys Res Commun 2000 274 350 354 10913342 Hickey MS Carey JO Azevedo JL Houmard JA Pories WJ Skeletal muscle fiber composition is related to adiposity and in vitro glucose transport rate in humans Am J Physiol 1995 268 E453 E457 7900793 Hood DA Contractile activity-induced mitochondrial biogenesis in skeletal muscle J Appl Physiol 2001 90 1137 1157 11181630 Jarvis JC Mokrusch T Kwende MM Sutherland H Salmons S Fast-to-slow transformation in stimulated rat muscle Muscle Nerve 1996 19 1469 1475 8874405 Lehman JJ Barger PM Kovacs A Saffitz JE Medeiros DM Peroxisome proliferator-activated receptor coactivator-1 promotes cardiac mitochondrial biogenesis J Clin Invest 2000 106 847 856 11018072 Lillioja S Young AA Culter CL Ivy JL Abbott WG Skeletal muscle capillary density and fiber type are possible determinants of in vivo insulin resistance in man J Clin Invest 1987 80 415 424 3301899 Lin J Wu H Tarr PT Zhang CY Wu Z Transcriptional co-activator PGC-1 drives the formation of slow-twitch muscle fibres Nature 2002 418 797 801 12181572 Luquet S Lopez-Soriano J Holst D Fredenrich A Melki J Peroxisome proliferator-activated receptor delta controls muscle development and oxidative capability FASEB J 2003 17 2299 2301 14525942 Muoio DM MacLean PS Lang DB Li S Houmard JA Fatty acid homeostasis and induction of lipid regulatory genes in skeletal muscles of peroxisome proliferator-activated receptor (PPAR) alpha knock-out mice: Evidence for compensatory regulation by PPAR delta J Biol Chem 2002 277 26089 26097 12118038 Naya FJ Mercer B Shelton J Richardson JA Williams RS Stimulation of slow skeletal muscle fibre gene expression by calcineurin in vivo J Biol Chem 2000 275 4545 4548 10671477 Ogilvie RW Feeback DL A metachromatic dye-ATPase method for the simultaneous identification of skeletal muscle fibre types I, IIA, IIB and IIC Stain Technol 1990 65 231 241 1703671 Olson EN Williams RS Remodeling muscles with calcineurin Bioessays 2000 22 510 519 10842305 Petersen KF Befroy D Dufour S Dziura J Ariyan C Mitochondrial dysfunction in the elderly: Possible role in insulin resistance Science 2003 300 1140 1142 12750520 Pette D Training effects on the contractile apparatus Acta Physiol Scand 1998 162 367 376 9578383 Ryder JW Bassel-Duby R Olson EN Zierath JR Skeletal muscle reprogramming by activation of calcineurin improves insulin action on metabolic pathways J Biol Chem 2003 278 44298 44304 12941959 Scholte HR Yu Y Ross JD Oosterkamp II Boonman AM Rapid isolation of muscle and heart mitochondria, the lability of oxidative phosphorylation and attempts to stabilize the process in vitro by taurine, carnitine and other compounds Mol Cell Biochem 1997 174 61 66 9309666 Tanaka T Yamamoto J Iwasaki S Asaba H Hamura H Activation of peroxisome proliferator-activated receptor beta induces fatty acid beta-oxidation in skeletal muscle and attenuates metabolic syndrome Proc Natl Acad Sci U S A 2003 100 15924 15929 14676330 Tanner CJ Barakat HA Dohm GL Pories WJ MacDonald KG Muscle fiber type is associated with obesity and weight loss Am J Physiol Endocrinol Metab 2002 282 E1191 E1196 12006347 Wang YX Lee CH Tiep S Yu RT Ham J Peroxisome-proliferator-activated receptor delta activates fat metabolism to prevent obesity Cell 2003 113 159 170 12705865 Wu H Kanatous SB Thurmond FA Gallardo T Isotani E Regulation of mitochondrial biogenesis in skeletal muscle by CaMK Science 2002 296 349 352 11951046 Wu Z Puigserver P Andersson U Zhang C Adelmant G Mechanisms controlling mitochondrial biogenesis and respiration through the thermogenic coactivator PGC-1 Cell 1999 98 115 124 10412986

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PMC509410

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2021-01-05 08:21:13

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PLoS Biol. 2004 Oct 24; 2(10):e294

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PLoS Biol

10.1371/journal.pbio.0020294

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020299SynopsisGenetics/Genomics/Gene TherapyMolecular Biology/Structural BiologyPlant SciencePlantsArabidopsisHormones Act in Concert to Direct Plant Growth Synopsis9 2004 24 8 2004 24 8 2004 2 9 e299Copyright: © 2004 Public Library of Science.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. Interdependency of Brassinosteroid and Auxin Signaling in Arabidopsis ==== Body Anyone who thinks plants are passive inhabitants of their environment has never seen time-lapse footage of a seedling bursting from its protective shell or a climbing vine coiling around a tree. Such films dramatize a fundamental fact of plant life: survival depends on responding to environmental cues. Shoots grow toward light and against gravity. Stems and roots curl around obstacles that block their paths. In plants, environmental cues trigger hormonal changes that in turn regulate cells' shapes and proliferation. In this way, subtle changes in the environment affect plant growth. Auxin, the first known plant hormone, spurs growth and shapes growth patterns in nearly every plant tissue throughout a plant's lifecycle. Brassinosteroids—a class of hormones chemically similar to animal steroids like testosterone—are linked to many of the same processes as auxin. Emerging leaf tips (yellow arrow) and hypocotyl (orange arrows) of an Arabidopsis mutant Early physiological and molecular experiments gave conflicting evidence about whether auxin and brassinosteroids had similar effects. For many years, biologists believed that these hormones acted through independent signal transduction pathways—chains of molecules that relay stimuli and elicit cellular responses, such as gene expression. But in the last few years, microarray studies, which can measure the transcription of thousands of genes simultaneously, showed that auxin and brassinosteroids do regulate expression of several genes in common. In this issue of PLoS Biology, Jennifer Nemhauser et al. assay the entire genome of Arabidopsis thaliana, a favorite for plant genetics studies, for effects of auxin and brassinosteroids. The group's microarray analyses show that these hormones affect transcription of about 80 genes in common—including many known players in the hormones' signal transduction pathways. To see how this regulation could occur, the research team looked at the genes turned on by both hormones to find common promoter sequences—regions of the genome that do not code for protein but instead help regulate gene transcription. They used a new computational approach to tease out promoter regions that auxin and brassinosteroid pathways both act upon, showing how these hormones have overlapping effects on gene transcription. The group also compared the effects of auxin and brassinosteroids on seedlings' stem growth and gene expression in a variety of mutant Arabidopsis lines. They showed that auxin and brassinosteroids greatly enhance each other's effects on stem growth, demonstrating that the interaction of these hormones is important for normal plant development. Mutants with a disabled auxin pathway don't respond normally to brassinosteroids, and vice versa. Also, mutants with abnormally high levels of auxin have a reduced number of genes that respond to brassinosteroids. Thus, these hormones act through overlapping, interdependent pathways—but they don't regulate each other directly. Instead, the researchers suggest, the pathways likely converge on the promoters of a few key genes. It's still an open question why plants use these hormones with such redundant effects. Nemhauser speculates that—as is known to be the case in animals—by having dual, interdependent pathways, plants can finely tune how these ubiquitous hormones act in different cells and tissues to shape patterns of growth. By showing clearly that auxin and brassinosteroids act together and how they affect many of the same genes, Nemhauser and colleagues have set the stage for more detailed studies of how these hormones act in specific parts of plants to shape growth.

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PMC509411

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2021-01-05 08:21:13

no

PLoS Biol. 2004 Sep 24; 2(9):e299

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PLoS Biol

10.1371/journal.pbio.0020299

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020300SynopsisCell BiologyHomo (Human)A Case for a Functional Actin Network in the Nucleus Synopsis9 2004 24 8 2004 24 8 2004 2 9 e300Copyright: © 2004 Public Library of Science.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. Emerin Caps the Pointed End of Actin Filaments: Evidence for an Actin Cortical Network at the Nuclear Inner Membrane ==== Body In June, muscular dystrophy patients lost one of their most passionate advocates to a rare form of this degenerative neuromuscular disorder—thirteen-year-old Mattie Stepanek. In his short life, Stepanek wrote five volumes of inspirational poetry, topping the New York Times bestseller list and winning accolades from the likes of Jimmy Carter. A wide range of inherited disorders falls under the rubric of muscular dystrophy, but all involve some form of progressive muscle wasting. Stepanek's condition impaired nearly all of his body's functions, but other more common forms, including Emery-Dreifuss muscular dystrophy (EDMD), selectively target skeletal muscle and induce cardiac abnormalities. EDMD is caused by mutations in either of two genes: one encodes lamin A, a structural protein associated with the nucleus, and the other encodes a nuclear membrane protein called emerin. Lamins, a major component of the structural network that supports the nuclear envelope, help the nuclear envelope maintain structural integrity and absorb mechanical stress without rupturing. (Structures that support the nucleus and regulate molecular traffic between the cytoplasm and nucleus are collectively referred to as the nuclear envelope. They include the inner and outer nuclear membranes, the nuclear pore complexes, and a network of lamin filaments, called the nuclear lamina, near the inner membrane.) Emerin binds to proteins that regulate gene transcription. Emerin and lamins are found in most cell types, yet EDMD attacks only skeletal muscles, major tendons, and the cells that regulate cardiac muscle contraction. So where does this tissue specificity come from? One theory suggests that emerin selectively targets proteins that specifically regulate gene expression in EDMD-affected tissues. Another theory proposes that emerin provides structural support to the nuclear envelope and that emerin mutations are most destructive in tissues subjected to mechanical stress—like skeletal muscle and tendons. Current evidence supports both models. Recent studies suggest that emerin forms complexes with actin—the mother of all structural proteins. Actin proteins can join together (polymerize) to form a variety of filaments. However, given longstanding doubts that actin exists in the nucleus, let alone functions there, researchers were unsure what the findings might indicate. Now James Holaska, Amy Kowalski, and Katherine Wilson propose that emerin not only functions as a structural protein in the nucleus but that it does so by interacting with actin. Interactions of structural proteins at the nuclear membrane Evidence that emerin and lamin A can form multiprotein complexes comes primarily from experiments in test tubes. To get a sense of the physiological significance of these findings, Wilson and colleagues purified emerin-binding proteins from the nuclei of living cells. They found that emerin binds to polymerized actin and, in fact, appears to stimulate polymerization. By binding and “capping” a specific end of the actin filament, emerin prevents filament de-polymerization (disassembly), effectively increasing the rate of actin polymerization by four- to twelve-fold. The authors propose that emerin “promotes the formation of a nuclear actin cortical network,” which could serve to anchor membrane proteins and lamin filaments to the inner nuclear membrane and thus enhance the structural integrity of the nuclear envelope. Whether emerin also interconnects the lamin and actin filament networks at the nuclear envelope—which could significantly reinforce its mechanical strength—will have to await further study. Muscle contraction places enormous stress on cell membranes. These results suggest that actin-based networks, in addition to lamin networks, support the structural integrity of the nuclear envelope. Defects in proteins involved in either network could compromise nuclear structure, which could in turn disrupt the cell's gene expression program, for example, or rupture the cell membrane, killing the cell. Subtle defects in proteins important for muscle cell integrity can cause several forms of muscular dystrophy. Now it appears that emerin defects could cause EDMD in part by compromising the mechanical integrity of nuclei in muscle cells and tendons.

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PMC509412

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2021-01-05 08:21:14

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PLoS Biol. 2004 Sep 24; 2(9):e300

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PLoS Biol

10.1371/journal.pbio.0020300

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020305SynopsisMolecular Biology/Structural BiologyHomo (Human)The Structural Basis of a Prostate Cancer Protein's Unique Selectivity Synopsis9 2004 24 8 2004 24 8 2004 2 9 e305Copyright: © 2004 Public Library of Science.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. Recognition and Accommodation at the Androgen Receptor Coactivator Binding Interface ==== Body One of the major players in prostate cancer is a nuclear signaling protein called the androgen receptor. Prostate growth and development is regulated by androgen hormones (like testosterone) that activate the androgen receptor. When an androgen binds the receptor, the receptor binds other proteins, called coactivators, to activate genes controlling cell growth, survival, and differentiation. Unlike other receptors that function in the nucleus, the androgen receptor normally shuns coactivators with a leucine-rich binding domain in favor of those with “aromatic” domains. (Aromatic amino acids are defined by their ring structure.) But during prostate cancer, the receptor interacts with both coactivator types, to promote disease progression. The secret to a protein's binding preference rests in the underlying sequence of its amino acids, which determines the protein's structure and ultimate behavior. Robert Fletterick and colleagues set out to identify the “full repertoire” of amino acid sequences that might conceivably consort with the androgen receptor. Their findings help explain the unusual behavior of the androgen receptor during prostate cancer progression—a first step toward developing new anticancer therapies. Treatment for hormone-dependent prostate cancers focuses primarily on reducing androgen levels by using chemicals that compete for androgen receptor docking rights in the hormone-binding pocket of the ligand-binding domain, or LBD. (A ligand is a molecule, like the androgen hormone, that binds to a receptor.) But cancer cells eventually circumvent these chemical assaults through increased levels of either androgen receptors or their coactivators, or through mutations that make androgen receptors immune to chemotherapy. That's why Fletterick and colleagues turned their attentions to the receptor's consorts. Since targeting the hormone-binding pocket of the receptor offers limited benefits, a better strategy might involve disrupting associations with the receptor's coactivators. Dozens of proteins interact with different regions of the androgen receptor, but the details of these interactions were not known. When a hormone binds to the LBD of other nuclear receptors, it triggers a conformational change that creates a binding surface called AF-2 for the leucine-rich domains of the coactivator proteins. It was not clear, however, how the AF-2 region of the androgen receptor distinguishes between aromatic and leucine-rich domains. To characterize the receptor's binding selectivity, Fletterick and colleagues tested 20 billion peptides, or protein fragments, to see whether they interacted with the LBD region of a hormone-bound androgen receptor. As expected, most of the peptides that associated with the LBD domain were aromatic. And they interacted with the same region that naturally occurring coactivators bind to. Next, Fletterick and colleagues determined the three-dimensional structure of both the receptor bound to just the androgen hormone and the androgen–receptor pair bound to a subset of seven peptides. The different structures showed that the androgen receptor uses a single surface to bind both leucine-rich and aromatic peptides; when the aromatic peptides have bulky appendages, the receptor's AF-2 domain reorganizes to accommodate them. Surface complimentarity of hydrophobic motifs The various structures and binding affinities for the different receptor–peptide complexes described here show how the receptor can interact with a diverse array of proteins. The androgen receptor, unlike other nuclear receptors, has specific amino acid sequences that better support aromatic peptide binding. Interestingly, mutations in one of these amino acid sequences have been found in prostate cancer. Altogether, the authors conclude, the unique properties of the receptor's AF-2 surface make it “an attractive target for pharmaceutical design.” Drugs that directly interfere with coactivator binding, they explain, are likely to inhibit androgen receptor activity. Here, the authors recommend novel sites on the receptor as promising targets for androgen-receptor-specific inhibitors.

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PMC509413

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2021-01-05 08:27:51

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PLoS Biol. 2004 Sep 24; 2(9):e305

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PLoS Biol

10.1371/journal.pbio.0020305

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020314SynopsisBiophysicsNeuroscienceCatThe Case of the Noisy Neurons Synopsis9 2004 24 8 2004 24 8 2004 2 9 e314Copyright: © 2004 Public Library of Science.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. Amplification of Trial-to-Trial Response Variability by Neurons in Visual Cortex ==== Body People are unpredictable. One night you may crave Italian food, but another only Thai will do. One day you might finish a crossword puzzle in record time, and the next not a single clue prompts an answer. Such behavioral variation has been found in laboratory studies, too: a person's ability to find a faint image on a screen varies widely from one viewing to the next. Similarly, when an animal repeatedly receives the same stimulus—for example, a faint image—a neuron in a region of the animal's visual brain might be very active upon one presentation and relatively quiet the next. Across the cerebral cortex—the brain region that integrates the senses and controls voluntary movement—neurons are notorious for their unpredictable behavior. The neurons themselves don't create this noise; when directly stimulated with an electrode multiple times, neurons will give the same response every time. Most neurons, however, receive signals from a host of other neurons. These various signals combine to form a seemingly noisy electrical input, which shows up as fluctuations in the recipient neuron's membrane potential—a difference in electrical charge between the inside and outside of the cell's membrane. Neuron function is intimately tied to the membrane potential, which is usually maintained within a narrow range, called the resting potential. But incoming signals can push the resting potential higher or lower. If the membrane potential rises above a certain threshold, the neuron fires, sending an electrical signal down its length. In this way, the brain relays and processes information. Since the 1960s, neuroscientists trying to account for the cortex's variable responses have pointed to noisy inputs from other parts of the brain as the prime suspect. In this issue of PLoS Biology, Matteo Carandini addresses this longstanding mystery of neuron variability and comes up with a different answer. Carandini simultaneously measured the membrane potentials and firing patterns of individual neurons in the cat visual cortex. He found, surprisingly, that the membrane potentials varied much less than the firing patterns, ruling out noisy inputs as the cause of neurons' noisy outputs. Instead, the neurons amplified noise in the signals they received. Noise and threshold make neurons unpredictable Carandini then used a simple model of neuron behavior to explain why this would occur. He started with a tried-and-true approximation of neuron behavior, called the rectification model: a neuron doesn't fire until its membrane potential rises above a threshold, but once it crosses this threshold, its firing rate is correlated with the strength of incoming signals. Then he added the assumption that the neurons receive signals with some randomness. Given these minimal assumptions, Carandini showed that neurons fed a noisy signal will tend to amplify the noise in the signal. Importantly, his model reproduced a well-known phenomenon: as cortical neurons' average firing rate goes up, their firing rate also becomes more variable—that is, they get noisier. Carandini's model also predicted something new: as the firing rate continues to increase, the firing rate should become more consistent and less noisy—which he calls saturation of variability. Carandini's measurements in cats showed neurons actually behave this way, a key validation of his model. It's not clear whether this amplification of variability is something that helps or hampers the brain. Despite being a nuisance to neuroscientists, such fluctuations could be crucial to how the brain functions, Carandini speculates. Without some variability in their cortex, animals would act like cameras or other simple machines that respond the same way each time to a stimulus. It's advantageous for behavior, and hence brains, to be adaptable. But amplifying noise in a signal seems to run counter to relaying and processing the information in the signal. Carandini suggests that what appears as noise in the experiments are signals from other parts of the cortex—that is, noise is in the eye of the beholder. Now that the source of the variability is clear, neuroscientists can study whether it serves a function in the brain.

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PMC509414

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2021-01-05 08:21:14

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PLoS Biol. 2004 Sep 24; 2(9):e314

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PLoS Biol

10.1371/journal.pbio.0020314

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==== Front PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020322SynopsisBioengineeringBiotechnologyCell BiologyDevelopmentMolecular Biology/Structural BiologyPhysiologyMus (Mouse)Gene Targeting Turns Mice into Long-Distance Runners Synopsis10 2004 24 8 2004 24 8 2004 2 10 e322Copyright: © 2004 Public Library of Science.2004This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. Regulation of Muscle Fiber Type and Running Endurance by PPARδ ==== Body Have you ever noticed that long-distance runners and sprinters seem specially engineered for their sports? One's built for distance, the other speed. The ability to generate quick bursts of power or sustain long periods of exertion depends primarily on your muscle fiber type ratio (muscle cells are called fibers), which depends on your genes. To this extent, elite athletes are born, not made. No matter how hard you train or how many performance-enhancing drugs you take, if you're not blessed with the muscle composition of a sprinter, you're not going to break the 100-meter world record in your lifetime. (In case you'd like to try, that's 9.78 seconds for a man and 10.49 seconds for a woman.) Of course that doesn't prevent those at the highest levels from using the latest performance enhancer to get that extra 1% edge. But wait until trainers hear about the Marathon Mouse. A new study by Ronald Evans and colleagues provides evidence that endurance and running performance can be dramatically enhanced through genetic manipulation. Skeletal muscles come in two basic types: type I, or slow twitch, and type II, or fast twitch. Slow-twitch fibers rely on oxidative (aerobic) metabolism and have abundant mitochondria that generate the stable, long-lasting supplies of adenosine triphosphate, or ATP, needed for long distance. (For more on muscle fiber metabolism, see synopsis titled “A Skeletal Muscle Protein That Regulates Endurance”) Fast-twitch fibers, which produce ATP through anaerobic glycolysis, generate rapid, powerful contractions but fatigue easily. Top-flight sprinters have up to 80% type II fibers while long-distance runners have up to 90% type I fibers. Coach potatoes have about the same percentage of both. Endurance training can enhance the metabolic performance of muscle types, and now it appears that training can also induce conversion between fiber types. Specific changes in gene expression trigger this oxidative fiber transformation, but the transcription factor responsible for engineering this shift was unknown. Evans and colleagues suspected that a nuclear receptor called PPARδ—a major regulator of fat burning in fat tissue that is also prevalent in skeletal muscle—might be involved. To investigate this possibility, the authors genetically engineered mice to express an activated form of the PPARδ protein in skeletal muscle. Type I fibers normally express higher levels of PPARδ than type II fibers, and the transgenic mice showed much higher levels of the protein than their normal littermates. The transgenic mice also had much redder muscles than the controls—type I fibers have high levels of myoglobin, the red-pigmented protein that facilitates the movement of oxygen within muscle—and elevated levels of proteins associated with mitochondrial biogenesis and operation. A final line of evidence indicating a type I fiber switch was the elevated level of specialized type I contractile proteins and decreased level of specialized type II contractile proteins in the transgenic mice. Interestingly, these same results were seen when naturally occurring (endogenous) PPARδ levels were stimulated in the normal mice (with an orally active compound). This suggests that muscle fibers can be transformed into type I endurance fibers by simply activating the endogenous PPARδ pathway. In a weight-conscious world, oxidative fibers are thought to offer resistance against obesity since obese individuals have fewer type I fibers than average-weight individuals. Sure enough, transgenic mice fed a high-fat diet gained far less weight than normal mice fed the same diet, even in the absence of exercise. The transgenic mice had much smaller fat cells, which the authors attribute to enhanced oxidative capacity of the muscle tissue, and improved glucose tolerance. (Obese individuals lose the ability to metabolize glucose, which puts them at risk for diabetes.) But what about performance? Remarkably, the marathon mice ran about an hour longer than controls, showing dramatic improvement in both running time and distance—increases of 67% and 92%, respectively. Altogether, these results show that PPARδ drives the conversion of type I muscle fibers by activating pathways that enhance physical performance and protect against obesity. The finding that endurance and running capacity can be genetically manipulated suggests that muscle tissue is far more adaptable than previously thought. Maybe Olympiads can be made after all—but don't give up on training just yet. A full understanding of the molecular basis of muscle fiber determination, including the interactions between PPARδ and its regulatory components, awaits further study.

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PMC509415

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2021-01-05 08:21:13

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PLoS Biol. 2004 Oct 24; 2(10):e322

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PLoS Biol

10.1371/journal.pbio.0020322

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==== Front BMC Cell BiolBMC Cell Biology1471-2121BioMed Central London 1471-2121-5-281528203510.1186/1471-2121-5-28Research ArticleCalcineurin activation influences muscle phenotype in a muscle-specific fashion Talmadge Robert J 1rjtalmadge@csupomona.eduOtis Jeffrey S 2jotis@pharm.emory.eduRittler Matthew R 2mrittler@vt.eduGarcia Nicole D 1MandNGarcia@aol.comSpencer Shelly R 1srspencer2@hotmail.comLees Simon J 2leessj@missouri.eduNaya Francisco J 3fnaya@bu.edu1 Department of Biological Sciences, California State Polytechnic University, Pomona, CA 91768, USA2 Department of Human Nutrition, Foods and Exercise, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA3 Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA2004 28 7 2004 5 28 28 10 5 2004 28 7 2004 Copyright © 2004 Talmadge et al; licensee BioMed Central Ltd.2004Talmadge et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background The calcium activated protein phosphatase 2B, also known as calcineurin, has been implicated as a cell signaling molecule involved with transduction of physiological signals (free cytosolic Ca2+) into molecular signals that influence the expression of phenotype-specific genes in skeletal muscle. In the present study we address the role of calcineurin in mediating adaptations in myosin heavy chain (MHC) isoform expression and muscle mass using 3-month old wild-type (WT) and transgenic mice displaying high-level expression of a constitutively active form of calcineurin (MCK-CN* mice). Results Slow muscles, e.g., soleus, were significantly larger (by ~24%), whereas fast muscles, e.g., medial gastrocnemius (MG) and tibialis anterior were significantly smaller (by ~26 and ~16%, respectively) in MCK-CN* mice compared to WT. The masses of mixed phenotype muscles, such as the plantaris and the extensor digitorum longus, were not significantly changed from WT. The soleus, plantaris, MG and diaphragm displayed shifts toward slower MHC isoforms, e.g., soleus from WT mice contained ~52% MHC-I, ~39% MHC-IIa, and ~9% MHC-IIx, whereas MCK-CN* mice had ~67% MHC-I, ~26% MHC-IIa, and ~7% MHC-IIx. The specific isoforms that were either up or down-regulated were muscle-specific. For instance, the proportion of MHC-IIa was decreased in the soleus and diaphragm, but increased in the plantaris and MG of MCK-CN* mice. Also, the proportion of MHC-IIx was unchanged in the soleus, decreased in the diaphragm and increased in the plantaris and MG of MCK-CN* relative to WT mice. Fast to slow shifts in fiber type proportions were evident for the plantaris, but not the soleus. Fast, but not slow, plantaris fibers of MCK-CN* mice had higher oxidative and lower glycolytic properties than WT. Conclusion These data suggest that calcineurin activation can influence muscle phenotype and that the specific influence of calcineurin activation on the phenotypic and mass characteristics of a muscle is dependent upon the original phenotypic state of the muscle. ==== Body Background Skeletal muscle adapts to neural and use-dependent signals by altering its mass and phenotypic properties, including the proportion of slow (I) and fast (IIa, IIx, and IIb) myosin heavy chain (MHC) isoforms [1,2]. Calcineurin has been implicated as a regulatory molecule involved in the transduction of contractile activity-based signals to molecular signals involved in the regulation of muscle growth and phenotypic gene expression in skeletal muscle [3-14]. Calcineurin is a phosphatase (protein phosphatase 2B) that is activated by calmodulin upon binding Ca2+ and has been shown to play an important role in the regulation of cytokine gene expression in lymphocytes [15,16]. Substrates for calcineurin include the phosphorylated isoforms of a transcription factor known as the nuclear factor of activated T cells (NFAT) [17]. Upon dephosphorylation, NFAT isoforms translocate into the nucleus where they can bind to a conserved DNA binding site known as the NFAT response element (NRE) and alter transcription, leading to enhanced expression of specific genes [15-17]. It has been proposed that in skeletal muscle nuclear NFAT can activate the expression of slow muscle phenotypic genes [3-5,8,11,14]. In addition, MEF2 and NFAT appear to act synergistically in turning on slow muscle fiber specific genes [18]. Thus, increased muscle contractile activity and the resulting sustained elevations in cytosolic Ca2+ could potentially result in altered phenotype-specific gene expression via calcineurin [4]. To date, however, no studies have reported the influence of chronically elevated calcineurin activity on the MHC isoform composition and fiber cross-sectional areas (CSAs) of limb and respiratory skeletal muscles. Therefore, in the present study, transgenic mice containing a highly expressed transgene consisting of a constitutively active form of calcineurin (CN*) driven by the muscle creatine kinase (MCK) enhancer were used to assess the influence of chronic calcineurin activation on MHC isoform protein and muscle mass and fiber cross-sectional area (CSA). Previous studies using the same line of transgenic mice demonstrated that calcineurin activation elevates the expression of some slow phenotypic genes [11], the percentage of EDL fibers with MHC-IIa [19], and proteins related to insulin-stimulated glucose uptake [20]. Results The MCK-CN* transgenic mice expressed the transgene in all muscles tested as shown in Figure 1. As expected, due to transgene expression being driven by a fast muscle-specific enhancer (MCK enhancer), the fast MG muscle displayed the highest level of expression. The soleus (a mixed fast and slow muscle in mice), diaphragm and plantaris showed relatively similar levels of transgene expression. Figure 1 A) SYBR® Green I stained agarose gel of PCR products following RT-PCR for the MCK-CN* mRNA product. No specific product (~900 bp, arrow) is observed in the DNase-treated RNA samples (first 4 lanes) of either wild-type (WT) or MCK-CN* transgenic (CN*) mouse gastrocnemius. Therefore, there is no contaminating genomic DNA in the RNA samples used for RT-PCR. As expected, RT-PCR of the cDNA (second four lanes) reveals that expression of the transgene is only observed in the MCK-CN* mice. A positive (+) control of tail DNA from an MCK-CN* mouse is shown on the right. B) Western blot of CN* and WT mouse soleus (SOL), diaphragm (DIA), plantaris (PLANT) and gastrocnemius (GAST) muscles for calcineurin. The polyclonal MAb recognized both the endogenous (CN, ~60 kDa) and constitutively active (CN*, ~45 kDa) forms. As expected, muscle from WT muscles did not contain the CN* protein. C) Relative semi-quantitative analysis of CN* mRNA (via RT-PCR) and protein (western blotting) in muscles of MCK-CN* mice. All values were normalized to the same soleus muscle (n = 3 – 6 per group). The asterisk (*) denotes significantly different (p ≤ 0.05) from other muscles. As shown in Figure 2, the muscles from MCK-CN* mice showed significant shifts towards slower MHC isoforms compared to WT. However, the specific isoforms that were either up- or down-regulated were muscle specific. For instance, the soleus of MCK-CN* mice showed an elevation in MHC-I at the expense of MHC-IIa. The MG showed a reduction in MHC-IIb, the fastest of the MHC isoforms expressed in mice, and elevations in MHCs-I, -IIa, and -IIx. The diaphragm showed an elevation in MHC-I and reductions in MHCs-IIa and -IIx. The diaphragm of the MCK-CN* mice also showed a complete absence of MHC-IIb, which was present in small proportions in WT mice. The plantaris of MCK-CN* mice showed similar directional adaptations in MHC isoforms as did the MG, i.e., higher proportions of MHCs-I, -IIa, and -IIx, and reduced MHC-IIb relative to WT mice. Thus, in MCK-CN* mice, MHC-I was consistently elevated and MHC-IIb reduced (if it was present in the WT muscle). In contrast, MHC-IIa was increased in the MG and plantaris, but decreased in the soleus and diaphragm of MCK-CN* mice. Also, MHC-IIx was increased in the MG and plantaris, decreased in the diaphragm, and unchanged in the soleus of MCK-CN* mice relative to WT. Figure 2 Adult myosin heavy chain (MHC) isoform proportions of the soleus (A), medial gastrocnemius (B), diaphragm (C), and plantaris (D) muscles of wild-type (dark bars) and MCK-CN* transgenic (gray bars) mice as determined by SDS-PAGE of whole muscle extracts. The * denotes significantly different from wild-type at p ≤ 0.05. Note the elevated proportions of slower MHC isoforms in the transgenic mice compared to wild-type. The plantaris muscle of MCK-CN* mice showed a significant shift in fiber type proportions from fast to slow as measured by the proportions of fast and slow isoforms of MHC, sarco(endo)plasmic reticulum Ca2+-ATPase (SERCA), and troponin I (Figure 3). Plantaris fibers that stained positively for the slow isoform of one protein stained positively for the slow isoforms of the other proteins and likewise for fast protein isoforms. In contrast, immunohistochemical techniques did not detect significant differences in the proportions of fibers containing specific MHC isoforms in the soleus of MCK-CN* mice (Figure 4). However, there was a non-statistically significant tendency for increased proportions of fibers with slower MHC isoforms. Figure 3 Proportions of plantaris fibers staining positively for slow and fast isoforms of MHC, sarco(endo)plasmic reticulum Ca2+ ATPase (SERCA), and troponin I (Tn I) in wild-type and MCK-CN* transgenic mice. MHC-I, SERCA2, and TN I slow are the slow muscle isoforms and MHC-II, SERCA1 and Tn I fast are the fast muscle isoforms. The * denotes significantly different from wild-type at p ≤ 0.05. Note the elevated proportions of fibers staining positively for the slow isoforms in the transgenic mice compared to wild-type. All fibers that stained positively for the slow MHC (MHC-I) were positive for the slow isoforms of SERCA and Tn I and all fibers that stained positively for the fast MHC (MHC-II) were positive for the fast isoforms of SERCA and Tn I. Figure 4 Proportions of soleus fibers staining positively for specific fast and slow MHC isoforms in wild-type and MCK* transgenic mice. No fibers stained positively for MHC-IIb with mAb BF-F3, thus antibody RT-D9 which is specific for MHC-IIx and MHC-IIb indicated the presence of MHC-IIx. No significant differences in fiber proportions of the soleus were found between wild-type and MCK-CN* mice. To ascertain if other phenotypic properties of muscle fibers were influenced by calcineurin activation, plantaris fibers of MCK-CN* and WT mice were analyzed for marker enzymes of oxidative (succinate dehydrogenase, SDH) and glycolytic (α-glycerophosphate dehydrogenase, GPD) capacity. Fast plantaris fibers of MCK-CN* mice showed a significant increase in SDH staining intensity, indicative of elevated mitochondrial content, and a decrease in glycolytic staining intensity, indicative of reduced glycolytic capacity (Figure 5). In contrast, slow plantaris fibers of MCK-CN* mice were not different from WT (Figure 5). Figure 5 Oxidative and glycolytic enzymatic profiles of individual plantaris fibers of wild-type and MCK-CN* transgenic mice. The * denotes significantly different from wild-type at p ≤ 0.05. A) The specific activity of succinate dehydrogenase (SDH, oxidative marker) was increased in fast (type II) plantaris fibers, but unchanged in slow (type I) fibers. The specific activity of α-glycerophosphate dehydrogenase (GPD, glycolytic marker) was significantly decreased in fast plantaris fibers, but not slow fibers. B) The integrated activity (see methods for explanation of integrated activity) of succinate dehydrogenase (SDH, oxidative marker) was increased in fast (type II) plantaris fibers, but unchanged in slow (type I) fibers. The integrated activity of α-glycerophosphate dehydrogenase (GPD, glycolytic marker) was significantly decreased in fast plantaris fibers, but not slow fibers. C) The GPD/SDH ratio (glycolytic/oxidative ratio) was significantly decreased in fast fibers, but unchanged in slow fibers of the plantaris of MCK-CN* mice relative to wild-type. As shown in Table 1, the mass of a characteristically slow muscle, i.e., the soleus, was greater; whereas, the mass of characteristically fast muscles, i.e., the MG and tibialis anterior were lower in MCK-CN* vs. WT mice. The masses of muscles that characteristically display a more intermediate phenotype, with relatively high proportions of fast oxidative (i.e., IIa and IIx) fibers, i.e., the plantaris and the extensor digitorum longus, were unchanged. Table 1 Body and absolute and relative muscle masses. Wild-type (n = 6) MCK-CN* (n = 10) Body Mass (g) 23.3 ± 0.9 20.7 ± 0.4* Absolute Muscle Mass (mg) Soleus 8.2 ± 0.6 10.2 ± 0.6* MG 46.7 ± 1.8 34.5 ± 1.9* PLT 16.8 ± 0.8 16.2 ± 0.7 TA 43.0 ± 1.2 36.0 ± 1.3* EDL 8.3 ± 1.3 7.8 ± 0.5 Relative Muscle Mass (mg/g body mass) Soleus 0.35 ± 0.02 0.48 ± 0.02* MG 2.01 ± 0.04 1.66 ± 0.09* PLT 0.72 ± 0.03 0.78 ± 0.04 TA 1.85 ± 0.04 1.74 ± 0.06 EDL 0.36 ± 0.05 0.38 ± 0.03 Abbreviations: MG, medial gastrocnemius; PLT, plantaris; TA, tibialis anterior; EDL, extensor digitorum longus. Values with asterisks are significantly different from wild-type at p ≤ 0.05. As expected, based on the overall differences in muscle mass between MCK-CN* and WT mice, the soleus contained fibers with CSAs greater than WT, whereas the MG contained fibers with CSAs smaller than WT (Figure 6A). The plantaris, which showed no change in mass, also showed no change in fiber CSA (Figure 6B). In the soleus, both slow and fast fibers were larger (Figure 6C). However, slow fibers were increased in CSA by 49% and fast fibers by only 22%. This resulted in a ~20% increase in the proportion of the muscle CSA occupied by slow fibers in MCK-CN* mice (Figure 6D). Thus, the changes in overall phenotype of the soleus can be partially accounted for by changes in the size of specific types of fibers. Figure 6 Individual fiber cross sectional areas (CSAs) in muscles of wild-type and MCK-CN* mice. A) Mean fiber CSAs in soleus and medial gastrocnemius (MG) muscle regardless of fiber type. B) Mean fiber CSAs of slow (type I) and fast (type II) fibers of the plantaris muscle. C) Mean fiber CSAs of slow (type I) and fast (type II) fibers of the soleus muscle. D) The percent of the entire soleus muscle cross-section occupied by slow (type I) and fast (type II) fibers. The * denotes significantly different from wild-type at p ≤ 0.05. Discussion Elevated calcineurin activity altered the phenotypic profile and mass of both fast and slow muscles and muscle fibers. The phenotypic changes were indicated by the general fast to slow adaptation in MHC isoform expression in MCK-CN* versus WT mice. The changes in phenotype were apparently not restricted to MHC isoforms since the plantaris of MCK-CN* mice had higher proportions of fibers that stained positive for the slow isoforms of MHC, SERCA and troponin I, suggesting a coordinated increase in the expression of slow phenotypic proteins upon calcineurin activation. Fast plantaris fibers also had elevated oxidative and reduced glycolytic profiles, suggesting that calcineurin activation influenced the metabolic profile of fibers promoting a more oxidative phenotype. These data suggest that fibers that did not show adaptations in MHC, SERCA or troponin I isoforms and remained fast were still influenced by calcineurin activation to acquire an oxidative phenotype. These changes are consistent with the proposed role of calcineurin as a sensor of contractile activity and transducer of contractile signals into molecular signals that induce the expression of a slow oxidative phenotype [4]. The overall changes in MHC isoform composition for some muscles, such as the soleus, were apparently aided by fiber type-specific changes in the CSA of the fibers, such that type I fibers were increased and type II fibers decreased (or increased only slightly in the soleus) in CSA as a result of elevated calcineurin activity. These data are consistent with the hypothesis that elevated calcineurin activity induces increased expression of slow muscle phenotypic genes resulting in elevated mass of slow muscles and muscle fibers. In addition, fibers from fast muscles may attain a smaller CSA in MCK-CN* mice relative to WT as a result of the change in phenotype from a fast glycolytic type of fiber (typically the largest fibers) towards a slow or fast oxidative type of fiber (typically the smallest fibers), see Rivero et al. [21,22]. Although the general adaptations in phenotype were in the direction of faster to slower isoforms, the actual transitions in MHC isoform content were muscle-specific. This is reminiscent of the muscle-specific influence of thyroid hormone treatment on muscle phenotype [23]. Of the muscles examined, the diaphragm of MCK-CN* mice showed the greatest absolute elevation in MHC-I content. Also, in the soleus and diaphragm of MCK-CN* mice, MHC-I was up-regulated at the expense of MHC-IIa. However, in the MG, MHCs-I, -IIa, and -IIx were up-regulated at the expense of MHC-IIb. The mechanisms by which some muscles (MG and plantaris) respond to calcineurin activation by up-regulating MHC-IIa and IIx whereas others (soleus and diaphragm) down-regulate these MHCs is currently unknown. In vitro data suggest that MHC-IIa is highly (100 fold) and MHC-IIx and -IIb moderately (~5 – 10 fold) stimulated by calcineurin activation in mouse C2C12 cells [24]. Because the adaptations were muscle-specific it is likely that additional mechanisms must be invoked in the in vivo state to modulate the ultimate response to calcineurin activation. Since the diaphragm showed the greatest response to calcineurin activation and the diaphragm is a chronically active muscle it is tempting to speculate that the chronic motor activity of this muscle results in an up-regulation of parallel signaling pathways that may support a more pronounced calcineurin activity-induced shift in fiber phenotype. The observation that MHC-IIa and MHC-IIx were up-regulated in fast muscles and MHC-I was up-regulated in slow muscles of MCK-CN* mice is in agreement with the idea of a limited adaptive range for muscles of varying phenotype. The limited adaptive range theory essentially states that muscles from a slow developmental lineage have the capacity to adapt in the range of I ↔ IIa ↔ IIx, whereas muscles from a fast developmental lineage can adapt in the range of IIa ↔ IIx ↔ IIb [25]. Thus, MG and plantaris fibers may be restricted to express MHC-IIa as the 'slowest' MHC isoform. In contrast, soleus and diaphragm fibers have the capacity to express MHC-I as the slowest MHC. However, recent data demonstrate that the suggested limited adaptive range for slow muscle is not strict. For example, combined treatment of rats with thyroid hormone and hindlimb suspension results in substantial expression of MHC-IIb by the soleus [26]. Another potential explanation for the muscle-specific response to chronic calcineurin activation is a possible obligatory step-wise transition from MHC-IIb ↔ IIx ↔ IIa ↔ I [27]. Following this scheme a fast muscle fiber would initially express MHC-IIx and then IIa as it transitioned towards a slower phenotype. However, this is a temporal scheme and the animals in this study were 3 months of age, therefore, sufficient time was available for a complete transition of fast muscles to MHC-I. In addition, previous studies from our [28-31] and other [26,32] laboratories have demonstrated that the obligatory step-wise transition scheme is not always followed. For instance, some rat soleus fibers can transition from MHC-I to MHC-IIx without apparent expression of MHC-IIa protein following hindlimb suspension, spaceflight, or paralysis induced by either spinal cord transection or spinal cord isolation [28-31]. The molecular mechanisms involved in directing the muscle-specific response are unknown, but could involve parallel signaling pathways, perhaps involving CAMKinase, MEF2, PGC-1, or altered histone acetylation at specific sites. It is also possible that variability in inherent motor-neuron activity influences the expression of specific sets of parallel signaling pathways which in turn allows for alteration of only specific sets of phenotypic proteins in muscles of differing phenotype. Our data showing that the diaphragm, a chronically active muscle, had the greatest absolute increase in MHC-I protein lends support to this idea. Ultimately, these data support the idea that calcineurin activity plays a role in the regulation of muscle phenotype. Since the expression level of the transgene in these mice results in basal calcineurin activity levels that are ~10 times the activity in WT mice [33], and since the phenotypic adaptations were somewhat modest, this suggests that parallel pathways likely need to be invoked to induce a more complete fiber type shift. In addition, the activation of calcineurin did not completely supersede the developmental-based phenotypic lineage. For instance, in the MCK-CN* mice the soleus retained ~40% fast (type II) fibers and the MG was predominantly composed of fast MHC isoforms. However, it must be noted that the transgene is active in the MCK-CN* mice during all stages of development. Thus, negative feedback mechanisms that may reduce the down-stream effectiveness of calcineurin activation may be enhanced or invoked during the development and maturation of the skeletal musculature. It is also possible that parallel pathways must be invoked with calcineurin to fully activate the slow muscle specific phenotype, as suggested by Dunn et al., [7] and demonstrated by Wu et al., [18]. Presence of the transgene will only directly influence the basal calcineurin activity and it is possible that higher sustained levels of calcineurin activity, such as may occur with sustained contractile activity-induced elevations in myoplasmic calcium, would support a more complete fiber transformation. Since the Ca2+-calmodulin stimulation of calcineurin can be as great as 100-fold [15], it is possible that normal in vivo calcium-induced activation of endogenous calcineurin would result in a much greater elevation in calcineurin activity and a greater degree of fiber type transformation. Several studies have suggested that calcineurin activation does not influence muscle mass [7,34-36] or phenotype [37]. One of these studies, Dunn et al., [7], made use of a similar transgenic mouse model as that used in this study. However, the level of basal calcineurin activity in the mice used by Dunn et al., [7] was reported to be several times lower (~same as WT) than that reported for the mice used in our study, ~10× greater than WT, i.e., transgenic mouse line #1 from reference [33]. Thus, the lack of effect in some of the previous studies may be related to the level of transgene expression and the lower basal calcineurin activity. It is interesting to note that the transgenic mice used by Dunn et al. [7], also did not display differences in fiber phenotype compared to WT. In contrast, other studies have demonstrated that calcineurin activation and or the accumulation of nuclear NFAT may be involved in the mediation of growth inducing factors, such as IGF-1 [10,13,38]. Curiously, our data suggest that chronic calcineurin activation results in elevated mass of slow muscle and reduced mass of fast muscle. This suggests that the changes in mass and fiber CSA may be secondary to the changes in phenotype. The differential effect of chronic calcineurin activation on slow vs. fast muscle mass may be explained as follows. Elevated expression of slow phenotypic genes in a slow muscle could theoretically result in an increased accretion of slow phenotypic proteins and elevated size of slow fibers. Fast muscle fibers showed an elevation in oxidative enzyme activity, i.e., transitioned from a fast glycolytic (FG) to a fast oxidative glycolytic (FOG) phenotype. Typically, FG fibers are larger than FOG fibers in mammalian muscle. A strong inverse correlation exists between oxidative capacity and fiber CSA [39,40]. Thus, as fast fibers transitioned from FG towards FOG in response to calcineurin activation, they would achieve a smaller CSA. Conclusions Collectively, the data support the hypothesis that calcineurin activation plays an important role in the modulation of skeletal muscle phenotype. The responses to calcineurin activation were muscle specific, suggesting that inherent differences in signaling mechanisms within distinct muscles likely modulate the response to calcineurin activation. The observation that a 10-fold increase in basal calcineurin activity results in alterations in the expression of fast versus slow phenotypic proteins and alterations in the metabolic capacities of fibers that do not show a transition to slow fiber type isoforms suggests that the activation of this pathway can modulate multiple aspects of fiber phenotype. However, parallel pathways likely need to be invoked to completely alter the phenotype of all fibers in a muscle. Methods Animals Breeding pairs of MCK-CN* transgenic mice were obtained from the primary colony at the University of Texas Southwestern Medical Center [11] and housed at the Animal Care Facility at Virginia Polytechnic Institute and State University. This specific line of transgenic mice has been used previously to study the influence of calcineurin activation on the expression of utrophin [19], and insulin-sensitive glucose uptake [20]. Female B6C3F1 mice expressing a transgene consisting of 4800 bp of the MCK enhancer, the coding sequence of the activated form of calcineurin, which codes for amino acids 1 to 398 and lacks the autoinhibitory and calmodulin binding domains [41], and 620 bp of the human growth hormone polyadenylation signal (MCK-CN* mice) were crossed with the C57Bl6J strain. Transgenic offspring were identified by PCR amplification of tail DNA using primers specific for sequences within the calcineurin coding region (5'-GAA CCA GCA GTT CCT GTG TGT ACA CG-3') and the hGH polyadenylation signal (5'-CAC TCC AGC TTG GTT CCC GAA TAG AC-3'). Since the transgenic mice were generated in the B6C3F1 strain and were then crossed with the C57Bl6J line, all comparisons were made to wild-type (WT) littermate controls, which would share any strain dependent variables with the MCK-CN* transgenic mice. All animal procedures were approved by the Virginia Polytechnic Institute and State University and California State Polytechnic University Institutional Animal Care and Use Committees and conform to the American Physiological Society's guiding principles for the care and use of animals. MCK-CN* (n = 10) and WT littermate controls (n = 6) were sacrificed by pentobarbital injection at 3 months of age. Animals from two independent litters were used. The diaphragm, soleus, medial gastrocnemius (MG), plantaris, tibialis anterior, and extensor digitorum longus muscles were dissected free, trimmed of excess connective tissue, and weighed (diaphragm weights were not obtained). The muscles (except tibialis anterior and extensor digitorum longus) were then rapidly frozen in melting isopentane cooled with liquid nitrogen and stored at -70°C. Muscle RNA analyses Total RNA was isolated from frozen muscle (soleus, MG, plantaris, and diaphragm) samples using Trizol reagent according to the manufacturer's instructions (Invitrogen Corp., Carlsbad, CA, USA). The final RNA pellet was dissolved in nuclease-free water, treated with DNA-free™ (Ambion Inc, Austin, TX, USA) to remove potential contaminating genomic DNA, and then quantified by UV (A260) light absorbance. All RNA samples had A260:A280 ratios of greater than 1.8. Two μg of the isolated RNA were reverse transcribed to cDNA with Superscript II (Invitrogen Corp.) in a final volume of 20 μl. The same PCR primers used for genotyping were used to amplify the specific cDNA fragment from transgenic mice expressing the MCK-CN* transgene. The PCR reaction included: 1 μl of cDNA, 1X Platinum Taq PCR buffer (Invitrogen Corp.), 1.5 mM MgCl2, 0.2 mM dNTPs, 1 μM each primer, and 1 unit Platinum Taq (Invitrogen Corp.) in a final volume of 25 μl. The PCR cycle conditions were 94°C for 4 min and then 40 cycles of 94°C for 30 sec, 61°C for 30 sec, and 72°C for 30 sec, followed by a final step at 72°C for 5 min. The PCR products were separated on 1.5% agarose gels, stained with SYBR® green I (Molecular Probes Inc., Eugene, OR, USA) and quantified using a ChemiImager 5500 (Alpha Innotech, San Leandro, CA, USA). Muscle protein analyses One MG, plantaris and soleus muscle from each animal were serially sectioned perpendicular to the fiber axis using a Microm cryostat, stained imuunohistochemically for fast or slow myosin heavy chain (MHC) isoforms using either anti-fast or anti-slow MHC monoclonal antibodies (mAb, Novocastra Laboratories, Inc.) according to Talmadge et al., [30]. Soleus tissue sections were also analyzed for the presence of MHC-IIa, MHC-IIx and MHC-IIb using mAbs specific for MHC-IIa (mAb SC-71), MHCs-IIx & -IIb (mAb RT-D9) and MHC-IIb (mAb BF-F3). Serial sections of the plantaris were also immunohistochemically stained for the presence of fast and slow isoforms of troponin I (Research Diagnostics Inc.) and sarco(endo)plasmic reticulum Ca2+ ATPase (SERCA, Novocastra Laboratories, Inc.) isoforms using similar techniques. The sections treated for immunohistochemistry were used to measure the cross-sectional area (CSA) of fifty individual muscle fibers per muscle using a calibrated microscopy-based image analysis system consisting of a GMS-300 grayscale microscopy system (Scion, Frederick, MD) and a Nikon Eclipse E400 microscope. The MG, plantaris and soleus from the opposite limb and the whole diaphragm (including costal and crural portions) were subjected to high resolution SDS-PAGE for analysis of myosin heavy chain isoforms as detailed in Talmadge and Roy [42]. These muscles were also analyzed for constitutively active and endogenous calcineurin protein levels by semi-quantitative western blotting as described in detail previously by Spangenburg et al. [43]. The primary antibody used for western blotting was a rabbit anti-calcineurin Pan A polyclonal (AB1695) from Chemicon International (Temecula, CA, USA) which recognized both the constitutively active (CN*) and endogenous forms of calcineurin. The western blot results obtained using this primary antibody were verified (data not shown) with other antibodies that showed similar patterns of reactivity, including antibodies CN-A1 (Sigma Chemical Co., St. Louis, Mo, USA), SC-9070 (Santa Cruz Biotechnology Inc., Santa Cruz, CA, USA), and AB1696 (Chemicon International). Quantitative histochemistry of individual muscle fibers Quantitative histochemical analyses of oxidative and glycolytic enzyme activities were measured on 50 plantaris fibers per muscle that were immunohistochemically typed for fast or slow MHC isoform content in serial sections. According to Rivero et al., [21,22], succinate dehydrogenase (SDH; EC 1.3.5.1) was used as a marker for oxidative capacity and α-glycerophosphate dehydrogenase (GPD) was used as a marker for glycolytic capacity of individual muscle fibers. Histochemical staining and image analysis were performed as previously described in detail [21,22]. The specific enzymatic activity per unit fiber volume (i.e., enzyme concentration) is expressed as change in OD per minute of reaction. The integrated enzymatic activities (ISDH and IGPD) were calculated as the product of specific enzymatic activity (OD/min for a given fiber) and CSA of that fiber which reflects the enzyme content per fiber and is expressed as OD/min × microns2. Statistical analyses Student's t-tests were used for comparing mean data between transgenic and WT mice at each age. Statistical differences were significant at p ≤ 0.05. Authors' contributions RJT: conception, design, data collection and analysis, manuscript preparation, research funds collection. JSO: quantitative histochemical analyses, genotyping, statistical analysis, figure preparation. MRR: electrophoretic analyses, statistical analysis, figure preparation. NDG: mRNA and electrophoretic analyses, figure preparation. SRS: western blotting, figure preparation. SJL: muscle sample collection. FJN: supplied transgenic mice, provided genotyping expertise. Acknowledgments We thank Shannon Weber for excellent technical assistance. The authors thank R.W. Grange for help with transgenic animal identification methods and Jay H. Williams for laboratory facilities. The current address for Simon J. Lees is Department of Veterinary Biomedical Sciences, University of Missouri, Columbia, MO 65211; for Jeffrey S. Otis is Emory University, Rollins Research Center, 1510 Clifton Road, Atlanta, GA 30329; and for Francisco J. Naya is Biology Department, Boston University, Boston, MA. 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10.1002/(SICI)1097-0185(19990601)255:2<188::AID-AR9>3.0.CO;2-H Talmadge RJ Roy RR Edgerton VR Prominence of myosin heavy chain hybrid fibers in soleus muscle of spinal cord-transected rats J Appl Physiol 1995 78 1256 1265 7615431 Andersen JL Gruschy-Knudsen T Sandri C Larsson L Schiaffino S Bed rest increases the amount of mismatched fibers in human skeletal muscle J Appl Physiol 1999 86 455 460 9931176 Wu H Rothermel B Kanatous S Rosenberg P Naya FJ Shelton JM Hutcheson KA DiMaio JM Olson EN Bassel-Duby R Williams RS Activation of MEF2 by muscle activity is mediated through a calcineurin-dependent pathway EMBO J 2001 20 6414 6423 11707412 10.1093/emboj/20.22.6414 Bodine SC Stitt TN Gonzalez M Kline WO Stover GL Bauerlein R Zlotchenko E Scrimgeour A Lawrence JC Glass DJ Yancopoulos GD Akt/mTOR pathway is a crucial regulator of skeletal muscle hypertrophy and can prevent muscle atrophy in vivo Nat Cell Biol 2001 3 1014 1019 11715023 10.1038/ncb1101-1014 Rommel C Bodine SC Clarke BA Rossman R Nunez L Stitt TN Yancopoulos GD Glass DJ Mediation of IGF-1-induced skeletal myotube hypertrophy by PI(3)K/Akt/mTOR and PI(3)K/Akt/GSK3 pathways Nat Cell Biol 2001 3 1009 1013 11715022 10.1038/ncb1101-1009 Parsons SA Millay DP Wilkins BJ Bueno OF Tsika GL Neilson JR Liberatore CM Yutzey KE Crabtree GR Tsika RW Molkentin JD Genetic loss of calcineurin blocks mechanical overload-induced skeletal muscle fiber type switching but not hypertrophy J Biol Chem 2004 279 26192 26200 15082723 10.1074/jbc.M313800200 Swoap SJ Hunter RB Stevenson EJ Felton HM Kansagra NV Lang JM Esser KA Kandarian SC The calcineurin-NFAT pathway and muscle fiber-type gene expression Am J Physiol Cell Physiol 2000 279 C915 C924 11003571 Vyas DR Spangenburg EE Abraha TW Childs TE Booth FW GSK-3beta negatively regulates skeletal myotube hypertrophy Am J Physiol Cell Physiol 2002 283 C545 C551 12107064 Nakatani T Nakashima T Kita T Hirofuji C Itoh K Itoh M Ishihara A Succinate dehydrogenase activities of fibers in the rat extensor digitorum longus, soleus, and cardiac muscles Arch Histol Cytol 1999 62 393 399 10596950 Nakatani T Nakashima T Kita T Hirofuji C Itoh K Itoh M Ishihara A Cell size and oxidative enzyme activity of different types of fibers in different regions of the rat plantaris and tibialis anterior muscles Jpn J Physiol 2000 50 413 418 11082539 O'Keefe SJ Tamura J Kincaid RL Tocci MJ O'Neill EA FK-506- and CsA-sensitive activation of the interleukin-2 promoter by calcineurin Nature 1992 357 692 694 1377361 10.1038/357692a0 Talmadge RJ Roy RR Electrophoretic separation of rat skeletal muscle myosin heavy-chain isoforms J Appl Physiol 1993 75 2337 2340 8307894 Spangenburg EE Williams JH Roy RR Talmadge RJ Skeletal muscle calcineurin: influence of phenotype adaptation and atrophy Am J Physiol Regul Integr Comp Physiol 2001 280 R1256 R1260 11247852

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==== Front BMC Evol BiolBMC Evolutionary Biology1471-2148BioMed Central London 1471-2148-4-231528386010.1186/1471-2148-4-23Research ArticlePhylogenetic relationships of typical antbirds (Thamnophilidae) and test of incongruence based on Bayes factors Irestedt Martin 12martin.irestedt@nrm.seFjeldså Jon 3jfeldsaa@zmuc.ku.dkNylander Johan AA 4johan.nylander@ebc.uu.seEricson Per GP 1per.ericson@nrm.se1 Department of Vertebrate Zoology and Molecular Systematics Laboratory, Swedish Museum of Natural History, P.O. Box 50007, SE-104 05, Stockholm, Sweden2 Department of Zoology, University of Stockholm, SE-106 91 Stockholm, Sweden3 Vertebrate Department, Zoological Museum, University of Copenhagen, Universitetsparken 15, DK-2100 Copenhagen Ø, Denmark4 Department of Systematic Zoology, Evolutionary Biology, Centre, Uppsala University, Uppsala, Sweden2004 30 7 2004 4 23 23 26 4 2004 30 7 2004 Copyright © 2004 Irestedt et al; licensee BioMed Central Ltd.2004Irestedt et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background The typical antbirds (Thamnophilidae) form a monophyletic and diverse family of suboscine passerines that inhabit neotropical forests. However, the phylogenetic relationships within this assemblage are poorly understood. Herein, we present a hypothesis of the generic relationships of this group based on Bayesian inference analyses of two nuclear introns and the mitochondrial cytochrome b gene. The level of phylogenetic congruence between the individual genes has been investigated utilizing Bayes factors. We also explore how changes in the substitution models affected the observed incongruence between partitions of our data set. Results The phylogenetic analysis supports both novel relationships, as well as traditional groupings. Among the more interesting novel relationship suggested is that the Terenura antwrens, the wing-banded antbird (Myrmornis torquata), the spot-winged antshrike (Pygiptila stellaris) and the russet antshrike (Thamnistes anabatinus) are sisters to all other typical antbirds. The remaining genera fall into two major clades. The first includes antshrikes, antvireos and the Herpsilochmus antwrens, while the second clade consists of most antwren genera, the Myrmeciza antbirds, the "professional" ant-following antbirds, and allied species. Our results also support previously suggested polyphyly of Myrmotherula antwrens and Myrmeciza antbirds. The tests of phylogenetic incongruence, using Bayes factors, clearly suggests that allowing the gene partitions to have separate topology parameters clearly increased the model likelihood. However, changing a component of the nucleotide substitution model had much higher impact on the model likelihood. Conclusions The phylogenetic results are in broad agreement with traditional classification of the typical antbirds, but some relationships are unexpected based on external morphology. In these cases their true affinities may have been obscured by convergent evolution and morphological adaptations to new habitats or food sources, and genera like Myrmeciza antbirds and the Myrmotherula antwrens obviously need taxonomic revisions. Although, Bayes factors seem promising for evaluating the relative contribution of components to an evolutionary model, the results suggests that even if strong evidence for a model allowing separate topology parameters is found, this might not mean strong evidence for separate gene phylogenies, as long as vital components of the substitution model are still missing. ==== Body Background The typical antbirds (Thamnophilidae) is a speciose family within the furnariid radiation (sensu [1]) of the New World suboscine clade. The family includes fully 200 species [2] that all are restricted to neotropical forests. Most species are arboreal or undergrowth inhabitants, while only a few members are clearly terrestrially adapted, which otherwise seems to be the commonest lifestyle for most members in closely related clades (e.g., gnateaters Conopophagidae, antpittas Grallariidae, tapaculos Rhinocryptidae, and antthrushes Formicariidae). The highest diversity of typical antbirds is found in the Amazonian basin, and differences in ecological specializations make it possible to find as many as 40 species in the same area [3]. Morphologically typical antbirds shows considerable variation in size and patterns and colors of the plumage (black and shades of grey, buff and chestnut, with sexual plumage dimorphism in many species), while the variation in shape is more restricted. Many insectivorous niches are occupied, but the specialization of some species to follow army ants (to capture escaping insects) is perhaps the most well known. This habit has also given raise to the vernacular family name. In traditional classifications, the antpittas (Grallariidae) and antthrushes (Formicariidae) were grouped together with typical antbirds in an even larger family. However, the support for the expanded antbird family was indeed weak, and both morphological [4-6] and molecular [1,7] evidence suggests that antpittas and antthrushes are distantly related to typical antbirds. DNA sequence data [1,8] suggests that gnateaters (Conopophagidae) forms the sister clade to typical antbirds, while antpittas and antthrushes are more closely related to tapaculos (Rhinocryptidae), woodcreepers and ovenbirds (Furnariidae). Even though the monophyly of typical antbirds seems to be well supported by both syrinx morphology [6] and molecular data [1,7] the phylogenetic relationships within this assemblage are poorly understood, and the confusion extending to all taxonomic levels. Both the monophyly of several genera of typical antbirds has been questioned [3,9,10], as well as the delimitation of certain species [2,11-14]. Some species have also been moved from one genus to another (e.g., the black-hooded antwren that has been moved from the genus Myrmotherula to Formicivora [15]). The current knowledge of the phylogenetic relationships among typical antbirds rests mainly on interpretations drawn from external features, mostly of bill and feet, and has remained essentially the same for 150 years [2]. As typical antbirds are morphologically and ecologically diverse, they form a challenging group for studies of, e.g. adaptive evolution. However, such studies, as well as biogeographic interpretations, are difficult to make as long as there is no phylogenetic hypothesis. The aim of this study is therefore to create a hypothesis of generic relationships of typical antbirds that could be used as a framework for more detailed studies of the evolution of the group. Two nuclear introns, intron 2 in myoglobin and intron 11 in the glyceraldehyde-3-phosphodehydrogenase gene (G3PDH), and the mitochondrial cytochrome b gene, have been sequenced for 51 typical antbird taxa representing 38 out of the 45 genera recognized by Ridgely and Tudor [3]. We have used Bayesian inference and Markov chain Monte Carlo (MCMC) to estimate the phylogenetic relationships. A common assumption made by molecular systematists is that gene trees accurately reflect species trees. Nevertheless, different data partitions may have different phylogenies due to processes as lineage sorting, gene duplication followed by extinction, and lateral transfer by hybridization and introgression (reviewed in [16-18]). Primarily, there are two contradictory strategies utilized to handle data sets with significant phylogenetic incongruence between independent data partitions. Advocates for a "total evidence approach" (e.g., [19,20]) suggest that available data always should be combined, even though individual data partitions might be partly incongruent. The arguments are that a combination of different data partitions might improve the total resolution as different data partitions might be useful to resolve different areas of the tree, and that additive data sets might enhance phylogenetic informative characters that have been hidden by noise in the individual partitions. Opponents to this view (e.g., [21,22]) advice that data partitions with a significant level of incongruence should not be combined, as reliable characters might be obscured by random or systematic errors and in the worse case result in an erroneous topology (even though individual data partitions might provide consistent estimates). However, when independent evidence is lacking and incongruence occurs between individual data partitions, it may be difficult to determine whether particular partitions are better estimates of the species tree than others. Researchers might favor the "total evidence approach" for this particular reason (even though the argument for not combining data partitions with significant levels of incongruence have strong merits). However, the degree of incongruence between individual gene trees could be used to determine whether the phylogenetic conclusions should be based on the combined data set, or only those parts that are similar among the different partitions. A commonly used approach for analysing combined data with maximum likelihood is to assume a single (the same) substitution model for all of the combined genes (for exceptions, see [23,24]). A significant result of incongruence between the combined result and the individual genes can then be hard to explain, since the incongruence could be due to both true difference in gene phylogeny and a misfit in the assumed model of evolution for the combined data [21,25]. This misfit could, for example, be a result of not allowing a heterogeneous model, that is, not allowing the different genes to have separate substitution models in the combined analysis [26]. We have thus explored our data partitions (the individual genes) by the congruence test described by Nylander et al. [27], which utilizes Bayes factors. The test is not an explicit significance test but compares the strength of evidence between two models of character evolution. Although nuclear genes (as when situated on different chromosomes) may be considered as members of different linkage groups, the maternally inherited mitochondrial genome is effectively independent from the nuclear genome. Organelle genomes have also been suggested to more susceptible to "flow" between taxa during hybridization (although much less common in animals than in plants). In birds Degnan and Moritz [28] and Degnan [29], for example, have demonstrated that the mitochondrial tree in Australian white-eyes misrepresented the tree of nuclear loci and the expected species tree, possibly due to previous hybridization events. We have thus primarily been interested in the potential incongruence between the mitochondrial cytochrome b and the two nuclear genes (myoglobin and G3PDH), but all combinations of the three genes were examined. However, limitations in the substitution models might be the most important explanation to observed incongruence between data partitions, rather than an intrinsic phylogenetic incongruence [27]. We also explored how changes in substitution models affected the observed incongruence in our data set. Results Molecular variation and sequence distances After alignment, the concatenated sequences become 2173 bp long. A total of between 679 bp (Sclerurus scansor) and 723 bp (Myrmotherula leucophthalma) was obtained from myoglobin intron 2, between 351 bp (Rhegmatorina melanosticta) and 400 bp (Myrmeciza griseiceps) from G3PDH intron 11, and 999 bp from cytochrome b. The observed, pairwise distances between ingroup taxa range between 0, 7% and 10, 7% in myoglobin, between 0, 3% and 19, 3% in G3PDH and between 6, 5% and 23, 9% in cytochrome b. Indels were found both in the myoglobin intron 2 and in the G3PDH intron 11. In most cases these are autapomorphic indels or occur in especially variable and repeatable regions. Given the tree topologies obtained from the Bayesian analyses, some synapomorphic indels were observed. For example, all Thamnophilus representatives share with Sakesphorus bernardi an insertion in the G3PDH intron, and, together with Dysithamnus mentalis and Herpsilochmus atricapillus, an insertion in the myoglobin intron. Phylogenetic inference and molecular models A priori selection of substitution models showed that fairly parameter rich models were the best fit for all data partitions. Importantly, modeling rate variation seemed to be an important component. For the cytochrome b partition the GTR+I+Γ was the best fit, and for myoglobin intron 2, it was the GTR+ Γ. For the G3PDH intron 11 the somewhat simpler HKY+ Γ model was chosen. These models were used in the consecutive MCMC of the individual genes as well in the combined analysis. The parameter estimates from the two separate MCMC runs for each data set were found to be very similar (data not shown), thus allowing an inference from the concatenated output. After discarding the burn-in phase the inference for the cytochrome b was based on a total of 36, 000 samples from the posterior, for myoglobin the inference was based on 38, 000 samples, and for G3PDH and the combined data, inference were based on 38, 000, and 55, 600 samples, respectively. For the phylogenetic inference, the mode of the posterior distribution of topologies was presented as a majority-rule consensus tree from each analysis (Figures 1,2,3,4). Figure 1 The G3PDH majority rule consensus tree. The 50% majority rule consensus tree obtained from the Bayesian analyses of the G3PDH (glyceraldehydes-3-phosphodehydrogenase) intron 11 data set. Posterior probability values are indicated to the right of the nodes. Figure 2 The myoglobin majority rule consensus tree. The 50% majority rule consensus tree obtained from the Bayesian analyses of the myoglobin intron 2 data set. Posterior probability values are indicated to the right of the nodes. Figure 3 The cytochrome b majority rule consensus tree. The 50% majority rule consensus tree obtained from the Bayesian analyses of the cytochrome b data set. Posterior probability values are indicated to the right of the nodes. Figure 4 The combined majority rule consensus tree. The 50% majority rule consensus tree obtained from the analyses of the combined data set (G3PDH intron 11, the myoglobin intron 2 and the cytochrome b data sets). Clades A, B and C are major groups of typical antbirds discussed in the text. Posterior probability values are indicated to the right of the nodes. The trees obtained from the Bayesian analyses of the individual genes (cytochrome b, myoglobin and G3PDH) and the combined data set all differ in topology and degree of resolution. The G3PDH gene produced the poorest resolved tree (Figure 1) and also contains the smallest number of nodes with posterior probability values above 0.90. The myoglobin (Figure 2) and cytochrome b (Figure 3) genes produced trees with similar degree of resolution and nodal supports, but there is a weak tendency for cytochrome b giving better resolution and support at terminal nodes. The combined data set (cytochrome b, myoglobin and G3PDH) produced the most resolved tree (Figure 4) with the highest number of strongly supported nodes (exceeding 0.90 posterior probability). Overall, the myoglobin, the cytochrome b and the combined trees are topologically rather similar, while the G3PDH tree is the most deviant. A common pattern in all trees is that several nodes are unresolved, or short with low or intermediate posterior probabilities support values (0.50–0.90). The observed topological conflicts between the obtained trees generally occur at these short nodes, and there are only a few nodes with posterior probabilities values above 0.90 that are in conflict between the trees. Of these, one concerns the outgroup relationships (the G3PDH tree supports with 0.96 posterior probability a position of Pteroptochos tarnii that differs from all other trees). The other two conflicts concern internal relationships within well supported sub-clades: The cytochrome b tree places with 0.98 posterior probability Myrmotherula menetriesii basal to a clade consisting of Myrmotherula axillaris, Myrmotherula behni and Formicivora rufa. In the combined tree Myrmotherula menetriesii instead is nested within this clade with 1.00 posterior probability. The myoglobin tree suggests with 0.94 posterior probability that Taraba major is basal to Batara cinerea and Hypoedaleus guttatus, while Taraba major is basal also to Mackenziaena severa and Frederickena unduligera with 0.99 posterior probability in both the combined and the cytochrome b trees. However, most suggested relationships are congruently supported by more than one of the trees obtained from the individual genes and by the combined data set. Several clades are also supported by all three genes trees as well as by the combined data set, including the recognition of a monophyletic origins of 1) the "large antshrikes" (Taraba major, Batara cinerea, Hypoedaleus guttatus, Mackenziaena severa, and Frederickena unduligera), 2) the "professional" ant-following antbirds (Pithys albifrons, Phlegopsis erythroptera, Phaenostictus mcleannani, Rhegmatorhina melanosticta and Gymnopithys leucaspis), 3) a Sakesphorus-Thamnophilus antshrike lineage (Sakesphorus bernardi and the five representatives of the genus Thamnophilus), and 4) a clade consisting of the wing-banded antbirds (Myrmornis torquata), the spot-winged antshrike (Pygiptila stellaris) and the russet antshrike (Thamnistes anabatinus). Sistergroup relationships between antvireos (Dysithamnus mentalis) and Herpsilochmus antwrens (Herpsilochmus atricapillus), as well as between Myrmotherula obscura and Myrmochanes hemileucus are also recognized by all trees. Based on the tree obtained from the Bayesian analysis of the combined data set, typical antbirds could also be divided into three major clades (marked as A, B and C in Figure 4). The first clade (clade A) includes four genera that are suggested to have a basal position in relation to all other typical antbirds (1.00 posterior probability in the combined tree). This basal group (supported by 0.72 posterior probability in the combined tree) includes the representative of Terenura antwrens (Terenura humeralis), the wing-banded antbird (Myrmornis torquata), the spot-winged antshrike (Pygiptila stellaris) and the russet antshrike (Thamnistes anabatinus). The second clade (clade B, Figure 4) is supported by 0.95 posterior probability in the combined tree and includes all antshrike genera (except the spot-winged antshrike and the russet antshrike, see clade A), antvireos (Dysithamnus), Herpsilochmus antwrens and the banded antbird (Dichrozona cincta). Within this large clade several lineages occur that receives more than 0.95 posterior probability. Noticeable within this clade is that neither the analyses of the individual genes nor the combined data set conclusively support that the representative of the antshrike genus Sakesphorus (Sakesphorus bernardi) is phylogenetically separated from the Thamnophilus antshrikes. The last clade (clade C, Figure 4), including the Myrmeciza antbirds, most antwren genera (e.g., Myrmotherula and Formicivora), the "professional" ant-following antbirds, and some allied species, is supported by a 1.00 posterior probability value. Also within this clade several lineages are supported by posterior probability values above 0.90. However, the most interesting observation is the strong support for a polyphyletic origin of the Myrmeciza antbirds and the Myrmotherula antwrens. Tests of incongruence The Bayes factor tests showed extensive incongruence between partitions, at least in the sense that relaxing the assumption of a common topology parameter always gave a better model likelihood (Table 1). For example, allowing the cytochrome b partition to have a separate topology from the two nuclear partitions myoglobin and G3PDH, gave a 2logB12 of 60.8. This value strongly suggests that an unlinked model is superior to the model assuming a common topology parameter for all partitions. This would also suggest that there is strong conflict between the mitochondrial and the nuclear partitions. However, this conclusion is far from conclusive when we consider the linking of the topology parameter for other combinations of the data. Combining the topology parameter for either one of the nuclear partitions with the mitochondrial, actually gives a better model (higher Bayes factors) than considering the mitochondrial vs. the nuclear partition (Table 1). For example, compared to the model that assumes a common topology parameter, unlinking the myoglobin partition from the other gave a 2logB of 102.26. Unlinking the G3PDH partition gave an even better model, with a 2logB of 118.12. Furthermore, if we would have to choose the one partitioning scheme that had the highest model likelihood, the model allowing a separate topology parameter for all partitions would be the clear choice (having a 2logB of 241.36 compared to the common model). Table 1 Summary of Bayes factor tests of incongruence. Entries are twice the log of the Bayes factor in the comparison between models M1 and M2 (2logB12). The row models are arbitrarily labeled M1; thus, positive values indicate support for the column model over the row model. A dash (-) indicates which partitions that have linked topology parameters. Model Cyt b-Myo-G3PDH Cyt b, Myo-G3PDH Cyt b-Myo, G3PDH Cyt b-G3PDH, Myo Cyt b, Myo, G3PDH Cyt b-Myo-G3PDH 0 60.84 118.12 102.26 241.36 Cyt b, Myo-G3PDH 0 57.28 41.42 180.52 Cyt b-Myo, G3PDH 0 -15.86 123.24 Cyt b-G3PDH, Myo 0 139.1 Cyt b, Myo, G3PDH 0 The parsimony based ILD-test did not find a significant incongruence between the three gene partitions (p = 0.967). Discussion Phylogenetic incongruence between gene partitions Allowing the gene partitions to have separate topology parameters clearly increased the model likelihood. That is, the unlinked models clearly had a better fit to the data than the linked models. Judging from the absolute value of the 2logB (Table 1), we are inclined to conclude that we should treat each partition as having its own posterior distribution of trees. However, the question is if we from these results really can say that the gene partitions evolved on different phylogenies? There are several reasons why different data partitions may have different phylogenies, although being sampled from the same taxa, or even the same individuals (se above). We cannot completely rule out the occurrence of any of these processes in our data. However, we believe that the interpretation based solely on Bayes factors might be hazardous. For instance, is it plausible that all three gene partitions had evolved on three different phylogenies, or that the linking of cytochrome b and myoglobin is a more reasonable partition of the data, instead of the mitochondrial versus the nuclear partitions? Nylander et al. [27], speculate that limitations in the substitution models might be more reasonable explanations to the high Bayes factors observed when comparing unlinked and linked models. Changing a component of the nucleotide substitution model, e.g. adding parameters to model rate variation, had much higher impact on the model likelihood than unlinking parameters among data partition. To illustrate the impact of changing the substitution model in our data, we run additional MCMC analyses under a different set of models, and compared them with the previous analyses using Bayes factors. The results were striking (Table 2). For example, we compared two models without rate variation, one with linked and the other with unlinked topologies (in both models GTR was used for cytochrome b and for myoglobin, and HKY for the G3PDH). The 2logB was 295.98 in favor for the unlinked model. However, adding parameters for modeling rate variation to either of the two models increased the model likelihood tremendously. The 2logB in favor of a model having parameters for rate variation (applying the same substitution models as the ones chosen a priori using AIC, see material and methods), varied between 5125.22 and 5662.56, depending on the model being compared (Table 2). Similar observations of magnitude changes in Bayes factors were made by Nylander et al. [27], when allowing rate variation. Another striking feature was that once parameters for modeling rate variation had been incorporated into the model, unlinking topologies did not seem to have as pronounced effect on the model likelihood (Table 2), compared to the models without rate variation. This observation is in concordance with previous findings that many functional genes have a strong among-site rate variation and that adding the relevant parameters to the model is likely to have a large effect on the likelihood [23,27,30,31]. Table 2 Summary of Bayes factor tests showing the effect of changing substitution model components. Entries are twice the log of the Bayes factor in the comparison between models M1 and M2 (2logB12). The row models are arbitrarily labeled M1; thus, positive values indicate support for the column model over the row model. A dash (-) indicates which partitions that have linked topology parameters. Asterisks (*) indicate models where the rates are assumed to be equal. Model Cyt b-Myo-G3PDH Cyt b, Myo, G3PDH Cyt b-Myo-G3PDH* Cyt b, Myo, G3PDH* Cyt b-Myo-G3PDH 0 241.36 -5421.2 -5125.22 Cyt b, Myo, G3PDH 0 -5662.56 -5366.58 Cyt b-Myo-G3PDH* 0 295.98 Cyt b, Myo, G3PDH* 0 It is worth noting that the parsimony based ILD-test did not find a significant incongruence between the three gene partitions. The value of this observation is uncertain, however, as the ILD test is based on another optimality criterion (parsimony). Furthermore, the strength of the test and interpretation of the results have also been questioned (e.g., [32]) In conclusion, allowing partitions to have separate topology parameters put fewer restrictions on the data. Hence, we should expect to find a better fit of the model to the data. Bayes factors seem promising for evaluating the relative contribution of components to an evolutionary model. However, judging from the relative increase in model likelihood when unlinking topologies compared to e.g., adding parameters for rate variation, we would anticipate components in the substitution model (for example, allowing rate variation among lineages) to have more effects on accommodating incongruence in the data. That is, even if we find strong evidence for a model allowing separate topology parameters, this might not mean strong evidence for separate gene phylogenies, as long as vital components of the substitution model are still missing. For further discussions on Bayesian approaches to combined data issues see e.g., [25,26,33]. Phylogeny and morphological variation in typical antbirds Even though we are unable to conclusively tell whether the observed phylogenetic incongruence between the individual gene partitions is due to genuine differences in phylogeny, or to limitations in the models used, we believe that the tree obtained from the combined data set represents the best estimate of the true relationships within the typical antbird assemblage. Obviously, several relationships are strongly supported, by congruent recognition by the individual gene trees and/or by high nodal support values. Nevertheless, other relationships have to be regarded as tentative, and especially those where any of the individual gene trees gives a strong nodal support for an alternative topology. It is noticeable that, although the individual genes congruently support several terminal groups, basal relationships are generally less well resolved and more often in conflict. Even though this observation might be biased due to the use of improper molecular models when calculating the trees, biased mutation rate in studied genes, or a biased taxon sampling, it could indicate that the diversifications of typical antbirds was characterized by some rapid speciation bursts. There are only a few recent studies of typical antbirds with taxon samplings that includes representatives from several genera, but these studies show similar difficulties in resolving generic relationships. For example, in a study of phylogenetic relationships of Myrmotherula antwrens that included representatives from several other typical antbird genera, Hackett and Rosenberg [10] obtained considerably different topologies from plumage characters, allozyme and morphometric data, respectively. In addition, the phylogenetic relationships suggested from mitochondrial DNA sequence data within a partly comparable taxon sampling [9], have little resemblance to those in Hackett and Rosenberg [10]. The nodes between typical antbirds in the DNA-DNA hybridization "tapestry" by Sibley and Ahlquist [[7]: Figure 372] also contain a high degree of short branches. It is also apparent that earlier antbird taxonomists, using external morphology, had difficulties in their taxonomic decisions and interpretations of higher-level relationships. Ridgway [[34]: p. 9] expressed that "The classification of this group is very difficult, more so probably than in the case of any American family of birds". Hackett and Rosenberg [10] concluded that antwren speciation mainly has been followed by plumage differentiation (and to some degree size differentiation) rather than changes in body proportions. Overall, this evolutionary pattern, with great changes in plumage and more limited changes in body proportions, seems to characterize the entire typical antbird assemblage (in contrast to the situation in ovenbirds, where there is a great variation in body proportions but not in plumage characters). However, Hackett and Rosenberg [10] suggested that neither plumage nor morphometric data correctly predicted the genetic relationships among the studied taxa. Our results seem to support their assumption as the traditionally used plumage characters in typical antbirds, as stripes, wingbars, and general coloration; seem to be irregularly distributed in the phylogenetic tree. It is reasonable to assume that plumage characters in typical antbirds are variable to such a degree that they are of limited use in studies of higher-level relationships. High levels of homoplasy (convergences and reversals) in plumage characters have also been reported in other passerine birds e.g., in Australian scrubwrens [35] brush-finches [36], and in New World orioles [37]. However, if excluding members in the "basal" group (clade A, Figure 4) and a few other aberrant taxa, the division of typical antbirds into the two main lineages in our phylogeny (clade B and C, Figure 4) is overall in good agreement with their body proportions (although there is a considerable size variation within both clades). The antshrikes (excluding Tamnistes and Pygiptila), antvireos and Herpsilochmus antwrens in clade B (Figure 4) are all more or less robust birds with heavy and prominently hooked bills, and many of them have a barred plumage pattern. The taxa in clade C (Figure 4), which includes most antwren genera, the Myrmeciza antbirds, the "professional" ant-following antbirds and some allied species, are generally slimmer birds with longer, thinner bills that have a less prominent hook. Most suggested relationships within clade B and C are in good agreement with traditional classifications. The recognition of monophyletic origins of most of the "professional" ant-following taxa (Phaenostictus, Gymnopithys, Rhegmatorhina, Pithys and Phlegopsis) and the "large" antshrikes (Taraba, Hypoedaleus, Batara, Frederickena and Mackenziaena) are two examples where our results are congruent with traditional classifications. The suggested relationships between the Hypocnemis and Drymophila antbirds, and the Herpsilochmus antwrens and the antvireos (Dysithamnus), respectively, have also been proposed previously based on molecular data [9,10]. Unfortunately, the genera Biatas, Clytoctantes, Percnostola, Rhopornis, Stymphalornis and Xenornis were lacking in our study; while most of these should probably be referred to Clade C, Biatas is difficult to place. Some novel relationships and the phylogenetic positions of some aberrant taxa For certain taxa the position in our combined phylogeny is unexpected considering the external morphology and traditional classification. Most noticeable are the position of the banded antbird (Dichrozona cincta), which is nested within the clade with antshrikes, antvireos and Herpsilochmus antwrens (clade B, Figure 4), and the position of the wing-banded antbird (Myrmornis torquata) as sister to the russet antshrike (Thamnistes anabatinus) and the spot-winged antshrike (Pygiptila stellaris) (clade A, Figure 4). However, the increased number of molecular based phylogenies in recent years have led to discoveries of several examples, at different phylogenetic levels, were birds have been misclassified due to significant morphological differences from the taxa to which they are most closely related [38-40]. The phylogenetic position of the wing-banded antbird (Myrmornis torquata) has long been obscured and it was long placed with the typical army-ant followers (e.g., [2]). The wing-banded antbird has also been suspected to be related to ground antbirds (Formicariidae sensu [7]) based on similarities in morphology and general appearance [7]. Our results confidently place it within typical antbirds, a conclusion further supported by its vocalization [2] and choice of nest site and its white egg [41]. The well supported relationship to the arboreal russet antshrike (Thamnistes anabatinus) and spot-winged antshrike (Pygiptila stellaris), suggested by our data, has apparently been obscured by structural differences caused by its adaptation to a terrestrial life-style shared with for example the antthrushes. A similar explanation may apply to the peculiar position of the banded antbird (Dichrozona cincta) in the combined phylogeny, as this taxon is also a mainly terrestrial bird, unlike the other members in the "antshrike" clade (clade B, Figure 4). The fact that the banded antbird has a rather long branch in the combined tree and that its phylogenetic position alter between the individual gene trees, leads us to consider the phylogenetic position of the banded antbird (Dichrozona cincta) as preliminary. However, it is obvious that it is not closely related to the Hylophylax antbirds with which it has traditionally been grouped (based on similarities in plumage patterns and weak sexual dimorphism). It should be noted that, due to the peculiar position of Dichrozona cincta, a second individual (ZMUC 128217) have been sequenced for all three genes. There were no variation at all found between the two individuals in G3PDH, in myoglobin 1 ambiguous position were found, and in cytochrome b 24 base pairs (2.4%) that differed as well as 3 ambiguous positions were found. Overall, this variation is within the variation that could be suspected between individuals within a species. Thus, the strange position of Dichrozona cincta in our analyses is unlikely to be due to sample or sequence mix-up. There are several other, less striking examples where the position of taxa in our phylogeny conflicts with relationships suggested in classifications based on external morphology. The Herpsilochmus antwrens for example (traditionally placed among Myrmotherula, Microrhopias and Formicivora antwrens), are quite different in appearance from their sister group Dysithamnus in being rather slim, lacking a particularly hook-bill, and in having a distinctly patterned plumage (however, as discussed above a close relationship between Herpsilochmus and Dysithamnus is also supported by an independent molecular study). Other examples are the positions of Myrmorchilus and Neoctantes, respectively (see discussion below). In these cases their true affinities may have been obscured by morphological adaptations to habitats or food sources that differ from those preferred by their closest relatives. The strong support in the combined tree for basal positions of Myrmornis, Pygiptila, Thamnistes and Terenura relative to all other typical antbirds is maybe the most unexpected result of our study. In a majority of classifications Terenura is placed close to other antwrens, but with no strong data support. Although the precise position of the Terenura antwrens is partly ambiguous in our analysis, they obviously belong to an ancient radiation that is only distantly related to the other "antwrens". The Terenura antwrens differ from other "antwrens" in plumage pattern and in being more slender and warbler-like with a thinner bill and longer tail. In a study based on mitochondrial DNA the position of Terenura was ambiguous depending on how the data set was analyzed [9] but clearly it was not closely related to the other taxa included in that study (e.g., Myrmotherula, Formicivora, Herpsilochmus, Hypocnemis, Drymophila). The well-supported phylogenetic position of Pygiptila and Thamnistes as the sistergroup to Myrmornis (instead of being close to other antshrikes as suggested in many linear classifications), is novel. However, Pygiptila and Thamnistes resemble each other in their ways of feeding in the sub-canopy, Thamnistes also resembling the Pygiptila female in appearance, and differing from most antshrikes in feeding behavior. DNA-DNA hybridization data [7] and protein electrophoresis [10] have previously shown Pygiptila to be genetically distant from the Thamnophilus antshrikes. The general external resemblance of Pygiptila and Thamnistes to other antshrikes is therefore best explained, as being plesiomorphic, and this may also be the case with their suspended nest-type. The polyphyly of Myrmotherula antwrens and Myrmeciza antbirds Our results confirm both previous molecular studies that suggest the Myrmotherula antwrens are polyphyletic [9,10], and the suspicion based on morphology that also the rather diverse genus Myrmeciza constitutes an unnatural taxon [3]. Nevetheless, most Myrmeciza antbirds studied herein belong to the same clade, although they are not monophyletic as several other genera (Myrmoborus, Gymnocichla, Pyriglena, Sclateria, Schistocichla, Hypocnemoides, and Hylophylax) are nested among them. However, the chestnut-tailed antbird (Myrmeciza hemimelaena), which represents a group of small and slim Myrmeciza antbirds with prominent wing spots in both sexes, groups with the Drymophila, Hypocnemis and Cercomacra antbirds. The small and slim Myrmeciza antbirds resembles morphologically the Hypocnemis antbirds in having similar wing spots as well as a rather short and rufous-brown tail. The clade that includes the remaining Myrmeciza antbirds consists of three unresolved lineage. The first includes a group of large and heavily built Myrmeciza antbirds (represented by Myrmeciza fortis). Next outside this group is the fire-eye (Pyriglena leuconota), followed by the bare-crowned antbird (Gymnocichla nudiceps) and the Myrmoborus antbird representative (Myrmoborus myotherinus). These taxa have rather stout bodies and in most cases red eyes. Both the fire-eyes and the bare-crowned antbird were previously assumed to be related to the large, heavy-billed Myrmeciza antbirds (e.g., [3]). The second lineage consists of the silvered antbird (Sclateria naevia) and the Schistocichla antbird representative (Schistocichla leucostigma). These relationships are in good agreement with the overall plumage characters in these taxa [3], with the males being rather uniform gray while the females are rufous. Such a plumage is also found in the genus Percnostola, with which the Schistocichla antbirds are considered to be most closely related (Schistocichla and Percnostola have even been regarded as congeneric, but it has also been suggested that Percnostola could be polyphyletic). In the third lineage, Myrmeciza griseiceps and Myrmeciza berlepschi form the sister clade to Myrmeciza loricata, Hypocnemoides maculicauda and Hylophylax naevia (the latter two are sister taxa). This group consists of rather typical shaped and sized "Myrmeciza" antbirds. Although it has a shorter tail, Hylophylax naevia shares plumage pattern with Myrmeciza loricata (Hypocnemoides maculicauda is more discretely patterned), while Myrmeciza griseiceps and Myrmeciza berleschi, on the other hand, are more uniformly colored birds. A non-monophyletic origin of Myrmotherula antwrens, suggested by our data, agrees with the results of previous molecular studies [9,10]. The results also support Hackett and Rosenberg's [10] protein electrophoresis data suggesting that the "gray" and "streaked" forms of Myrmotherula antwrens are more closely related to each other than either is to the "checker-throated" forms. The combined tree (Figure 4, clade C) suggests that the Myrmotherula antwrens evolved along two separate phylogenetic lineages. In the first, the "checker-throated" forms (Myrmotherula fulviventris and Myrmotherula leucophthalma) group with the black bushbird (Neoctantes niger) and constitute the sister to the dot-winged antwren (Microrhopias quixensis) and the stripe-backed antbird (Myrmorchilus strigilatus). Based on the external morphology these taxa indeed constitute a rather heterogeneous group. For example, the stripe-backed antbird has previously been suggested to be related to Formicivora and Drymophila antwrens [42], which are distantly related according to our results. However, Neoctantes, Microrhopias and Myrmorchilus are monotypic genera that lack obvious close relatives. Myrmorchilus is essentially a terrestrial bird, living in chaco scrub, thus differing in habits and habitat from the "typical" antwren lifestyle. Neoctantes lives in humid forest like most Myrmotherula antwrens, but its bill is modified to hammers on stems, vines etc., and to be used as a wedge to pry off strips of bark [2]. The morphological differences between Neoctantes and Myrmorchilus on one hand, and the "checker-throated" Myrmotherula antwrens on the other, could thus be the result of adaptive specializations in the former taxa. In the second lineage of Myrmotherula antwrens, the "streaked" forms represented by the short-billed antwren (Myrmotherula obscura) and the black-and-white antbird (Myrmochanes hemileucus) form the sister group to the "gray" forms (represented by Myrmotherula menetriesii, axillaris and behni) and Formicivora rufa. Although the support for nesting Formicivora rufa among the "gray" forms of Myrmotherula is rather weak, it suggests that the generic boundary between Formicivora and "gray" Myrmotherula antwren is far from unambiguously settled. This is also indicated by the recent transfer of the black-hooded antwren from the genus Myrmotherula to Formicivora [15]. Bates et al. [9] also found a close relationship between Myrmotherula longipennis (belonging to the "gray" form of Myrmotherula antwrens) and the genus Formicivora (Formicivora grisea and Formicivora rufa). Conclusions The phylogenetic results support that most antbirds could be divided into two major clades that are in broad agreement with traditional classifications. The first clade includes most antshrike genera, antvireos and the Herpsilochmus antwrens, while the second clade consists of the Myrmeciza antbirds, the "professional" ant-following antbirds, and allied. However, some relationships within these clades, as well as the support for that Terenura antwrens, the wing-banded antbird (Myrmornis torquata), the spot-winged antshrike (Pygiptila stellaris) and the russet antshrike (Thamnistes anabatinus) are basal to all other typical antbirds, are unexpected based on external morphology. Possibly the true affinities of these taxa have been obscured by morphological convergence due to adaptations to new habitats or food sources. Our results also strongly support that both the Myrmeciza antbirds and the Myrmotherula antwrens are unnatural groupings in need for taxonomic revisions. Also certain other taxa may be unnatural units, but definitive conclusions must await future analyses involving more taxa. Bayes factors seem promising for evaluating the relative contribution of components to an evolutionary model. However, changing a component of the nucleotide substitution model, e.g. adding parameters to model rate variation, had much higher impact on the model likelihood than unlinking parameters among data partition. Thus, even though strong evidence for a model allowing separate topology parameters is found, this might not mean strong evidence for separate gene phylogenies, as long as vital components of the substitution model are still missing. Methods Taxon sampling, amplification and sequencing Totally 51 typical antbird species were selected for the molecular analyses, including representatives from 38 genera out of 45 genera recognized by Ridgely and Tudor [3]. From some antbird genera (Myrmeciza, Myrmotherula and Thamnophilus) several species were included, as the monophyly for these genera had been questioned [3,9,10]. The phylogenetic trees were rooted using representatives from major furnariid lineages suggested by Irestedt et al. [1]. Sample identifications and GenBank accession numbers are given in Table 3 (see additional file 1 ). Nucleotide sequence data were obtained from two nuclear introns, myoglobin intron 2 and the glyceraldehydes-3-phosphodehydrogenase (G3PDH) intron 11, and from the mitochondrial cytochrome b gene. The complete myoglobin intron 2 (along with 13 bp and 10 bp of the flanking regions of exons 2 and 3, respectively) corresponding to the region between positions 303 (exon 2) and 400 (exon 3) in humans (GenBank accession number XM009949) and the complete G3PDH intron 11 (including 36 bp and 18 bp of exons 11 and 12, respectively) corresponding to the region 3915 to 4327 in Gallus gallus (GenBank accession number M11213) were sequenced. From the cytochrome b gene 999 bp were obtained corresponding to positions 15037 to 16035 in the chicken mitochondrial genome sequence [43]. Some indels were observed in the alignments of myoglobin intron 2 and the G3PDH intron 11, respectively (see results), but all gaps in the sequences were treated as missing data in the analyses. No insertions, deletions, stop or nonsense codons were observed in any of the cytochrome b sequences. Extraction, amplification and sequencing procedures for cytochrome b and myoglobin intron 2 follow the descriptions in Ericson et al. [44] and Irestedt et al. [1]. A protocol described by Fjeldså et al. [45] was followed for the amplification and sequencing of the G3PDH intron. For each gene and taxon, multiple sequence fragments were obtained by sequencing with different primers. These sequences were assembled to complete sequences with SeqMan II™ (DNASTAR inc.). Positions where the nucleotide could not be determined with certainty were coded with the appropriate IUPAC code. Due to a rather low number of insertions in myoglobin intron 2 and G3PDH intron 11 the combined sequences could easily be aligned by eye. Phylogenetic inference and model selection We used Bayesian inference and Markov chain Monte Carlo (MCMC) for estimating phylogenetic hypothesis from DNA data (see recent reviews by Holder and Lewis, [46]; Huelsenbeck et al., [47]). Bayesian inference of phylogeny aims at estimating the posterior probabilities of trees and other parameters of an evolutionary model. Importantly, two components need to be specified (apart from the data): the model of nucleotide substitution and the prior distributions for the parameters in that model. The models for nucleotide substitutions were selected for each gene individually, prior to the MCMC, and using the Akaike Information Criterion (AIC [48]). This was done using the program MrModeltest [49] in conjunction with PAUP* [50]. Specifically, MrModeltest compares 24 standard substitution models, including models allowing rate variation, utilizing the likelihood scores calculated by PAUP* on an initial, approximate phylogeny (see e.g., [51]). After models had been selected for the individual gene partitions, prior distributions for the model parameters were specified. For stationary state frequencies, we used a flat Dirichlet prior, Dir(1, 1, 1, 1). A Dirichlet prior, Dir(1, 1, 1, 1, 1, 1) were also used for the nucleotide substitution rate ratios of the general time-reversible model (GTR [52-54]). A Beta distribution, Beta(1, 1), were used for the transition/transversion rate ratio of the Hasegawa-Kishino-Yano model (HKY [55]). A uniform prior, Uni(0.1, 50), was used on the shape parameter of the gamma distribution of rate variation (Γ [56]), and a Uni(0, 1) prior was used for the proportion of invariable sites (I [57]). An exponential prior, Exp(10), were used for branch lengths, and all trees were assumed to be equally likely (flat prior on topology). The posterior probabilities of trees and parameters in the substitution models were approximated with MCMC and Metropolis coupling using the program MrBayes [58]. The gene partitions were analyzed both separately and combined. In the combined analysis, each gene partition was allowed to have separate parameters by using a rate multiplier [27,58,59]. One cold and three incrementally heated chains were run for 3 million generations, with a random starting tree and a temperature parameter value of 0.2. Trees were sampled every 100th generations, and the trees sampled during the burn-in phase (i.e., before the chain had reached its apparent target distribution) were discarded. Two runs, starting from different, randomly chosen trees, were made to ensure that the individual runs had converged on the same target distribution [60]. Convergence of parameters was checked by examining parameter means and variances between runs. After checking for convergence, final inference was made from the concatenated output from the two runs. A Bayesian test of incongruence Bayesian methods provide us ways not only to estimate posterior probabilities for trees and parameters in a model, but also to evaluate the model itself. Bayes factors [61], allow us to make sophisticated comparisons between models used in phylogenetic analyses [27,62,63]. Bayes factors measure the strength of evidence in favor of one model M1 compared to another M2, given the data X, and is calculated as the ratio of the model likelihoods, B12 = f(X|M1)/ f(X|M2). The model likelihoods f(X|Mi) are difficult to calculate analytically but can be estimated by using the output from an MCMC [27,62]. Here we explore the congruence test described by Nylander et al. [27], which utilizes Bayes factors. The test is not a significance test but merely compares the strength of evidence between two models of character evolution. In the first model, data partitions are allowed to have their own unique set of substitution parameters, but we assume the data as having evolved on the same topology, but with partition-specific branch lengths. Strictly speaking, we are restricting the data partitions to have the same posterior distribution for topologies, but (potentially) different distributions in all other parameters. In the second model we relax the assumption of a single distribution of topologies for all data partitions. That is, if the data partitions (genes) truly evolved on different phylogenies, they are allowed to do so in the model. The comparison or 'test' is to see if the second model provides compelling evidence as to be accepted as superior. Here we use the log of the Bayes factor and a value of >10 for 2 logB12 have been suggested as strong evidence against the alternative model, M2 [61]. To accomplish the incongruence test we utilized the unlink command in MrBayes, which allows the user to let parameters as well as topologies to be unlinked between partitions. We calculated Bayes factors and compared the effects on the model likelihood when linking or unlinking topologies between all the gene partitions. We were primarily interested in the potential incongruence between the mitochondrial cytochrome b partition and the two nuclear partitions myoglobin and G3PDH, but all combinations of the three genes in our data set were examined. For comparison, we also tested whether the different gene partitions were in significant conflict with each other by using the parsimony based incongruence-length differences test (ILD) [64], implemented in PAUP* [50]. The results are based on 10,000 replicates, with ten iterations (random additions of taxa) per replicate. Authors' contribution MI designed the study, carried out the labwork, participated in the phylogenetic analyses, and drafted the manuscript. JF assisted with the design of the study and with the draft of the manuscript. JN performed the phylogenetic analyses, drafted parts of the results, and material and methods section of the manuscript. PE conceived the study. All authors read and approved the manuscript. Supplementary Material Additional File 1 Table 3. Samples used in the study. The classification follows Ridgely and Tudor [3] for typical antbirds, and Irestedt et al. [1] for families. Abbreviations: AHMN = American Museum of Natural History, New York; FMNH = Field Museum of Natural History, Chicago; LSUMZ = Louisiana State University, Museum of Natural Science; NRM = Swedish Museum of Natural History; ZMCU = Zoological Museum of the University of Copenhagen. References: (1) Irestedt et al. [1]; (2) Fjeldså et al. [45]; (3) Johansson et al. [65]; Fjeldså et al. [66]. Click here for file Acknowledgements We are grateful to many people and institutions that have been involved in this work. Most tissue and blood samples were obtained from the Zoological Museum, University of Copenhagen (ZMUC) and the Swedish Museum of Natural History. Support to expeditions where tissue samples were acquired and stored at the ZMUC, was provided over many years by the Danish Natural Research Council (mainly grants 11-0380 and 9502155). Many samples at the Swedish Museum of Natural History were collected in Paraguay in collaboration with the Museo Nacional de Historia Natural del Paraguay, San Lorenzo. Important samples have also been obtained from the Field Museum, Chicago (Shannon Hackett, David E. Willard), Museum of Natural Science, Louisiana State University (Donna Dittman), and the American Museum of Natural History, New York (Paul Sweet). Jan Ohlson and Niels Krabbe are thanked for commenting on the manuscript. Mari Källersjö provided logistic support and advice for the work at the Molecular Systematics Laboratory at the Swedish Museum of Natural History, and Dario Zuccon is thanked for practical support at the laboratory. The Swedish Research Council (grant no. 621-2001-2773 to P.E.) funded the laboratory work. 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==== Front BMC GenomicsBMC Genomics1471-2164BioMed Central London 1471-2164-5-541531038810.1186/1471-2164-5-54Research ArticleFrom biomedicine to natural history research: EST resources for ambystomatid salamanders Putta Srikrishna 1sputt2@uky.eduSmith Jeramiah J 1jjsmit3@uky.eduWalker John A 1jawalk2@uky.eduRondet Mathieu 2mrondet@uci.eduWeisrock David W 1weisrock@uky.eduMonaghan James 1james.monaghan@uky.eduSamuels Amy K 1aksamu2@uky.eduKump Kevin 1kevinkump@gmail.comKing David C 3dck163@psu.eduManess Nicholas J 4njmaness@wisc.eduHabermann Bianca 5habermann@mpi-cbg.deTanaka Elly 6tanaka@mpi-cbg.deBryant Susan V 2svbryant@uci.eduGardiner David M 2dmgardin@uci.eduParichy David M 7dparichy@mail.utexas.eduVoss S Randal 1srvoss@uky.edu1 Department of Biology, University of Kentucky, Lexington, KY 40506, USA2 Department of Developmental and Cell Biology and the Developmental Biology Center, University of California, Irvine, CA 92697, USA3 The Life Sciences Consortium, 519 Wartik Laboratory, Penn State University, University Park, PA 16802, USA4 Department of Zoology, University of Wisconsin-Madison, 250 N. Mills, Madison, WI 53706, USA5 Scionics Computer Innovation GmbH, Pfotenhauerstrasse 110, 01307 Dresden, Germany6 Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstrasse 108, 01307 Dresden, Germany7 Section of Integrative Biology and Section of Molecular, Cell and Developmental Biology, Institute for Cellular and Molecular Biology, University of Texas, Austin, TX 78712, USA2004 13 8 2004 5 54 54 19 7 2004 13 8 2004 Copyright © 2004 Putta et al; licensee BioMed Central Ltd.2004Putta et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background Establishing genomic resources for closely related species will provide comparative insights that are crucial for understanding diversity and variability at multiple levels of biological organization. We developed ESTs for Mexican axolotl (Ambystoma mexicanum) and Eastern tiger salamander (A. tigrinum tigrinum), species with deep and diverse research histories. Results Approximately 40,000 quality cDNA sequences were isolated for these species from various tissues, including regenerating limb and tail. These sequences and an existing set of 16,030 cDNA sequences for A. mexicanum were processed to yield 35,413 and 20,599 high quality ESTs for A. mexicanum and A. t. tigrinum, respectively. Because the A. t. tigrinum ESTs were obtained primarily from a normalized library, an approximately equal number of contigs were obtained for each species, with 21,091 unique contigs identified overall. The 10,592 contigs that showed significant similarity to sequences from the human RefSeq database reflected a diverse array of molecular functions and biological processes, with many corresponding to genes expressed during spinal cord injury in rat and fin regeneration in zebrafish. To demonstrate the utility of these EST resources, we searched databases to identify probes for regeneration research, characterized intra- and interspecific nucleotide polymorphism, saturated a human – Ambystoma synteny group with marker loci, and extended PCR primer sets designed for A. mexicanum / A. t. tigrinum orthologues to a related tiger salamander species. Conclusions Our study highlights the value of developing resources in traditional model systems where the likelihood of information transfer to multiple, closely related taxa is high, thus simultaneously enabling both laboratory and natural history research. ==== Body Background Establishing genomic resources for closely related species will provide comparative insights that are crucial for understanding diversity and variability at multiple levels of biological organization. Expressed sequence tags (EST) are particularly useful genomic resources because they enable multiple lines of research and can be generated for any organism: ESTs allow the identification of molecular probes for developmental studies, provide clones for DNA microchip construction, reveal candidate genes for mutant phenotypes, and facilitate studies of genome structure and evolution. Furthermore, ESTs provide raw material from which strain-specific polymorphisms can be identified for use in population and quantitative genetic analyses. The utility of such resources can be tailored to target novel characteristics of organisms when ESTs are isolated from cell types and tissues that are actively being used by a particular research community, so as to bias the collection of sequences towards genes of special interest. Finally, EST resources produced for model organisms can greatly facilitate comparative and evolutionary studies when their uses are extended to other, closely related taxa. Salamanders (urodele amphibians) are traditional model organisms whose popularity was unsurpassed early in the 20th century. At their pinnacle, salamanders were the primary model for early vertebrate development. Embryological studies in particular revealed many basic mechanisms of development, including organizer and inducer regions of developing embryos [1]. Salamanders continue to be important vertebrate model organisms for regeneration because they have by far the greatest capacity to regenerate complex body parts in the adult phase. In contrast to mammals, which are not able to regenerate entire structures or organ systems upon injury or amputation, adult salamanders regenerate their limbs, tail, lens, retina, spinal cord, heart musculature, and jaw [2-7]. In addition, salamanders are the model of choice in a diversity of areas, including vision, embryogenesis, heart development, olfaction, chromosome structure, evolution, ecology, science education, and conservation biology [8-15]. All of these disciplines are in need of genomic resources as fewer than 4100 salamander nucleotide sequences had been deposited in GenBank as of 3/10/04. Here we describe results from an EST project for two ambystomatid salamanders: the Mexican axolotl, Ambystoma mexicanum and the eastern tiger salamander, A. tigrinum tigrinum. These two species are members of the Tiger Salamander Complex [16], a group of closely related species and subspecies that are widely distributed in North America. Phylogenetic reconstruction suggests that these species probably arose from a common ancestor about 10–15 million years ago [16]. Ambystoma mexicanum has a long research history of over 100 years and is now principally supplied to the research community by the Axolotl Colony [17], while A. t. tigrinum is obtained from natural populations in the eastern United States. Although closely related with equally large genomes (32 × 109 bp)[18], these two species and others of the Complex differ dramatically in life history: A. mexicanum is a paedomorphic species that retains many larval features and lives in water throughout it's life cycle while A. t. tigrinum undergoes a metamorphosis that is typical of many amphibians. Like many other traditional model organisms of the last century, interest in these two species declined during the rise of genetic models like the fly, zebrafish, and mouse [19]. However, "early" model organisms such as salamanders are beginning to re-attract attention as genome resources can rapidly be developed to exploit the unique features that originally identified their utility for research. We make this point below by showing how the development of ESTs for these two species is enabling research in several areas. Furthermore, we emphasize the value of developing resources in model systems where the likelihood of information transfer to multiple, closely related taxa is high, thus simultaneously enabling both laboratory and natural history research programs. Results and Discussion Selection of libraries for EST sequencing Eleven cDNA libraries were constructed using a variety of tissues (Table 1). Pilot sequencing of randomly selected clones revealed that the majority of the non-normalized libraries were moderate to highly redundant for relatively few transcripts. For example, hemoglobin-like transcripts represented 15–25% of the sampled clones from cDNA libraries V1, V2, and V6. Accordingly, we chose to focus our sequencing efforts on the non-normalized MATH library as well as the normalized AG library, which had lower levels of redundancy (5.5 and 0.25% globins, respectively). By concentrating our sequencing efforts on these two libraries we obtained transcripts deriving primarily from regenerating larval tissues in A. mexicanum and several non-regenerating larval tissues in A. t. tigrinum. Table 1 Tissues selected to make cDNA libraries. ID Tissue cDNAs sequenced GARD limb blastema 1029 MATH limb blastema 16244 V1 tail blastema 1422 V2 brain 3196 V3 liver 792 V4 spleen 337 V5 heart 38 V6 gill 3039 V7 stage 22 embryo 96 AG liver, gonad, lung, kidney, heart, gill 19871 Further information is found in Methods and Materials. EST sequencing and clustering A total of 46,064 cDNA clones were sequenced, yielding 39,982 high quality sequences for A. mexicanum and A. t. tigrinum (Table 2). Of these, 3,745 corresponded to mtDNA and were removed from the dataset; complete mtDNA genome data for these and other ambystomatid species will be reported elsewhere. The remaining nuclear ESTs for each species were clustered and assembled separately. We included in our A. mexicanum assembly an additional 16,030 high quality ESTs that were generated recently for regenerating tail and neurula stage embryos [20]. Thus, a total of 32,891 and 19,376 ESTs were clustered for A. mexicanum and A. t. tigrinum, respectively. Using PaCE clustering and CAP3 assembly, a similar number of EST clusters and contigs were identified for each species (Table 2). Overall contig totals were 11,190 and 9,901 for A. mexicanum and A. t. tigrinum respectively. Thus, although 13,515 more A. mexicanum ESTs were assembled, a roughly equivalent number of contigs were obtained for both species. This indicates that EST development was more efficient for A. t. tigrinum, presumably because ESTs were obtained primarily from the normalized AG library; indeed, there were approximately twice as many ESTs on average per A. mexicanum contig (Table 2). Thus, our EST project yielded an approximately equivalent number of contigs for A. mexicanum and A. t. tigrinum, and overall we identified > 21,000 different contigs. Assuming that 20% of the contigs correspond to redundant loci, which has been found generally in large EST projects [21], we identified transcripts for approximately 17,000 different ambystomatid loci. If ambystomatid salamanders have approximately the same number of loci as other vertebrates (e.g. [22]), we have isolated roughly half the expected number of genes in the genome. Table 2 EST summary and assembly results. A. mex A. t. tig cDNA clones sequenced 21830 24234 high-quality sequences 19383 20599 mt DNA sequence 2522 1223 seqs submitted to NCBI 16861 19376 sequences assembled 32891a 19376  PaCE clusters 11381 10226  ESTs in contigs 25457 12676  contigs 3756 3201  singlets 7434 6700  putative transcripts 11190 9901 aIncludes 16,030 ESTs from [20]. Identification of vertebrate sequences similar to Ambystoma contigs We searched all contigs against several vertebrate databases to identify sequences that exhibited significant sequence similarity. As our objective was to reliably annotate as many contigs as possible, we first searched against 19,804 sequences in the NCBI human RefSeq database (Figure 1), which is actively reviewed and curated by biologists. This search revealed 5619 and 4973 "best hit" matches for the A. mexicanum and A. t. tigrinum EST datasets at a BLASTX threshold of E = 10-7. The majority of contigs were supported at more stringent E-value thresholds (Table 3). Non-matching contigs were subsequently searched against the Non-Redundant (nr) Protein database and Xenopus tropicalus and X. laevis UNIGENE ESTs (Figure 1). These later two searches yielded a few hundred more 'best hit' matches, however a relatively large number of ESTs from both ambystomatid species were not similar to any sequences from the databases above. Presumably, these non-matching sequences were obtained from the non-coding regions of transcripts or they contain protein-coding sequences that are novel to salamander. Although the majority are probably of the former type, we did identify 3,273 sequences from the non-matching set that had open reading frames (ORFs) of at least 200 bp, and 911 of these were greater than 300 bp. Figure 1 Results of BLASTX and TBLASTX searches to identify best BLAST hits for Ambystoma contigs searched against NCBI human RefSeq, nr, and Xenopus Unigene databases. Table 3 Ambystoma contig search of NCBI human RefSeq, nr, and Xenopus Unigene databases. A. mex A. t. tig # BLASTX Best Matches 6283 5545 < E-100 630 870 < E-50 > E-100 2015 1990 < E-20 > E-50 2153 1595 < E-10 > E-20 967 745 < E-7 > E-10 518 345 The distribution of ESTs among contigs can provide perspective on gene expression when clones are randomly sequenced from non-normalized cDNA libraries. In general, frequently sampled transcripts may be expressed at higher levels. We identified the 20 contigs from A. mexicanum and A. t. tigrinum that contained the most assembled ESTs (Table 4). The largest A. t. tigrinum contigs contained fewer ESTs than the largest A. mexicanum contigs, probably because fewer overall A. t. tigrinum clones were sequenced, with the majority selected from a normalized library. However, we note that the contig with the most ESTs was identified for A. t. tigrinum: delta globin. In both species, transcripts corresponding to globin genes were sampled more frequently than all other loci. This may reflect the fact that amphibians, unlike mammals, have nucleated red blood cells that are transcriptionally active. In addition to globin transcripts, a few other house-keeping genes were identified in common from both species, however the majority of the contigs were unique to each list. Overall, the strategy of sequencing cDNAs from a diverse collection of tissues (from normalized and non-normalized libraries) yielded different sets of highly redundant contigs. Only 25% and 28% of the A. mexicanum and A. t. tigrinum contigs, respectively, were identified in common (Figure 2). We also note that several hundred contigs were identified in common between Xenopus and Ambystoma; this will help facilitate comparative studies among these amphibian models. Table 4 Top 20 contigs with the most assembled ESTs. Contig ID # ESTs Best Human Match E-value MexCluster_4615_Contig1 415 (NM_000519) delta globin E-39 MexCluster_600_Contig1 354 (NM_182985) ring finger protein 36 isoform a E-110 MexCluster_6279_Contig1 337 (NM_000559) A-gamma globin E-32 MexCluster_10867_Contig1 320 (NM_000558) alpha 1 globin E-38 MexCluster_5357_Contig1 307 (NM_000558) alpha 1 globin E-37 MexCluster_9285_Contig3 285 (NM_001614) actin, gamma 1 propeptide 0 MexCluster_7987_Contig3 252 (NM_001402) eukaryotic translation elongation f1 0 MexCluster_9285_Contig1 240 (NM_001101) beta actin; beta cytoskeletal actin 0 MexCluster_9279_Contig3 218 (NM_000223) keratin 12 E-113 MexCluster_11203_Contig1 181 (NM_002032) ferritin, heavy polypeptide 1 E-70 MexCluster_8737_Contig2 152 (NM_058242) keratin 6C E-131 MexCluster_3193_Contig1 145 (NM_004499) heterogeneous nuclear ribonucleoprotein E-90 MexCluster_8737_Contig7 134 (NM_058242) keratin 6C E-131 MexCluster_5005_Contig3 132 (NM_031263) heterogeneous nuclear ribonucleoprotein E-124 MexCluster_6225_Contig1 125 (NM_001152) solute carrier family 25, member 5 E-151 MexCluster_1066_Contig1 122 [31015660] IMAGE:6953586 E-16 MexCluster_8737_Contig4 114 (NM_058242) keratin 6C; keratin, epidermal type II E-132 MexCluster_8187_Contig2 113 (NM_005507) cofilin 1 (non-muscle) E-65 MexCluster_2761_Contig1 109 (NM_001961) eukaryotic translation elongation factor2 0 MexCluster_9187_Contig1 105 (NM_007355) heat shock 90 kDa protein 1, beta 0 A. t. tigrinum TigCluster_6298_Contig1 654 (NM_000519) delta globin E-38 TigCluster_10099_Contig2 193 (NM_001614) actin, gamma 1 propeptide 0 TigCluster_6470_Contig1 167 (NM_000558) alpha 1 globin E-39 TigCluster_9728_Contig2 142 (NM_000477) albumin precursor E-140 TigCluster_6594_Contig1 117 (NM_001402) eukaryotic translation elongation f1 0 TigCluster_5960_Contig1 91 (NM_001101) beta actin; beta cytoskeletal actin 0 TigCluster_7383_Contig1 77 (NM_001614) actin, gamma 1 propeptide 0 TigCluster_6645_Contig1 76 (NM_001063) transferrin 0 TigCluster_7226_Contig4 74 (NM_006009) tubulin, alpha 3 E-160 TigCluster_7191_Contig1 67 (NM_019016) keratin 24 E-89 TigCluster_10121_Contig1 64 (NM_005141) fibrinogen, beta chain preproprotein 0 TigCluster_6705_Contig1 63 (NM_000558) alpha 1 globin E-39 TigCluster_7854_Contig1 62 (NM_021870) fibrinogen, gamma chain isoform E-121 TigCluster_6139_Contig1 52 (NM_001404) eukaryotic translation elongation f1 0 TigCluster_7226_Contig2 51 (NM_006009) tubulin, alpha 3 0 TigCluster_10231_Contig1 44 (NM_003018) surfactant, pulmonary-associated prot. E-08 TigCluster_6619_Contig1 36 (NM_000041) apolipoprotein E E-38 TigCluster_7232_Contig2 35 (NM_003651) cold shock domain protein A E-46 TigCluster_5768_Contig1 34 (NM_003380) vimentin E-177 TigCluster_9784_Contig3 32 |XP_218445.1| similar to RIKEN cDNA 1810065E05 E-15 Figure 2 Venn diagram of BLAST comparisons among amphibian EST projects. Values provided are numbers of reciprocal best BLAST hits (E<10-20) among quality masked A. mexicanum and A. t. tigrinum assemblies and a publicly available X. tropicalis EST assembly Functional annotation For the 10,592 contigs that showed significant similarity to sequences from the human RefSeq database, we obtained Gene Ontology (23) information to describe ESTs in functional terms. Although there are hundreds of possible annotations, we chose a list of descriptors for molecular and biological processes that we believe are of interest for research programs currently utilizing salamanders as model organisms (Table 5). In all searches, we counted each match between a contig and a RefSeq sequence as identifying a different ambystomatid gene, even when different contigs matched the same RefSeq reference. In almost all cases, approximately the same number of matches was found per functional descriptor for both species. This was not simply because the same loci were being identified for both species, as only 20% of the total number of searched contigs shared sufficient identity (BLASTN; E<10-80 or E<10-20) to be potential homologues. In this sense, the sequencing effort between these two species was complementary in yielding a more diverse collection of ESTs that were highly similar to human gene sequences. Table 5 Functional annotation of contigs A. mex A. t. tig Molecular Function (0016209)  antioxidant (0016209) 25 29  binding (0005488) 3117 2578  chaparone (0003754) 100 85  enzyme regulation (003023) 193 223  motor (0003774) 73 75  signal transduction (0004871) 344 375  structural protein (0005198) 501 411  transcriptional reg. (0030528) 296 221  translational reg. (0045182) 94 59  bone remodeling (0046849) 8 8  circulation (0008015) 23 78  immune response (000695) 182 263  respiratory ex. (0009605) 254 288  respiratory in. (0009719) 72 58  stress (0006950) 263 320 Biological Process (0008150) Cellular (0009987)  activation (0001775) 4 6  aging and death (0008219) 158 148  communication (0007154) 701 696  differentiation (0030154) 31 20  extracellular mat. (0043062) 4 4  growth and main. (0008151) 1731 1445  migration (0016477) 8 14  motility (0006928) 163 154 Developmental (0007275)  aging (0007568) 32 21  embryonic (0009790) 6 1  growth (0040007) 2 2  morphogenesis (0009653) 350 272  pigment (0048066) 13 26  post embryonic (0009791) 8 13  reproduction (0000003) 42 27 Physiological (0007582)  coagulation (0050817) 22 73  death and aging (0016265) 159 148  homeostasis (0042592) 22 27  metabolism (0008152) 3059 2513  secretion (0046903) 9 16  sex differentiation (0007548) 3 2 Numbers in parentheses reference GO numbers [23]. Informatic searches for regeneration probes The value of a salamander model to regeneration research will ultimately rest on the ease in which data and results can be cross-referenced to other vertebrate models. For example, differences in the ability of mammals and salamanders to regenerate spinal cord may reflect differences in the way cells of the ependymal layer respond to injury. As is observed in salamanders, ependymal cells in adult mammals also proliferate and differentiate after spinal cord injury (SCI) [24,25]; immediately after contusion injury in adult rat, ependymal cell numbers increase and proliferation continues for at least 4 days [[26]; but see [27]]. Rat ependymal cells share some of the same gene expression and protein properties of embryonic stem cells [28], however no new neurons have been observed to derive from these cells in vivo after SCI [29]. Thus, although endogenous neural progenitors of the ependymal layer may have latent regenerative potential in adult mammals, this potential is not realized. Several recently completed microarray analyses of spinal cord injury in rat now make it possible to cross-reference information between amphibians and mammals. For example, we searched the complete list of significantly up and down regulated genes from Carmel et al. [30] and Song et al. [31] against all Ambystoma ESTs. Based upon amino acid sequence similarity of translated ESTs (TBLASTX; E<10-7), we identified DNA sequences corresponding to 69 of these 164 SCI rat genes (Table 6). It is likely that we have sequence corresponding to other presumptive orthologues from this list as many of our ESTs only contain a portion of the coding sequence or the untranslated regions (UTR), and in many cases our searches identified closely related gene family members. Thus, many of the genes that show interesting expression patterns after SCI in rat can now be examined in salamander. Table 6 Ambystoma contigs that show sequence similarity to rat spinal cord injury genes. Ambystoma Contig ID RAT cDNA clone E-value MexCluster_7440_Contig1 gi|1150557|c-myc, exon 2 E-29 MexCluster_4624_Contig1 gi|1468968| brain acyl-CoA synthtase II E-09 TigCluster_4083_Contig1 E-09 TigSingletonClusters_Salamander_4_G20_ab1 gi|1552375| SKR6 gene, a CB1 cannabinoid recept. E-08 MexSingletonClusters_NT009B_B04 gi|17352488| cyclin ania-6a E-46 TigCluster_3719_Contig1 E-114 TigCluster_8423_Contig1 gi|1778068| binding zyginI E-102 TigCluster_7064_Contig1 gi|1836160| Ca2+/calmodulin-dependent E-20 MexCluster_3225_Contig1 gi|1906612| Rattus norvegicus CXC chemokine E-68 TigSingletonClusters_Salamander_13_F03_ab1 E-38 MexSingletonClusters_BL285B_A06 gi|203042| (Na+, K+)-ATPase-beta-2 subunit E-63 TigCluster_6994_Contig1 E-65 MexSingletonClusters_BL014B_F12 gi|203048| plasma membrane Ca2+ ATPase-isoform 2 E-112 TigSingletonClusters_Salamander_5_F07_ab1 E-92 MexCluster_1251_Contig1 gi|203167| GTP-binding protein (G-alpha-i1) E-110 TigSingletonClusters_Salamander_3_P14_ab1 E-152 TigSingletonClusters_Salamander_22_B01_ab1 gi|203336| catechol-O-methyltransferase E-47 TigSingletonClusters_Salamander_17_N04_ab1 gi|203467| voltage-gated K+ channel protein (RK5) E-08 MexSingletonClusters_v1_p8_c16_triplex5ld_ gi|203583| cytosolic retinol-binding protein (CRBP) E-77 TigCluster_6321_Contig1 E-18 MexCluster_5399_Contig1 gi|204647| heme oxygenase gene E-67 TigCluster_2577_Contig1 E-67 MexCluster_4647_Contig1 gi|204664| heat shock protein 27 (Hsp27) E-83 TigSingletonClusters_Salamander_12_M05_ab1 E-51 MexSingletonClusters_BL285C_F02 gi|205404| metabotropic glutamate receptor 3 E-41 TigSingletonClusters_Salamander_2_B24_ab1 gi|205508| myelin/oligodendrocyte glycoprotein E-26 TigCluster_5740_V2_p10_M20_TriplEx5ld_ gi|205531| metallothionein-2 and metallothionein 1 E-08 TigSingletonClusters_V2_p5_A2_TriplEx5ld_ gi|205537| microtubule-associated protein 1A E-59 MexCluster_1645_Contig1 gi|205633| Na, K-ATPase alpha-2 subunit E-149 TigSingletonClusters_Contig328 0 TigSingletonClusters_Contig45 gi|205683| smallest neurofilament protein (NF-L) E-63 MexSingletonClusters_NT016A_A09 gi|205693| nerve growth factor-induced (NGFI-A) E-95 TigSingletonClusters_I09_Ag2_p9_K24_M13R E-24 MexSingletonClusters_NT007A_E07 gi|205754| neuronal protein (NP25) E-64 TigCluster_7148_Contig1 E-57 MexCluster_9504_Contig1 gi|206161| peripheral-type benzodiazepine receptor E-73 MexSingletonClusters_BL016B_B02 gi|206166| protein kinase C type III E-36 TigCluster_981_Contig1 E-27 MexSingletonClusters_nm_19_k3_t3_ gi|206170| brain type II Ca2+/calmodulin-dependent E-117 MexSingletonClusters_v11_p42_j20_t3_049_ab1 gi|207138| norvegicus syntaxin B 1e-079 MexSingletonClusters_nm_14_h19_t3_ gi|207473| neural receptor protein-tyrosine kinase E-40 TigSingletonClusters_Contig336 E-34 TigSingletonClusters_E10_Ag2_p18_O19_M13 gi|2116627| SNAP-25A E-123 MexCluster_211_Contig1 gi|220713| calcineurin A alpha E-63 TigSingletonClusters_Salamander_7_K14_ab1 E-87 MexSingletonClusters_NT014A_G03 gi|220839| platelet-derived growth factor A chain E-21 TigSingletonClusters_Salamander_9_M15_ab1 E-56 TigSingletonClusters_Salamander_19_M06_ab1 gi|2501807| brain digoxin carrier protein E-55 MexSingletonClusters_Contig100 gi|2746069| MAP-kinase phosphatase (cpg21) E-108 TigSingletonClusters_Salamander_11_A16_ab1 E-70 MexCluster_8345_Contig1 gi|2832312| survival motor neuron (smn) E-40 TigCluster_8032_Contig1 E-49 MexCluster_3580_Contig1 gi|294567| heat shock protein 70 (HSP70) 0 TigCluster_8592_Contig2 E-161 TigSingletonClusters_Salamander_17_N08_ab1 gi|2961528| carboxyl-terminal PDZ E-10 MexSingletonClusters_BL286C_D09 gi|298325| sodium-dependent neurotransmitter tran. E-12 TigSingletonClusters_Contig95 E-22 MexSingletonClusters_Contig461 gi|2996031| brain finger protein (BFP) E-08 TigSingletonClusters_Salamander_11_O19_ab1 E-23 TigSingletonClusters_E16_Ag2_p8_O20_M13R gi|3135196| Ca2+/calmodulin-dependent E-33 MexSingletonClusters_Contig188 gi|3252500| CC chemokine receptor protein E-15 MexCluster_6961_Contig1 gi|3319323| suppressor of cytokine signaling-3 E-08 MexSingletonClusters_nm_14_p15_t3_ gi|349552| P-selectin E-16 TigCluster_218_Contig2 E-99 MexSingletonClusters_Contig506 gi|3707306| Normalized rat embryo, cDNA clone E-14 TigSingletonClusters_I16_Ag2_p5_N7_M13R gi|3711670| Normalized rat muscle, cDNA clone E-35 MexSingletonClusters_V1_p1_a10_Triplex5Ld gi|3727094| Normalized rat ovary, cDNA clone E-15 TigSingletonClusters_v2_p1_D20_triplex5ld E-16 MexSingletonClusters_NT005B_F02 gi|3811504| Normalized rat brain, cDNA clone E-35 TigSingletonClusters_Salamander_22_I04_ab1 E-34 TigSingletonClusters_Ag2_p34_N23_M13R gi|405556| adenylyl cyclase-activated serotonin E-17 TigSingletonClusters_Salamander_1_H02_ab1 gi|4103371| putative potassium channel TWIK E-22 MexCluster_4589_Contig1 gi|4135567| Normalized rat embryo, cDNA clone E-32 TigSingletonClusters_Contig220 E-09 TigCluster_4093_Contig1 gi|4228395| cDNA clone UI-R-A0-bc-h-02-0-UI E-104 MexSingletonClusters_nm_21_2_m7_t3_ gi|425471| nuclear factor kappa B p105 subunit E-22 TigCluster_8535_Contig1 E-11 MexSingletonClusters_v6_p1_j6_triplex5_1ld_ gi|430718| Sprague Dawley inducible nitric oxide E-13 TigSingletonClusters_Salamander_15_D22_ab1 E-41 MexCluster_3498_Contig1 gi|436934| Sprague Dawley protein kinase C rec. 0 TigCluster_6648_Contig1 0 MexSingletonClusters_BL279A_B12 gi|464196| phosphodiesterase I E-49 TigSingletonClusters_Salamander_25_P03_ab1 E-75 MexCluster_8708_Contig1 gi|466438| 40kDa ribosomal protein E-168 TigCluster_5877_Contig1 E-168 MexSingletonClusters_nm_14_a9_t3_ gi|493208| stress activated protein kinase alpha II E-51 TigSingletonClusters_Salamander_11_A13_ab1 gi|517393| tau microtubule-associated protein E-44 TigSingletonClusters_Salamander_12_J14_ab1 gi|55933| c-fos E-26 MexSingletonClusters_nm_21_2_l13_t3_ gi|56822| major synaptic vesicel protein p38 E-39 TigCluster_2065_Contig1 E-50 MexCluster_10965_Contig1 gi|56828| nuclear oncoprotein p53 E-75 TigCluster_5315_Contig1 E-66 MexCluster_4245_Contig1 gi|56909| pJunB gene E-50 TigSingletonClusters_G05_Ag2_p9_G8_M13R E-09 MexSingletonClusters_NT013D_C12 gi|56919| region fragment for protein kinase C E-33 TigSingletonClusters_Salamander_21_H19_ab1 E-24 MexCluster_9585_Contig1 gi|57007| ras-related mRNA rab3 E-61 TigCluster_4885_Contig1 E-63 TigSingletonClusters_Salamander_1_M03_ab1 gi|57238| silencer factor B E-13 MexSingletonClusters_NT008B_D05 gi|57341| transforming growth factor-beta 1 E-13 TigSingletonClusters_Salamander_24_I16_ab1 E-20 MexCluster_9533_Contig1 gi|57479| vimentin 0 TigCluster_5768_Contig1 0 MexSingletonClusters_BL283B_A11 gi|596053| immediate early gene transcription E-12 TigSingletonClusters_Salamander_13_J19_ab1 E-16 MexSingletonClusters_v6_p4_j2_triplex5_1ld_ gi|790632| macrophage inflammatory protein-1alpha E-22 TigCluster_2146_Contig1 gi|951175| limbic system-associated membrane prot. E-11 MexSingletonClusters_v11_p54_o4_t3_ gi|971274| neurodegeneration associated protein 1 E-09 TigSingletonClusters_Salamander_2_J12_ab1 E-11 Similar gene expression programs may underlie regeneration of vertebrate appendages such as fish fins and tetrapod limbs. Regeneration could depend on reiterative expression of genes that function in patterning, morphogenesis, and metabolism during normal development and homeostasis. Or, regeneration could depend in part on novel genes that function exclusively in this process. We investigated these alternatives by searching A. mexicanum limb regeneration ESTs against UNIGENE zebrafish fin regeneration ESTs (Figure 3). This search identified 1357 significant BLAST hits (TBLASTX; E<10-7) that corresponded to 1058 unique zebrafish ESTs. We then asked whether any of these potential regeneration homologues were represented uniquely in limb and fin regeneration databases (and not in databases derived from other zebrafish tissues). A search of the 1058 zebrafish ESTs against > 400,000 zebrafish ESTs that were sampled from non-regenerating tissues revealed 43 that were unique to the zebrafish regeneration database (Table 7). Conceivably, these 43 ESTs may represent transcripts important to appendage regeneration. For example, our search identified several genes (e.g. hspc128, pre-B-cell colony enhancing factor 1, galectin 4, galectin 8) that may be expressed in progenitor cells that proliferate and differentiate during appendage regeneration. Overall, our results suggest that regeneration is achieved largely through the reiterative expression of genes having additional functions in other developmental contexts, however a small number of genes may be expressed uniquely during appendage regeneration. Figure 3 Results of BLASTN and TBLASTX searches to identify best BLAST hits for A. mexicanum regeneration ESTs searched against zebrafish EST databases. A total of 14,961 A. mexicanum limb regeneration ESTs were assembled into 4485 contigs for this search. Table 7 Ambystoma limb regeneration contigs that show sequence similarity to zebrafish fin regeneration ESTs Mex. Contigs Human ID E-value Zfish ID E-value Contig94 gi|10835079| 1e-63 gnl|UG|Dr#S12319632 1e-58 nm_30_a11_t3_ gi|32306539| 1e-58 gnl|UG|Dr#S12312602 1e-35 Contig615 gi|4502693| 1e-70 gnl|UG|Dr#S12313407 1e-34 nm_23_l13_t3_ No Human Hit gnl|UG|Dr#S12320916 1e-31 nm_9_e22_t3_ gi|4758788| 1e-98 gnl|UG|Dr#S12309914 1e-29 nm_8_l17_t3_ gi|21361310| 1e-16 gnl|UG|Dr#S12313396 1e-27 Contig531 gi|13775198| 1e-27 gnl|UG|Dr#S12309680 1e-26 Contig152 gi|5453712| 1e-32 gnl|UG|Dr#S12239884 1e-26 nm_32h_j20_t3_ gi|39777601| 1e-79 gnl|UG|Dr#S12136499 1e-25 Contig1011 gi|39752675| 1e-65 gnl|UG|Dr#S12136499 1e-24 v11_p50_b24_t3_ gi|41208832| 1e-36 gnl|UG|Dr#S12319219 1e-23 Contig589 gi|4506505| 1e-56 gnl|UG|Dr#S12312662 1e-22 Contig785 gi|33695095| 1e-61 gnl|UG|Dr#S12264765 1e-22 Contig157 gi|21361122| 1e-138 gnl|UG|Dr#S12313094 1e-21 v11_p42_j20_t3_049_ab1 gi|47591841| 1e-100 gnl|UG|Dr#S12137806 1e-21 Contig610 gi|10801345| 1e-114 gnl|UG|Dr#S12310326 1e-20 nm_27_o1_t3_ gi|7706429| 1e-72 gnl|UG|Dr#S12310422 1e-19 Contig439 gi|4504799| 1e-25 gnl|UG|Dr#S12309233 1e-19 nm_31_d5_t3_ gi|8923956| 1e-50 gnl|UG|Dr#S12264745 1e-17 v11_p41_h12_t3_026_ab1 No Human Hit gnl|UG|Dr#S12320916 1e-17 Contig129 gi|34932414| 1e-103 gnl|UG|Dr#S12313534 1e-17 nm_14_j21_t3_ gi|4505325| 1e-42 gnl|UG|Dr#S12136571 1e-17 Contig1321 gi|4501857| 1e-80 gnl|UG|Dr#S12309233 1e-17 nm_19_k3_t3_ gi|26051212| 1e-106 gnl|UG|Dr#S12137637 1e-17 Contig488 gi|4557525| 1e-105 gnl|UG|Dr#S12311975 1e-15 nm_35h_k19_t3_ gi|16950607| 1e-43 gnl|UG|Dr#S12196214 1e-15 Contig195 gi|4557231| 1e-99 gnl|UG|Dr#S12309233 1e-14 nm_14_h19_t3_ gi|4503787| 1e-86 gnl|UG|Dr#S12310912 1e-13 v11_p51_d20_t3_ gi|30520322| 1e-19 gnl|UG|Dr#S12321150 1e-13 g3-n14 gi|13654278| 1e-23 gnl|UG|Dr#S12318856 1e-13 nm_29_f2_t3_ gi|4506517| 1e-65 gnl|UG|Dr#S12312662 1e-13 g4-h23 gi|24111250| 1e-33 gnl|UG|Dr#S12312651 1e-13 Math_p2_A2_T3_ No human Hit gnl|UG|Dr#S12078998 1e-13 nm_35h_f4_t3_ gi|41148476| 1e-67 gnl|UG|Dr#S12319663 1e-13 Contig952 gi|21264558| 1e-61 gnl|UG|Dr#S12318843 1e-12 g4-g21 gi|11995474| 1e-65 gnl|UG|Dr#S12192716 1e-12 Contig854 gi|8922789| 1e-117 gnl|UG|Dr#S12313534 1e-11 Contig1105 gi|6912638|| 1e-83 gnl|UG|Dr#S12079967 1e-11 nm_26_f7_t3_ gi|30181238| 1e-83 gnl|UG|Dr#S12319880 1e-11 Contig949 gi|21284385| 1e-68 gnl|UG|Dr#S12290856 1e-11 g3-n3 gi|18490991| 1e-64 gnl|UG|Dr#S12320832 1e-10 v11_p41_m16_t3_007_ab1 gi|4885661| 1e-33 gnl|UG|Dr#S12310912 1e-10 Contig653 gi|4505047| 1e-124 gnl|UG|Dr#S12239868 1e-09 Contig1349 gi|9665259| 1e-46 gnl|UG|Dr#S12320840 1e-09 6h12 gi|31317231| 1e-43 gnl|UG|Dr#S12321311 1e-09 v11_p43h_i14_t3_070_ab1 No Human Hit gnl|UG|Dr#S12320916 1e-09 nm_35h_d11_t3_ gi|7661790| 1e-35 gnl|UG|Dr#S12196146 1e-09 nm_35h_k22_t3_ gi|5031977| 1e-124 gnl|UG|Dr#S12242267 1e-09 v11_p48_g2_t3_087_ab1 gi|11496277| 1e-60 gnl|UG|Dr#S12312396 1e-09 nm_30_e11_t3_ gi|32483357| 1e-56 gnl|UG|Dr#S12309103 1e-08 nm_28_f23_t3_ gi|42544191| 1e-25 gnl|UG|Dr#S12239884 1e-08 nm_12_p16_t3_ gi|21361553| 1e-21 gnl|UG|Dr#S12310912 1e-08 nm_32h_a8_t3_ gi|11386179| 1e-22 gnl|UG|Dr#S12312152 1e-08 Human RefSeq sequence ID's are provided to allow cross-referencing. DNA sequence polymorphisms within and between A. mexicanum and A. t. tigrinum The identification of single nucleotide polymorphisms (SNPs) within and between orthologous sequences of A. mexicanum and A. t. tigrinum is needed to develop DNA markers for genome mapping [32], quantitative genetic analysis [33], and population genetics [34]. We estimated within species polymorphism for both species by calculating the frequency of SNPs among ESTs within the 20 largest contigs (Table 4). These analyses considered a total of 30,638 base positions for A. mexicanum and 18,765 base positions for A. t. tigrinum. Two classes of polymorphism were considered in this analysis: those occurring at moderate (identified in 10–30% of the EST sequences) and high frequencies (identified in at least 30% of the EST sequences). Within the A. mexicanum contigs, 0.49% and 0.06% of positions were polymorphic at moderate and high frequency, while higher levels of polymorphism were observed for A. t. tigrinum (1.41% and 0.20%). Higher levels of polymorphism are expected for A. t. tigrinum because they exist in larger, out-bred populations in nature. To identify SNPs between species, we had to first identify presumptive, interspecific orthologues. We did this by performing BLASTN searches between the A. mexicanum and A. t. tigrinum assemblies, and the resulting alignments were filtered to retain only those alignments between sequences that were one another's reciprocal best BLAST hit. As expected, the number of reciprocal 'best hits' varied depending upon the E value threshold, although increasing the E threshold by several orders of magnitude had a disproportionately small effect on the overall total length of BLAST alignments. A threshold of E<10-80yielded 2414 alignments encompassing a total of 1.25 Mbp from each species, whereas a threshold of E<10-20 yielded 2820 alignments encompassing a total of 1.32 Mbp. The percent sequence identity of alignments was very high among presumptive orthologues, ranging from 84–100% at the more stringent E threshold of E<10-80. On average, A. mexicanum and A. t. tigrinum transcripts are estimated to be 97% identical at the nucleotide level, including both protein coding and UTR sequence. This estimate for nuclear sequence identity is surprisingly similar to estimates obtained from complete mtDNA reference sequences for these species (96%, unpublished data), and to estimates for partial mtDNA sequence data obtained from multiple natural populations [16]. These results are consistent with the idea that mitochondrial mutation rates are lower in cold versus warm-blooded vertebrates [35]. From a resource perspective, the high level of sequence identity observed between these species suggests that informatics will enable rapidly the development of probes between these and other species of the A. tigrinum complex. Extending EST resources to other ambystomatid species Relatively little DNA sequence has been obtained from species that are closely related to commonly used model organisms, and yet, such extensions would greatly facilitate genetic studies of natural phenotypes, population structures, species boundaries, and conservatism and divergence of developmental mechanisms. Like many amphibian species that are threatened by extinction, many of these ambystomatid salamanders are currently in need of population genetic studies to inform conservation and management strategies [e.g. [13]]. We characterized SNPs from orthologous A. mexicanum and A. t. tigrinum ESTs and extended this information to develop informative molecular markers for a related species, A. ordinarium. Ambystoma ordinarium is a stream dwelling paedomorph endemic to high elevation habitats in central Mexico [36]. This species is particularly interesting from an ecological and evolutionary standpoint because it harbors a high level of intraspecific mitochondrial variation, and as an independently derived stream paedomorph, is unique among the typically pond-breeding tiger salamanders. As a reference of molecular divergence, Ambystoma ordinarium shares approximately 98 and 97% mtDNA sequence identity with A. mexicanum and A. t. tigrinum respectively [16]. To identify informative markers for A. ordinarium, A. mexicanum and A. t. tigrinum EST contigs were aligned to identify orthologous genes with species-specific sequence variations (SNPs or Insertion/Deletions = INDELs). Primer pairs corresponding to 123 ESTs (Table 8) were screened by PCR using a pool of DNA template made from individuals of 10 A. ordinarium populations. Seventy-nine percent (N = 97) of the primer pairs yielded amplification products that were approximately the same size as corresponding A. mexicanum and A. t. tigrinum fragments, using only a single set of PCR conditions. To estimate the frequency of intraspecific DNA sequence polymorphism among this set of DNA marker loci, 43 loci were sequenced using a single individual sampled randomly from each of the 10 populations, which span the geographic range of A. ordinarium. At least one polymorphic site was observed for 20 of the sequenced loci, with the frequency of polymorphisms dependent upon the size of the DNA fragment amplified. Our results suggest that the vast majority of primer sets designed for A. mexicanum / A. t. tigrinum EST orthologues can be used to amplify the corresponding sequence in a related A. tigrinum complex species, and for small DNA fragments in the range of 150–500 bp, approximately half are expected to have informative polymorphisms. Table 8 EST loci used in a population-level PCR amplification screen in A. ordinarium Locus ID Forward Primer 5' to 3' Reverse Primer 5' to 3' 1F8 AAGAAGGTCGGGATTGTGGGTAA CAGCCTTCCTCTTCATCTTTGTCTTG 1H3 GGCAAATGCTGGTCCCAACACAAA GGACAACACTGCCAAATACCACAT 2C8 GCAAGCACCAGCCACATAAAG GGCCACCATAACCACTCTGCT 3B10 TCAAAACGAATAAGGGAAGAGCGACTG TTGCCCCCATAATAAGCCATCCATC 5E7 ACGCTTCGCTGGGGTTGACAT CGGTAGGATTTCTGGTAGCGAGCAC 5F4 CCGAGATGAGATTTATAGAAGGAC TAGGGGAAGTTAAACATAGATAGAA 6A3 GTTTATGAAGGCGAGAGGGCTATGACCA ATCTTGTTCTCCTCGCCAGTGCTCTTGT 6B1 TGATGCTGGCGAGTACAAACCCCCTTCT TTTACCATTCCTTCCCTTCGGCAGCACA 6B3 ACCACGTGCTGTCTTCCCATCCAT ACGAAGCTCATTGTAGAAGGTGTG 6B4 CCCACGATGAATTGGAATTGGACAT CTGCCTGCCAGACCTACAGACTATCGT 6C4 ATGGCGCCAAAGTGATGAGTA GGGCCAGGCACACGACCACAAT 6D2 ATCAAGGCTGGCATGGTGGTCA GGGGGTCGTTCTTGCTGTCA 6H8 GAAGAAGACAGAAACGCAGGAGAAAAAC CGGGCGGGGGCGGGTCACAGTAAAAC BL005B_A01.5.1 GACAGGTCATGAACTTTTGAAAATAA AAAGTATATGTACCAAATGGGAGAGC BL006A_G07.5.1 GATGTCCTCTCCACTATACAAGTGTG GTTTGACTTGTCACCACTTTATCAAC BL012D_F02.5.1 ACAGCCAGAAATAGAAACTTTGAACT TGAAAGTATGTATTGTTTTCACAGGG BL013C_E01.5.1 AGGATGAAATAATATGCTGTGCTTC ACCGTGATAAACTCCATCCCTT BL014D_B11.5.1 AGCAAAACTCCTCTATGAATCTCG ATTGCACACTAAATAGGTGAATACGA BL279A_G10.5.1 ATGGCAGGATGAAGAAAGACAT ATGCACTTTGGACCCACTGAG Et.fasta.Contig1023.5.1 TGTGGTTATTGGACTACTTCACTCTC AAACGTCCATTTGACACTGTATTTTA Et.fasta.Contig1166.5.1 GAATGAAGAGAAAATGTTTTGAAGGT GCACAGTATTGGCTATGAGCAC Et.fasta.Contig1311.5.1 AGAAAACTGTGTCAAGCTTATTTTCC CAACTTAGTGTTCACATTTCTGAGGT Et.fasta.Contig1335.5.1 CCACTTATGGTAGTTCCCACTTTTAT GCTAAAGAATACCAAGAACCTTTGAC Et.fasta.Contig1381.5.1 GTCACAGGTATAACATTGAAAGGATG TAAATGAATCAAACATTGAAGAGAGC Et.fasta.Contig1459.5.1 ATAACAAGGACATGTTCTGCTGG CTAGCAGAACCCTGTATAGCCTG Et.fasta.Contig1506.5.1 AGGATATCCGCTCAGAAATATGAAG CTGACCACTTGCAAAACTTACTACCT Et.fasta.Contig1578.5.1 CCTAGAACATTACCAAAACAGACTCA AATGAAGAAGTATTGCATGTGAGAAC Et.fasta.Contig1647.5.1 GTACAACGTCAGGCAAAGCTATTCT ATCTCCAACACCGTGGCTAAT Et.fasta.Contig1717.5.1 GAACTTGTTGGCAGGTTTCTCTT CTAGTGATAGGTTGGACATACCAGAG Et.fasta.Contig1796.5.1 TGTGGGTATGTATATGGCTAACTTGT AGATTTTATGTGCTACTGCATTTACG Et.fasta.Contig1908.5.1 CTCATGACTTAATTGCTGTTCTTCG ATAACCATTCTGAGGTTTTGAGTTG Et.fasta.Contig1941.5.1 ATCTCCTGCTTCATCTCTTGATTTAT TAACAGATTTAATAAACGTCCCCTTC Et.fasta.Contig1943.5.1 AGTACGATGAATCTGGTCCTTCAAT CCACAATACTGACATACTCTGGTCTT Et.fasta.Contig325.5.1 GTGAAGTCAGTGAGTAAAGTCCATGT CTAGGATACCAGTGGGAGAGTGTAAT Et.fasta.Contig330.5.1 GTCATCACCTCCACTACTTCACAAG TTTTGGCACTGTAAGATTCTATGAAC Et.fasta.Contig536.5.1 CCTTAGGTAGAACAGACTGAAGCAG GAAACATGAAACTGGACTTGTTTTAG Et.fasta.Contig917.5.1 GGATGCAGATTCTTCCTATTTTACTC CTGGTCACTTTACTTGTTTTCAGTGT Et.fasta.Contig926.5.1 TTCATCACATTCTACTTCACAAATCA CTAGGCAAGCAAGCTTTCTAATAGTT Et.fasta.Contig93.5.1 GAATAAAAGCAACAATTGCAGAGTTA CTCGACTCCTTCTACGATCTCTACTC Et.fasta.Contig990.5.1 GTTTAGGTTAGTATGAAGGATCCCAA TGCCAGTACTCACCAATTAGTAAAAG G1-C12 CCCAAATCCAGGAGTTCAAA TGGGACCTGGGGCTTCATT G1-C13 TTGCCCGAGAAAAGGAAGGACATA CAAGGGTGGGTGAGGGACATC G1-C5 F-CACTGTTGACTTGGGTTATGTTATT CTGCTCCTAGGGTTTGTGAAG G1-C7 CCCGTGTGGCTGGCTTGTGC TCGGCTACTTTGGTGTTTTTCTCCCTCAT G1-C9 TGGTCCGGCAACAGCATCAGA GCTTTTCGGTATTCAACGGCAGAGTG G1-C9 TGGTCCGGCAACAGCATCAGA GCTTTTCGGTATTCAACGGCAGAGTG G1-D5 AGACCCTTGCTGTGTAACTGCT GACTGGGACTGACTTCTATGACG G1-D6 CAGCGTGCCCACCCGATAGAA TCCCAAAAAGTAAAATGTGCAAAGAAAA G1-D7 CAGCGGTGGAAATGACAAACAGG CCAAGACGACGAGGAACGGTATT G1-E12 CAACCATGAGAGGAGGCCAGAGAAC AAAACAGCACTACCTACAAAACCCTATT G1-F1 TTAGTTTGGGTGCAGACAGGA GGTGCTCAACAACAAATCAACT G1-F20 TCCCCAACAACTCCAGCAGAT GGAAACCACCTAGACGAAAAATG G1-I18 CATGTTTGTGGGTGTGGTGAA AAAAGCGGCATCTGGTAAGG G1-I19 ACCCAGACCTGTCCACCTCA GAACAGCTCTCCAATCCACAAG G1-I21 CCAAGCGAAGGAGGCGTGTG CATGTGGCTCTTTGTTTCTGGA G1-I5 TAATCGTGTTTGGTGGCATCCTTGAGTC AGCAGCAGTTCCATTTTCCCACACCA G1-I8 ACCTGCAGTGGGCTAAGACC ATGGAAATAATAAAATAAAATGTT G1-J10 CGTTCGCTTTGCCTGCCACA GGCTCTTCCCCGGTCGTCCAC G1-J17 AGCGCCTTCTACACGGACAC TATGCCCCAATTACTCTTCTGC G1-J2 TACAGTAACTATGCCAAGATGAAATG CAATATGGATAATGGCTGTAGACC G1-J20 ATCCTCCAAGCTCACTACAACA CCAGCCCCTTCCCAAACAG G1-J9 CTGTCATTGCCTGCATCGGGGAGAAG TGTTGAGGGGAAGCAGTTTTG G1-K2 GCTTTCGCCTTTGACACCTC GGCCGGACCATTGCTGAAGAAG G1-L11 AAAGTGACCATCCAGTGCCCAAACCT CCGGCCGAAACTGACGAGATACATTAG G1-L13 TCAGCTGCACTAGGTTTGTC CATTTTGATTTGCTCCATAA G1-L19 GACAACCTTGAATCCTTTATG AGATGTTGGTTGGTGACTTAT G1-L20 TGGGCATAGATGGCAAGGAAAAA CCCCCAGCATCTCGCATACAC G1-L7 GTGCTACAGGAAGGAATGGATG TAGCACAGGAACAGCCGACAATAA G1-M14 CCGCTTGGACATGAGGAGAT TGGCAAAGAAACAGAACACAACTA G1-M19 GAGAAGTAGTGTCCCGGCAGAAAC ATGGGTGAAAACTTAGGTGAAATG G1-N9 GCGGGGCAATACATGACGTTCCACAG GACCCCCATCTCCGTTTCCCATTCC G1-O1 GGGGTAGAGCACAGTCCAGTT TTGCAAGGCCGAAAAGGTG G1-O12 GGAATTCCGGGGCACTACT TCGCGAGGACGGGGAAGAG G1-O24 CGGCCTTCCTGCAGTACAACCATC TCGGCAACGTGAAGACCATA G2-A11 GCCCCTGGAAGCTGTTGTGA GGGGTCCATCCGAGTCC G2-A7 TTACCCCACAGACAAAATCAACACC GGCGGCCCCTCATAGCAC G2-B1 GGGCCTAGTCCTGCTGGTC CAAAGAGTGCGGAGAAATGG G2-B8 CAACATGCGACCACTATAGCCACTTCCT CGCCACCGCCACCACCACA G2-C2 TTTGCAGGAAGAGTCATAACACAG GTCAACAACACCCTTTTCCCTTCCT G2-D1 GCAGGTCGGCAAGAAGCTAAAGAAGGAA AGGGTTGGTTTGAAAGGATGTGCTGGTAA G2-E17 GGAGCACCAAATTCAAGTCAG CGTCCCCGGTCAATCTCCAC G2-E19 CCAGTTTGAGCCCCAGGAG TCGCGGCAGTCAAGAGGTC G2-F17 TATCCTCTTATTGCTGCATTCTCCTCAC AGTACGGCCGTTCACCATCTCTG G2-F2 CACACCACAGACGCATTGAC TCCCCAGCCTGTGTAGAAC G2-G13 GGGAGGGGAGAAGGCTACCA ATACACGGCTTCCATGCTTCTTCTT G2-G15 CCACGGCCCCACATCCAGC TCCCGCAGAATTTCCGTATCCAT G2-G21 TCCAAGAGGGTGTGAGGTGAAC AAAGCCATGCGAAGCGGAAGAC G2-G23 GGTTTGGTACTTCAGCGGATGT CCAAAGCCTGTACTATGCGAAAAG G2-G5 CGGTCCCTACTGTGGTCTATGGTTTTCA GGCTCTGCATATCCTCGGTCACACTTCC G2-G6 CCCATGGCTGCAAGGATTACG CAGGGGTTGTTGGGAGGCAGTGT G2-H18 TTGTCAAATGGGCGAGTTCA TGTTTTGCACCCAGTTTTTG G2-I18 GATCTCCTCAGGTCTCTTTCA GATTATGGGCCGGTGTCTCT G2-I23 TGACTTTCCCAATGTGAGCAGAC CAGAGGTGGTGTTACAGCAGCAGTTT G2-J12 CCTCTTGTCCCAGTGCCAGTG TCCAGGGATCCGAAACAAAG G2-J21 CCGCCTCAGCCTGTTTCTCTACTTTT CTTTGAATTTCTGCTTTTGGTGCTCTGC G2-K12 ACATTAGTCCTGGTTACGAGAGC AAAGGGCAGTCCAGCATTGA G2-K2 CTGCCCAAGAAGACCGAGAGCCACAAG AGCGCCCCCTGCACCAAAATCA G2-L16 CCAAGGGTAGGAGAACAAGACA ATGGCATGCTGGGAAATCA G2-L21 GAATCTAGGTCCAAGCAGTCCCATCT GACCATCACACCACTACCCACACTCA G2-L3 TGAAAGAGGCCAGAAACAAGTAG TTCCCAAGGTCTCCATAACAAT G2-L4 TGGCCAAGAAGATGAAACAGGAAGAGGAG TGGCAAAGGACACGACGCAGAG G2-M14 CGGCCTCCTCGACGCATACG CCAGGCCGGCCCATTGTTC G2-M24 ACGGAGCACGGTCAGATTTCACG CCCGGCTGGCTCTTCTTGCTCTT G2-M3 CGATCCGCATTGAACGAGT TGTGGCAGGAAGGAGAAGG G2-N2 CGTGTTTTCCTCCTATGTCGACTTCTTTG ACGTGCTCTGCCTTTCTTGATCTTGTGTT G3-D7 AGGATTTCTTGGCCGGTGGAGTGG GAAGTTGAGGGCCTGGGTGGGGAAGTA NT001D_E08.5.1 AGAAGTTCCTAGATGAGTTGGAGGAG AATTAATTTCCTAAACCAGGTGACAG NT010B_E09.5.1 GAAGAGGTCCTAAAATATCAAGATGC ATGATAGACTTCGTCCTTGTCATAGA NT014D_E01.5.1 AAAGAAGTCCCGCATCTAACCT ATTAAATATGAGAAGATGTGTGCAGG V2_p1_b8 AGTCACTGTGTTACATTATCACCCAC ATAATTATACACTGCGGTCTGCATCT V2_p1_c5 AGTACCTGTTCGACAAGCACAC TGAGAACATAGACAAGTTAACATACACC V2_p1_d10 GAGATAGAAAGGCTGCATAAAGAAAT TATGTTTCAACAATGTACAGGAAACC V2_p1_d4 CACCAGAACAAGCTGTATTTTTATGT TGGTTTGCATCATATATTAAAGGGTA V2_p1_g7 GACTTCAAGCACATTGGGAAAC ATTGTAAACTTGATAGGCTGGTGAG V2_p2_g6 AGAATTCCCAATAGCACCTGAAAT CACTTGGTAAATACATACACACAGCA V2_p2_h2 CTTTTTGGCCTGGTCTTTTTG AGATTCTTCAGACTCGTCCTTCTTT V2_p3_a5 TTTACACAGAAACCTTGTTTATTTGGC TTTAAGGATGCTTAGAGGCAAAGTATT V2_p3_b1 AGTCACTGTGTTACATTATCACCCAC TATACACTGCGGTCTGCATCTACT V2_p5_b3 AATGGGATGAAGAGCGAGAAT CTGCCCCATTGACATTTACCTA V2_p5_h3 CCTTCAGACGAAAACAGCACTAAG TACAGTGTATGAGAGCCCAATATTTC V2_p6_a4 AGAAATACATCAAATATCGGGTGG AAAAAGGACAATGTTCAGCTCTCT V3_p1_a21 ACCAAGTTCTTGGAAAGTGGTG CTTAGTGTCTCCTGGGTTTGAATAG V3_p1_b13 GTCTTGGTACTCAATGAAGGAGATG TCAATCTGATGAAGAGTTTACATGTCT Comparative gene mapping Salamanders occupy a pivotal phylogenetic position for reconstructing the ancestral tetrapod genome structure and for providing perspective on the extremely derived anuran Xenopus (37) that is currently providing the bulk of amphibian genome information. Here we show the utility of ambystomatid ESTs for identifying chromosomal regions that are conserved between salamanders and other vertebrates. A region of conserved synteny that corresponds to human chromosome (Hsa) 17q has been identified in several non-mammalian taxa including reptiles (38) and fishes (39). In a previous study Voss et al. (40) identified a region of conserved synteny between Ambystoma and Hsa 17q that included collagen type 1 alpha 1 (Col1a1), thyroid hormone receptor alpha (Thra), homeo box b13 (Hoxb13), and distal-less 3 (Dlx3) (Figure 4). To evaluate both the technical feasibility of mapping ESTs and the likelihood that presumptive orthologues map to the same synteny group, we searched our assemblies for presumptive Hsa 17 orthologues and then developed a subset of these loci for genetic linkage mapping. Using a joint assembly of A. mexicanum and A. t. tigrinum contigs, 97 Hsa 17 presumptive orthologues were identified. We chose 15 genes from this list and designed PCR primers to amplify a short DNA fragment containing 1 or more presumptive SNPs that were identified in the joint assembly (Table 9). All but two of these genes were mapped, indicating a high probability of mapping success using markers developed from the joint assembly of A. mexicanum and A. t. tigrinum contigs. All 6 ESTs that exhibited 'best hits' to loci within the previously defined human-Ambystoma synteny group did map to this region (Hspc009, Sui1, Krt17, Krt24, Flj13855, and Rpl19). Our results show that BLAST-based definitions of orthology are informative between salamanders and human. All other presumptive Hsa 17 loci mapped to Ambystoma chromosomal regions outside of the previously defined synteny group. It is interesting to note that two of these loci mapped to the same ambystomatid linkage group (Cgi-125, Flj20345), but in human the presumptive orthologues are 50 Mb apart and distantly flank the syntenic loci in Figure 4. Assuming orthology has been assigned correctly for these loci, this suggests a dynamic history for some Hsa 17 orthologues during vertebrate evolution. Figure 4 Comparison of gene order between Ambystoma linkage group 1 and an 11 Mb region of Hsa17 (37.7 Mb to 48.7 Mb). Lines connect the positions of putatively orthologous genes. Table 9 Presumptive human chromosome 17 loci that were mapped in Ambystoma Marker ID Primersa Diagnosisb LGc Symbold RefSeq IDe E-valuef Pl_6_E/F_6 F-GAAAACCTGCTCAGCATTAGTGT ASA ul PFN1 NP_005013 E-34 R-TCTATTACCATAGCATTAATTGGCAG Pl_5_G/H_5 F-CTATTTCATCTGAGTACCGTTGAATG PE (A) 23 CGI-125 NP_057144 E-56 R-TAATGTAGAACTAAATGGCATCCTTC E-CCATGGTGCAGGAAGAGAGCCTATAT Pl_0.4_A/B_1 F-GTCTCATTATCCGCAAACCTGT SP 1 RPL19 NP_000972 E-67 R-ATTCTCATCCTCCTCATCCACGAC Pl_4_B_7/8 F-CCTAGAACATTACCAAAACAGACTCA RD (Dpn II) 1 KRT10 NP_061889 E-17 R-AATGAAGAAGTATTGCATGTGAGAAC Pl_4_B_9/10 F-GAACTTGTTGGCAGGTTTCTCTT RD (AciI) 1 KRT17 NP_000413 E-146 R-CTAGTGATAGGTTGGACATACCAGAG Pl_10_C/D_4 F-CTCCACTATTTAAAGGACATGCTACA PE (A) 1 SUI1 NP_005792 E-48 R-TTAATATAGCACAACATTGCCTCATT E-TGCTACATTAATGTAATAAACGGCATCATC Pl_6_E/F_11 F-AAGAGAAGTTCCTAGATGAGTTGGAG PE (A) 1 HSPC009 NP_054738 E-26 R-TGAAGAGAGAACTCAAAGTGTCTGAT E-TCATGTTTTGCTCTGCTGTGCAGT Pl_9_A/B_10 F-TGATAGTTTCTGGATTAAGACGAGTG PE (T) 1 FLJ13855 NP_075567 E-15 R-CTTAGAGCCATTGTTACAAGATGTTC E-GTGATCTAGTGGGATCAAACCCTAAAGACC Pl_10_C/D_9 F-AAAGTGCCAAGAAGGAGATTAACTT PE (T) 9 NME1 NP_000260 E-71 R-GAGCTCAGAAAACAAGGCAGTAAC E-AAATGGATCTACGAGTAGACCTTGACCC Pl_9_C/D_9 F-GAGTCTCCTTTAGGATTGACGTATCT PE (T) 23 FLJ20345 NP_060247 E-17 R-GCTATGTGAGCAGAGATAAAAGTCAG E-GTTACAGCATCAGTGGGATGTGGTATGT Pl_8_C/D_9 F-AGGATACCAACCTCTGTGCTATACAT PE (C) 15 H3F3B NP_005315 E-66 R-TAAATGTATTTACAAACCGAAAGCAA E-CGTGGCGAGCGTGCCTAGT Pl_9_C/D_4 F-GTGGTTATTTGTAACATTTCGTTGAC PE (A) 8 SFRS2 NP_003007 E-40 R-AATTACATTTGGGCTTCTCAATTTAC E-TTTTTAAACGCGTAAAAATGTTAACAGA Pl_6_C/D_5 F-CCGTAAATGTTTCTAAATGACAGTTG PE (G) 2 ACTG1 NP_001605 0 R-GGAAAGAAAGTACAATCAAGTCCTTC E-GATTGAAAACTGGAACCGAAAGAAGATAAA aSequences are 5' amplification primers, 3' amplification primers, or primer extension probes, and are preceded by F-, R-, and E- respectively. bGenotyping methods are abbreviated: allele specific amplification (ASA), size polymorphism (SP), restriction digestion (RD), primer extension (PE). Diagnostic restriction enzymes and diagnostic extension bases are provided in parentheses. cAmbystoma linkage group ID. "ul" designates markers that are unlinked. dOfficial gene symbols as defined by the Human Genome Organization Gene Nomenclature Committee . eBest BLASTX hit (highest e-value) from the human RefSeq database using the contig from which each marker was designed as a query sequence. fHighest E-value statistic obtained by searching contigs, from which EST markers were designed, against the human RefSeq database. Future directions Ambystomatid salamanders are classic model organisms that continue to inform biological research in a variety of areas. Their future importance in regenerative biology and metamorphosis will almost certainly escalate as genome resources and other molecular and cellular approaches become widely available. Among the genomic resources currently under development (see [41]) are a comparative genome map, which will allow mapping of candidate genes, QTL, and comparative anchors for cross-referencing the salamander genome to fully sequenced vertebrate models. In closing, we reiterate a second benefit to resource development in Ambystoma. Genome resources in Ambystoma can be extended to multiple, closely related species to explore the molecular basis of natural, phenotypic variation. Such extensions can better inform our understanding of ambystomatid biodiversity in nature and draw attention to the need for conserving such naturalistic systems. Several paedomorphic species, including A. mexicanum, are on the brink of extinction. We can think of no better investment than one that simultaneously enhances research in all areas of biology and draws attention to the conservation needs of model organisms in their natural habitats. Conclusions Approximately 40,000 cDNA sequences were isolated from a variety of tissues to develop expressed sequence tags for two model salamander species (A. mexicanum and A. t. tigrinum). An approximately equivalent number of contigs were identified for each species, with 21,091 unique contigs identified overall. The strategy to sequence cDNAs from a diverse collection of tissues from normalized and non-normalized libraries yielded different sets of highly redundant contigs. Only 25% and 28% of the A. mexicanum and A. t. tigrinum contigs, respectively, were identified in common. To demonstrate the utility of these EST resources, we searched databases to identify new probes for regeneration research, characterized intra- and interspecific nucleotide polymorphism, saturated a human/Ambystoma synteny group with marker loci, and extended PCR primer sets designed for A. mexicanum / A. t. tigrinum orthologues to a related tiger salamander species. Over 100 new probes were identified for regeneration research using informatic approaches. With respect to comparative mapping, 13 of 15 EST markers were mapped successfully, and 6 EST markers were mapped to a previously defined synteny group in Ambystoma. These results indicate a high probability of mapping success using EST markers developed from the joint assembly of A. mexicanum and A. t. tigrinum contigs. Finally, we found that primer sets designed for A. mexicanum / A. t. tigrinum EST orthologues can be used to amplify the corresponding sequence in a related A. tigrinum complex species. Overall, the EST resources reported here will enable a diversity of new research areas using ambystomatid salamanders. Methods cDNA library construction Ten cDNA libraries were constructed for the project using various larval tissues of A. mexicanum and A. t. tigrinum (Table 1). Larval A. mexicanum were obtained from adult animals whose ancestry traces back to the Axolotl Colony [17]. Larval A. t. tigrinum were obtained from Charles Sullivan Corp. The GARD and MATH A. mexicanum limb regeneration libraries were constructed using regenerating forelimb mesenchyme. Total RNAs were collected from anterior and posterior limbs amputated at the mid-stylopod level on 15 cm animals, and from the resulting regenerates at 12 h, 2 days, 5 days and early bud stages. One hundred μg fractions of each were pooled together and polyA-selected to yield 5 μg that was utilized for directional library construction (Lambda Zap, Stratagene). The V1 (A. mex), V2 (A. tig), V4-5 (A. tig), and V6-7 (A. mex) libraries were made from an assortment of larval tissues (see Table 1) using the SMART cDNA cloning kits (Clontech). Total RNAs were isolated and reverse transcribed to yield cDNAs that were amplified by long distance PCR and subsequently cloned into pTriplEX. The V3 and AG libraries were constructed by commercial companies (BioS&T and Agencourt, respectively). cDNA template preparation and sequencing cDNA inserts were mass excised as phagemids, picked into microtitre plates, grown overnight in LB broth, and then diluted (1/20) to spike PCR reactions: (94°C for 2 min; then 30 cycles at 94°C for 45 sec, 58°C for 45°sec, and 72°C for 7 min). All successful amplifications with inserts larger than ~500 bp were sequenced (ABI Big Dye or Amersham Dye terminator chemistry and 5' universal primer). Sequencing and clean-up reactions was carried out according to manufacturers' protocols. ESTs were deposited into NCBI database under accession numbers BI817205-BI818091 and CN033008-CN045937 and CN045944-CN069430. EST sequence processing and assembly The PHRED base-calling program [42] was used to generate sequence and quality scores from trace files. PHRED files were then quality clipped and vector/contaminant screened. An in-house program called QUALSCREEN was used to quality clip the ends of sequence traces. Starting at the ends of sequence traces, this program uses a 20 bp sliding window to identify a continuous run of bases that has an average PHRED quality score of 15. Mitochondrial DNA sequences were identified by searching all ESTs against the complete mtDNA genome sequence of A. mexicanum (AJ584639). Finally, all sequences less than 100 bp were removed. The average length of the resulting ESTs was 629 bp. The resulting high quality ESTs were clustered initially using PaCE [43] on the U.K. HP Superdome computer. Multi-sequence clusters were used as input sequence sets for assembly using CAP3 [44] with an 85% sequence similarity threshold. Clusters comprising single ESTs were assembled again using CAP3 with an 80% sequence similarity threshold to identify multi-EST contigs that were missed during the initial analysis. This procedure identified 550 additional contigs comprising 1150 ESTs. Functional annotation All contigs and singletons were searched against the human RefSeq database (Oct. 2003 release) using BLASTX. The subset of sequences that yielded no BLAST hit was searched against the non-redundant protein sequence database (Feb. 2004) using BLASTX. The remaining subset of sequences that yielded no BLAST hit was searched against Xenopus laevis and X. tropicalis UNIGENE ESTs (Mar. 2004) using TBLASTX. Zebrafish ESTs were downloaded from UNIGENE ESTs (May 2004). BLAST searches were done with an E-value threshold of E <10-7 unless specified. Sequence comparison of A. mexicanum and A. t. tigrinum assemblies All low quality base calls within contigs were masked using a PHRED base quality threshold of 16. To identify polymorphisms for linkage mapping, contigs from A. mexicanum and A. t. tigrinum assemblies were joined into a single assembly using CAP3 and the following criteria: an assembly threshold of 12 bp to identify initial matches, a minimum 100 bp match length, and 85% sequence identity. To identify putatively orthologous genes from A. mexicanum and A. t. tigrinum assemblies, and generate an estimate of gene sequence divergence, assemblies were compared using BLASTN with a threshold of E <10-20. Following BLAST, alignments were filtered to obtain reciprocal best BLAST hits. Extending A. mexicanum / A. t. tigrinum sequence information to A. ordinarium Polymorphic DNA marker loci were identified by locating single nucleotide polymorphisms (SNPs) in the joint A. mexicanum and A. t. tigrinum assembly. Polymerase chain reaction (PCR) primers were designed using Primer 3 [45] to amplify 100 – 500 bp SNP-containing fragments from 123 different protein-coding loci (Table 8). DNA was isolated from salamander tail clips using SDS, RNAse and proteinase K treatment, followed by phenol-chloroform extraction. Fragments were amplified using 150 ng DNA, 75 ng each primer, 1.5 mM MgCl2, 0.25 U Taq, and a 3-step profile (94°C for 4 min; 33 cycles of 94°C for 45 s, 60°C for 45 s, 72°C for 30 s; and 72°C for 7 min). DNA fragments were purified and sequenced using ABI Big Dye or Amersham Dye terminator chemistry. Single nucleotide polymorphisms were identified by eye from sequence alignments. Linkage mapping of human chromosome 17 orthologous genes Putative salamander orthologues of genes on human chromosome 17 (Hsa 17) were identified by comparing the joint A. mexicanum and A. t. tigrinum assembly to sequences from the human RefSeq (NCBI) protein database, using BLASTX at threshold E<10-7. Linkage distance and arrangement among markers was estimated using MapManager QTXb19 software [46] and the Kosambi mapping function at a threshold of p = 0.001. All markers were mapped using DNA from a previously described meiotic mapping panel [40]. All PCR primers and primer extension probes were designed using Primer 3 [45] and Array Designer2 (Premier Biosoft) software. Species-specific polymorphisms were assayed by allele specific amplification, restriction digestion, or primer extension, using the reagent and PCR conditions described above. Primer extension markers were genotyped using the AcycloPrime-FP SNP detection assay (Perkin Elmer). See Table 9 for amplification and extension primer sequences, and information about genotyping methodology. Author's contributions SP and DK: bioinformatics; JW: clone management and sequencing in support of A. mexicanum and A. t. tigrinum ESTs; JS: comparative mapping and polymorphism estimation; DW: extending ESTs to A. ordinarium; JM, KK, AS, NM: PCR and gel electrophoresis; BH and ET: cDNA library construction and sequencing for spinal cord regeneration ESTs; MR, SB, DG: cDNA library construction and clone management for limb regeneration ESTs; DP and SV conceived of the project and participated in its design and coordination. All authors read and approved the final manuscript. Acknowledgements We thank the Axolotl Colony. We thank Greg Chinchar and Betty Davidson for providing RNA to make cDNA libraries V3 and V4. 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Sugimori M Kosako H Nakatomi H Yamamoto N Takebayashi H Nabeshima Y Kitamura T Weinmaster G Nakamura K Nakafuku M Trancription factor expression and notch-dependent regulation of neural progenitors in the adult rat spinal cord J Neurosci 2001 21 9814 9823 11739589 Horner PJ Power AE Kempermann G Kuhn HG Plamer TD Winkler J Thal LJ Gage FH Proliferation and differentiation of progenitor cells throughout the intact adult spinal cord J Neurosci 2000 20 2218 2228 10704497 Carmel JB Galante A Soteropoulos P Tolias P Recce M Young W Hart RP Gene expression profiling of acute spinal cord injury reveals spreading inflammatory signals and neuron loss Physio Genomics 2001 7 201 213 Song G Cechvala C Resnick DK Dempsey RJ Rao VLR GeneChip analysis after acute spinal cord injury in rat J Neurochem 2001 79 804 815 11723173 10.1046/j.1471-4159.2001.00626.x Parichy DM Stigson S Voss SR Genetic analysis of Steel and the PG-M/versican-encoding gene AxPG as candidate genes for the white (d) pigmentation mutant in the salamander Ambystoma mexicanum Dev Genes Evol 1999 209 349 356 10370116 10.1007/s004270050263 Voss SR Shaffer HB Adaptive evolution via a major gene effect: paedomorphosis in the Mexican axolotl Proc Natl Acad Sci USA 1997 94 14185 14189 9391174 10.1073/pnas.94.25.14185 Fitzpatrick BM Shaffer HB Environment dependent admixture dynamics in a tiger salamander hybrid zone Int J Org Evolution 2004 58 1282 1293 Martin AP Palumbi SR Rate of mitochondrial DNA evolution is slow in sharks compared to mammals Proc Natl Acad Sci USA 1993 90 4087 4091 8483925 Anderson JD Worthington RD The life history of the Mexican salamander Ambystoma ordinarium Taylor Herpetologica 1971 27 165 176 Cannatella DC De Sa RO Xenopus laevis as a model organism Syst Biol 1993 42 476 507 Schmid M Nanda I Guttenbach M Steinlein C Hoehn H Schartl M Haaf T Weigend S Fries R Buderstedde J-M First report on chicken genes and chromosomes Cytogenet Cell Genet 2000 90 169 218 11124517 10.1159/000056772 Postlethwait JH Woods IG Ngo-Hazelett YP Yan Y-L Kelly PD Chu F Huang H Hill-Force A Talbot WS Zebrafish comparative genomics and the origins of vertebrate chromosomes Genome Res 2000 10 1890 1902 11116085 10.1101/gr.164800 Voss SR Smith JJ Gardiner DM Parichy DM Conserved vertebrate chromosome segments in the large salamander genome Genetics 2001 158 735 746 11404337 Salamander Genome Project Website Ewing B Green P Base-calling of automated sequencer traces using phred. II. Error probabilities Genome Res 1998 8 186 194 9521922 Kalyanaraman A Aluru S Kothari S Brendel V Efficient clustering of large EST data sets on parallel computers Nucleic Acids Res 2003 31 2963 2974 12771222 10.1093/nar/gkg379 Huang X Madan A CAP3: A dna sequence assembly program Genome Res 1999 9 868 877 10508846 10.1101/gr.9.9.868 Rozen S Skaletsky HJ Primer 3 1999 Meer JM Cudmore RH JrManly KF MapManager QTX 2004

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==== Front BMC ImmunolBMC Immunology1471-2172BioMed Central London 1471-2172-5-161529196910.1186/1471-2172-5-16Research ArticleP2 receptor mRNA expression profiles in human lymphocytes, monocytes and CD34+ stem and progenitor cells Wang Lingwei 1lingwei.wang@kard.lu.seJacobsen Sten Eirik W 2sten.jacobsen@stemcell.lu.seBengtsson Anders 3anders.bengtsson@reum.lu.seErlinge David 1david.erlinge@kard.lu.se1 Department of Cardiology, Lund University Hospital, S-221 85 Lund, Sweden2 Department of Hematopoietic Stem Cell Laboratory, Lund Center for Stem Cell Biology and Cell Therapy, Lund University Hospital, S-221 85 Lund, Sweden3 Department of Rheumatology, Lund University Hospital, S-221 85 Lund, Sweden2004 3 8 2004 5 16 16 13 2 2004 3 8 2004 Copyright © 2004 Wang et al; licensee BioMed Central Ltd.2004Wang et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background Extracellular nucleotides (ATP, ADP, UTP and UDP) exert a wide range of biological effects in blood cells mediated by multiple ionotropic P2X receptors and G protein-coupled P2Y receptors. Although pharmacological experiments have suggested the presence of several P2 receptor subtypes on monocytes and lymphocytes, some results are contradictory. Few physiological functions have been firmly established to a specific receptor subtype, partly because of a lack of truly selective agonists and antagonists. This stimulated us to investigate the expression of P2X and P2Y receptors in human lymphocytes and monocytes with a newly established quantitative mRNA assay for P2 receptors. In addition, we describe for the first time the expression of P2 receptors in CD34+ stem and progenitor cells implicating a potential role of P2 receptors in hematopoietic lineage and progenitor/stem cell function. Results Using a quantitative mRNA assay, we assessed the hypothesis that there are specific P2 receptor profiles in inflammatory cells. The P2X4 receptor had the highest expression in lymphocytes and monocytes. Among the P2Y receptors, P2Y12 and P2Y2 had highest expression in lymphocytes, while the P2Y2 and P2Y13 had highest expression in monocytes. Several P2 receptors were expressed (P2Y2, P2Y1, P2Y12, P2Y13, P2Y11, P2X1, P2X4) in CD34+ stem and progenitor cells. Conclusions The most interesting findings were the high mRNA expression of P2Y12 receptors in lymphocytes potentially explaining the anti-inflammatory effects of clopidogrel, P2Y13 receptors in monocytes and a previously unrecognised expression of P2X4 in lymphocytes and monocytes. In addition, for the first time P2 receptor mRNA expression patterns was studied in CD34+ stem and progenitor cells. Several P2 receptors were expressed (P2Y2, P2Y1, P2Y12, P2Y13, P2Y11, P2X1, P2X4), indicating a role in differentiation and proliferation. Thus, it is possible that specific antibodies to P2 receptors could be used to identify progenitors for monocytes, lymphocytes and megakaryocytes. P2 receptorreal-time PCRlymphocytesmonocytesCD34+ cellshematopoietic stem cells ==== Body Background Extracellular nucleotides (ATP, ADP, UTP and UDP) exert a wide range of biological effects in blood cells mediated by multiple ionotropic P2X receptors and G protein-coupled P2Y receptors [1-3]. So far, the P2Y family is composed of eight cloned and functionally distinct subtypes (P2Y1, P2Y2, P2Y4, P2Y6, P2Y11, P2Y12, P2Y13, P2Y14) [4,5]; the P2X family is composed of seven cloned subtypes (P2X1-P2X7) [6,7]. We have previously quantified P2 receptor mRNA expression in platelets (representing megakaryocyte expression), and demonstrated a selective expression of the ADP receptors P2Y12 and P2Y1, together with the ATP receptor P2X1 [8]. This is consistent with the clinical effect of the P2Y12 antagonist clopidogrel for the prevention of myocardial infarctions in patients with acute coronary syndromes [9,10]. However, virtually every hematopoietic cell is responsive to nucleotides [2]. Because effects as different as proliferation, differentiation, chemotaxis and release of cytokines are regulated by nucleotides, they could play a role in the atherosclerotic inflammatory process. Human lymphocytes, monocytes and macrophages constitute an important line of defence upon infection and exposure to inflammatory stimuli [11]. Circulating blood monocytes become activated, migrate to tissues, and undergo differentiation into macrophages during inflammation [12]. Monocytes have been shown to express several P2Y receptors and up-regulation of P2X7 receptor mRNA in monocytes has been observed upon cell differentiation to macrophages [13,14]. Although pharmacological experiments have suggested the presence of several P2 receptor subtypes on monocytes and lymphocytes, some results are contradictory [1,2]. Few physiological functions have been firmly established to a specific receptor subtype, partly because of a lack truly selective agonists and antagonists. This stimulated us to investigate the expression of P2X and P2Y receptors in human lymphocytes and monocytes with a newly established quantitative mRNA assay for P2 receptors [8,15]. In addition, we describe for the first time the mRNA expression of P2 receptors in CD34+ stem and progenitor cells implicating a potential role of P2 receptors in hematopoietic lineage and progenitor/stem cell function. Results and Discussion Our previous studies of P2 receptor mRNA expression in man with real-time PCR has shown a good resemblance with pharmacological and physiological experiments in vascular smooth muscle cells, endothelial cells and platelets [8,15]. It is therefore likely that our present mRNA findings in inflammatory, progenitor and stem cells are physiologically relevant. The lack of selective agonists and antagonists for most of the receptor subtypes combined with the absence of studies focused on several of the more recently cloned receptors makes the findings important. Furthermore, no pharmacological studies have been made on CD34+ stem and progenitor cells. Expression of P2Y receptors in lymphocytes In lymphocytes, all the target genes P2Y1, P2Y2, P2Y4, P2Y6, P2Y11, P2Y12, and P2Y13 could be detected (n = 6). To illustrate expression of the P2 receptors relative to each other the P2Y1 receptor was used as calibrator for the others, i. e. the other receptors were expressed as a ratio of the P2Y1. Among the P2Y receptor subtypes the P2Y12 and P2Y2 had highest expression (Figure 1A). The lowest expressed P2Y receptor was P2Y4. Figure 1 Relative P2 gene expression in lymphocytes. A, Bar graph shows relative P2Y1, P2Y2, P2Y4, P2Y6, P2Y11, P2Y12 and P2Y13 receptor gene expression normalized to GAPDH. B, Bar graph shows relative P2X1, P2X4 and P2X7 receptor gene expression normalized to GAPDH. P2Y1 was chosen to be calibrator. Extracellular nucleotides and their P2 receptors are involved in the regulation, proliferation but also apoptosis and cell death in lymphocytes and monocytes [3,16]. Previous studies have shown that ATP, ADP, UTP and UDP stimulate phospholipase C and Ca2+ release from intracellular stores, that fits well with the highly expressed P2Y2 receptor, together with the lesser expressed P2Y1 and P2Y6 receptors. ATP and ADP, but not UTP, can also increase cAMP [17]. This is in agreement with the P2Y11 receptor that had the third highest mRNA expression. The most interesting finding was that P2Y12 had the highest expression among the P2Y receptors in lymphocytes. It is not likely that this is the result of platelet contamination, because platelets contain very low amounts of RNA. To the best of our knowledge, there are no studies that have examined the effects of P2Y12 on lymphocytes, even though selective antagonists exist. It is expected to inhibit cAMP generation and may activate lymphocytes. This could explain the antiinflammatory effect of clopidogrel. Clopidogrel is a P2Y12 antagonist used in the clinic as a platelet aggregation inhibitor that reduces thrombotic cardiovascular events such as myocardial infarctions. However, it has also been shown to reduce CRP, even though aspirin in antiplatelet doses lacks this effect [18]. This effect may be mediated via P2Y12 receptors in lymphocytes. Expression of P2X receptors in lymphocytes The most abundant P2X receptor in lymphocytes was the P2X4 receptor. As showed in Figure 1B, the expression of P2X4 was 3.2 times higher than P2Y1. The expression of P2X4 was significantly higher than the expression of the other P2X receptors; P2X1 (P < 0.001) and P2X7(P < 0.01). Selective pharmacological tools to discriminate between P2X receptors are scarce. Nevertheless, several studies have suggested the importance of P2X7 in lymphocyte regulation. However, B lymphocytes stimulated with ATP do not undergo the typical increase in permeability up to 900 Da that is typical for the P2X7 receptor. On the other hand, P2X7 mediated effects on Ba2+ and ethidium influx, phospholipase D activity and shedding of L-selectin have been blocked by the P2X7 selective antagonist KN-62 in human lymphocytes [19]. Thus it is a surprising finding that the P2X4 receptor was the highest expressed subtype in lymphocytes at the mRNA level. Even though we have demonstrated that more than 90% of the preparation consists of lymphocytes (see methods), it is possible that a small contamination of monocytes may have influenced the results, at least regarding P2X4 receptor mRNA expression, because of its high expression levels in monocytes. P2X4 receptors have indeed been demonstrated at the protein level in human B lymphocytes by confocal immunohistochemistry, in which P2X1, P2X4 and P2X7 were detected at the protein level [20]. However, the P2X4 receptor staining was the most variable of the P2X receptors with weak to moderate levels of staining in a large proportion of cells in three patients and weak levels in only a minority of the cells from the other three patients examined [20]. Expression of P2Y receptors in monocytes Again, the P2Y1 expression was used as calibrator for the others, i. e. the other receptors were expressed as a ratio of the P2Y1. Among the P2Y receptors, the P2Y2, P2Y13 and P2Y11 had highest expression (Figure 2A, n = 6). The presence of P2Y receptor mRNA in monocytes and lymphocytes is in agreement with previous studies using regular RT-PCR [21]. Figure 2 Relative P2 gene expression in monocytes. A, Bar graph shows relative P2Y1, P2Y2, P2Y4, P2Y6, P2Y11, P2Y12 and P2Y13 receptor gene expression normalized to GAPDH. B, Bar graph shows relative P2X1, P2X4 and P2X7 receptor gene expression normalized to GAPDH. P2Y1 was chosen to be calibrator. Extracellular nucleotides stimulate interleukin secretion, iNOS-generation in monocytes, are involved in differentiation, cytotoxicity and killing of pathogens. All monocyte/macrophage cell lines express P2Y receptors coupled to IP3 generation and intracellular Ca2+ release, but the individual subtypes have not been investigated in detail in monocytes [2,3]. However, both ATP and UTP are active agonists, which is in agreement with the highest mRNA expression of the ATP/UTP receptor P2Y2 (Fig 2). ATP mediated increase in cAMP has suggested the presence of P2Y11, with a suggested role in maturation of human monocyte-dendritic cells [22]. A relatively high expression of P2Y11 was confirmed in our experiments. Interestingly, the P2Y13 had even higher mRNA levels. To our knowledge, no experiments have addressed the presence of this cAMP inhibitory ADP receptor in monocytes. In fact, it has been an unresolved issue in what tissue this receptor is expressed. High levels in the spleen could be in agreement with monocyte expression [23]. Thus, the presence of P2Y2 and P2Y11 receptors are confirmed as expected, with the interesting addition of P2Y13 receptors. Future experiments addressing the physiological role of P2Y13 receptors in monocytes are needed. Expression of P2X receptors in monocytes Early studies demonstrated that ATP activates a receptor on macrophages that increase cell permeability eventually leading to cell death [2,3]. P2X7 receptor transfection confers susceptibility to ATP-dependent permeabilization and ATP-resistant clones lack the P2X7 receptor, demonstrating that it is present on macrophages and necessary for permabilization. However, it is not known whether P2X7 is the only constitutive subunit or if it assembles with other subunits. As showed in Figure 2B, P2X4 was by far the highest expressed P2 receptor in monocytes and the P2X1 (P < 0.01) and P2X7 (P < 0.01) had lower levels. Thus, unexpectedly the P2X7 receptor was not the highest expressed P2X receptor in monocytes. This is in agreement with patch-clamp experiments suggesting that other P2X receptors are involved [24]. Interrelation of these experiments has suggested the contribution of P2X4 receptors, which is supported by our findings [25]. It should be noted that all the three P2X receptors were expressed at very high levels compared to other cell types (30-fold more than the calibrator gene for P2X4 and 6–7-fold more for P2X1 and P2X7). A physiological role for all three subtypes can therefore be expected. Expression of P2 receptors in CD34+ stem and progenitor cells CD34+ stem and progenitor cells are receiving an increasing attention because of their extensive self-renewal and multilineage differentiation ability making them attractive for cellular therapy [26]. Knowledge of their P2 receptor expression could be used for directing differentiation or for further subtype selection of early progenitors types. There are no previous pharmacological or expression studies of P2 receptors on human CD34+ stem and progenitor cells. We found expression of several P2Y receptors, especially P2Y1 and P2Y2 (Figure 3A, n = 3). This indicates that both ATP and UTP are agonists for CD34+ stem and progenitor cells and may stimulate IP3 and intracellular Ca2+ release. Figure 3 Relative P2 gene expression in CD34+ stem and progenitor cells. A, Bar graph shows relative P2Y1, P2Y2, P2Y4, P2Y6, P2Y11, P2Y12 and P2Y13 receptor gene expression normalized to GAPDH. B, Bar graph shows relative P2X1, P2X4 and P2X7 receptor gene expression normalized to GAPDH. P2Y1 was chosen to be calibrator. Among the P2X receptors the P2X1 receptor had the highest expression followed by P2X4 (P2X1 had significantly higher expression than P2X7, P < 0.05) (Figure 3B, n = 3), suggesting a potential role of these receptors in regulation of stem and progenitor cells. P2Y1, P2Y2 and P2X1 receptors have all been shown to stimulate proliferation, but also to be able to mediate apoptosis [26]. Such roles could be of major importance in the highly proliferative CD34+ stem and progenitor cells. Antagonists or agonists of these receptors could be used to control their differentiation or proliferation. Conclusions The P2X4 receptor had the highest mRNA expression in lymphocytes and monocytes. Among the P2Y receptors, P2Y12 and P2Y2 had highest expression in lymphocytes, while the P2Y2 and P2Y13 had highest expression in monocytes. The most interesting findings were the high mRNA expression of P2Y12 receptors in lymphocytes potentially explaining the anti-inflammatory effects of clopidogrel, P2Y13 receptors in monocytes and a previously unrecognised expression of P2X4 in lymphocytes and monocytes. In addition, for the first time P2 receptor mRNA expression patterns have been studied in CD34+ stem and progenitor cells. Several P2 receptors were expressed (P2Y2, P2Y1, P2Y12, P2Y13, P2Y11, P2X1, P2X4), indicating a role in differentiation and proliferation. Thus, it is possible that specific antibodies to P2 receptors could be used to identify progenitors for monocytes, lymphocytes and megakaryocytes. Methods The studies were approved by the local Ethics Committee of the Lund University and were conducted according to the principles of the Declaration of Helsinki. Preparation of monocytes and lymphocytes Peripheral blood was drawn from each of 6 healthy volunteers (after informed consent) into heparin vials. The mononuclear cells were isolated by density gradient centrifugation on Lymphoprep™ (Axis Shield Poc AS, Oslo, Norway) at 605 g for 30 minutes. The lymphocytes and monocytes thus obtained were washed three times in RPMI 1640 medium with L-glutamine (Gibco/BRL, Life Technologies Ltd, Paisleys, Scotland) and 0.1% human serum albumin (Sigma, St Louise, MO, USA), (medium), and centrifuged each time at 605 g for 5 minutes. The fraction of lymphocytes and monocytes obtained according to this procedure was resuspended in medium with 15% normal human serum (NHS) added to a concentration of 4 × 106 cells/ml. Flow cytometry (Epics XL-MCL Beckman-Coulter, Florida, USA) analysis on these cells by detection of cell surface CD14 and CD45 showed that approximately 10% of the cells were monocytes. 800 μl of this cell-suspension was plated on a chamber slide 4 well glass slide (Nalge Nunc International, IL, USA) at 37°C in an atmosphere containing 5% CO2 and 96% humidity for 1 h in order for the monocytes to adhere. Nonadherent cells were removed by washing three times with medium. Flow cytometry analysis of these nonadherent cells showed that at least 90% were lymphocytes, and were therefore used as source of lymphocytes. The cells attached to the glass slides (<90% monocytes as assessed by flow cytometry) were detached by adding first PBS and then 0.5 mM EDTA-PBS for 3 min in room temperature. Preparation of CD34+ stem and progenitor cells Bone marrow samples were obtained from healthy volunteers (n = 3), after informed consent, using guidelines approved by the Ethical Committee, Lund University. Mononuclear cells were isolated by density gradient centrifugation (Ficoll-Paque; Pharmacia, Uppsala, Sweden). CD34+ cells were isolated by 2passages through magnetic columns (MidiMacs;Miltenyi Biotec, Bergish Gladbach, Germany) by using a hapten-conjugated CD34 antibody (Qbend/10) and an antihapten antibody conjugated to magnetic beads (CD34+ isolation kit; Miltenyi Biotec). CD34 expression was analyzed by immunostaining with a FACSCalibur flow cytometer (Becton Dickinson) by using the CellQuest program (Becton Dickinson) and the purity of isolated populations was reproducibly > 95% [27]. RNA extraction Total cellular RNAs were extracted using TRIzol reagent (Gibco BRL, Life Technology) according to the supplier's instructions, dissolved in diethyl-pyrocarbonate (DEPC) treated water and stored at -70°C until used. Quantitative analysis of P2 receptors by real-time reverse transcription polymerase chain reaction TaqMan Reverse Transcription Reagents Kit was used to transcribe mRNA into cDNA. Real-time PCR were performed by means of a PRISM 7700Sequence Detector as described previously [8,15,28,29]. Oligonucleotide primers and TaqMan probes were designed using the Primer Express software, based on sequences from the GenBank database [8,15]. Constitutively expressed GAPDH were selected as endogenous control to correct for potential variation in RNA loading or efficiency of the amplification reaction. Previous analysis showed that amplification efficiencies were almost identical for GADPH and the following receptor mRNAs: P2Y1, P2Y2, P2Y4, P2Y6, P2Y11, P2Y12, P2Y13, P2X1, P2X4, and P2X7 normalized to GAPDH [8,15]. To confirm equal amplification efficiencies, we used the criterion of a regression slope of less than 0.1 for each gene normalized to GAPDH. This confirms that we could use the comparative CT method for the relative quantification of target without running standard curves on the same plate (Perkin-Elmer Applied Biosystems Inc; User Bulletin No. 2, December 1997). The amount of target and endogenous reference was determined from the comparative CT method. The target gene normalized to GAPDH was expressed as ΔCT (CT of target gene minus CT of GAPDH). P2Y1 was arbitrarily chosen to be the calibrator in the comparative analysis and is expressed as ΔCTP2Y1 (CT of target minus CT of GAPDH for P2Y1). The normalized calibrated value is given by the equation 2-ΔΔCt, where ΔΔCT is ΔCT -ΔCTP2Y1. To further verify the specificity of PCR assays, the PCR was performed with non-reverse-transcribed total cellular RNA and samples lacking the DNA template. No significant amplifications were obtained in any of these samples (data not shown). Drugs Unless otherwise stated, all reagents and drugs were purchased from Sigma Chemical Corp, St. Louis, MI, USA. PCR consumables were obtained from Perkin-Elmer Applied Biosystems Inc, Foster City, CA, USA. Statistical methods Data are expressed as mean and standard error of the mean (SEM) unless otherwise stated. n indicates the number of subjects that were tested. Statistical analysis of the normalized CT values (ΔCT) was performed with a one-way ANOVA, followed by a multiple comparison post test (Tukey's test) using GraphPad InStat version 3.00 (GraphPad Software Inc., USA). Significant differences were considered at P < 0.05 (two-tailed test). Authors' contributions LW designed the study, carried out the RNA isolation and real-time PCR, and wrote the manuscript. SEWJ supervised the isolation of CD34+ stem and progenitor cells, and participated in writing the manuscript. AB supervised the isolation of monocytes and lymphocytes, and participated in writing the manuscript. DE conceived the study, guided throughout the study, and wrote the manuscript. All authors read and approved the final manuscript. Acknowledgments The study has been supported by the Swedish Heart and Lung Foundation, Franke and Margareta Bergqvist Foundation, the Wiberg Foundation, the Bergwall Foundation, the Zoegas Foundation, the Tore Nilsson Foundation, and Swedish Medical Research Council Grant 13130. ==== Refs Kunapuli SP Daniel JL P2 receptor subtypes in the cardiovascular system Biochem J 1998 336 513 523 9841859 Di Virgilio F Chiozzi P Ferrari D Falzoni S Sanz JM Morelli A Torboli M Bolognesi G Baricordi OR Nucleotide receptors: an emerging family of regulatory molecules in blood cells Blood 2001 97 587 600 11157473 10.1182/blood.V97.3.587 Sak K Boeynaems JM Everaus H Involvement of P2Y receptors in the differentiation of haematopoietic cells J Leukoc Biol 2003 73 442 447 12660218 10.1189/jlb.1102561 von Kugelgen I Wetter A Molecular pharmacology of P2Y-receptors Naunyn Schmiedebergs Arch Pharmacol 2000 362 310 323 11111826 10.1007/s002100000310 Hollopeter G Jantzen HM Vincent D Li G England L Ramakrishnan V Yang RB Nurden P Nurden A Julius D Conley PB Identification of the platelet ADP receptor targeted by antithrombotic drugs Nature 2001 409 202 207 11196645 10.1038/35051599 Norenberg W Illes P Neuronal P2X receptors: localisation and functional properties Naunyn Schmiedebergs Arch Pharmacol 2000 362 324 339 11111827 10.1007/s002100000311 Khakh BS Burnstock G Kennedy C King BF North RA Seguela P Voigt M Humphrey PP International union of pharmacology. 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10.1186/1471-2172-5-16

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==== Front BMC OphthalmolBMC Ophthalmology1471-2415BioMed Central London 1471-2415-4-101529196310.1186/1471-2415-4-10Research ArticleCorneal topographic changes following retinal surgery Sinha Rajesh 1sinharaj1@rediffmail.comSharma Namrata 1namrata103@hotmail.comVerma Lalit 1lalitverma@yahoo.comPandey RM 2rasikvajpayee@rediffmail.comVajpayee Rasik B 1rasikvajpayee@rediffmail.com1 Rajendra Prasad Centre for Ophthalmic Sciences, All India Institute of Medical Sciences, New Delhi, India2 Department of Biostatistics, All India Institute of Medical Sciences, New Delhi, India2004 3 8 2004 4 10 10 2 5 2004 3 8 2004 Copyright © 2004 Sinha et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background To study the effect of retinal/ vitreoretinal surgeries on corneal elevations. Methods Patients who underwent retinal/ vitreoretinal surgeries were divided into 3 groups. Scleral buckling was performed in 11 eyes (Group 1). In 8 (25%) eyes, vitreoretinal surgery was performed along with scleral buckling (Group 2). In 12 eyes, pars plana vitrectomy was performed for vitreous hemorrhage (Group 3). An encircling element was used in all the eyes. The parameters evaluated were best-corrected visual acuity (BCVA), change in axial length, and corneal topographic changes on Orbscan topography system II, preoperative and at 12 weeks following surgery. Results There was a statistically significant increase in anterior corneal elevation in all the three groups after surgery (p = 0.003, p = 0.008 & p = 0.003 respectively). The increase in posterior corneal elevation was highly significant in all the three groups after surgery (p = 0.0000, p = 0.0001 & p = 0.0001 respectively). The increase in the posterior corneal elevation was more than the increase in the anterior elevation and was significant statistically in all the three groups (group I: p = 0.02; group II: p = 0.01; group III: p = 0.008). Conclusions Retinal/ vitreoretinal surgeries cause a significant increase in the corneal elevations and have a greater effect on the posterior corneal surface. anterior corneal elevationposterior corneal elevationscleral bucklingretinal surgery ==== Body Background Changes in corneal curvature and axial length have been reported following scleral buckling procedure using keratometer [1-7]. Videokeratography has also been used to assess the corneal surface changes after buckling procedure[8]. All these studies have reported a change in the corneal curvature in its anterior surface. However, no study has been performed to evaluate the posterior corneal topographic changes with scanning slit topography system following retinal surgeries. Hence, we made an attempt to study the effect of various retinal surgeries on posterior corneal surface using Orbscan II topography system. Methods A prospective study was performed by enrolling patients admitted in the Retina Services of Rajendra Prasad Centre for Ophthalmic Sciences, New Delhi for retinal/ vitreoretinal surgeries. Thirty one eyes of 31 patients who underwent retinal/ vitreoretinal surgery and came for regular follow-up as per schedule during the period between December 2001 and October 2002 were included in the study. Only those patients were included who had not undergone any previous ocular surgery & did not have any corneal pathology. An informed consent was obtained from all the patients. The patients were evaluated preoperatively on parameters of best-corrected visual acuity (BCVA), axial length (AL) measured by Ultrasound A-scan instrument (Sonomed, Inc., NY) and detailed corneal examination on slit-lamp biomicroscope and on Orbscan topography system II (Bausch and Lomb, Salt Lake City, Utah). The parameters that were evaluated by Orbscan topography system were anterior elevation, posterior elevation and simulated keratometry. All surgeries were performed by a single surgeon (LV) under local anesthesia by peribulbar injection of 6 ml of 2% xylocaine and 2 ml of 0.5% bupivacaine. Eyes with fresh retinal detachment with clear media and absence of advanced proliferative vitreoretinopathy underwent scleral buckling procedure (Group I, n = 11). In all these eyes, the break/ s were localized, cryotherapy was performed and subretinal fluid was drained. Only circumferential buckle of silicone of style 276 (Labtician Ophthalmics, Inc., Oakville, Canada) was used and radial buckle or sponge was not used in any eye. The size of the buckle was 90° to 360° depending upon the requirement in individual cases. Encircling element of style 240 (Labtician Ophthalmics, Inc., Oakville, Canada) was used in all the eyes undergoing scleral buckling. In eyes with associated vitreous hemorrhage or advanced proliferative vitreoretinopathy changes along with retinal detachment, vitreoretinal surgery was performed along with scleral buckling (Group II, n = 8). Pars plana vitrectomy was performed and vitreoretinal membranes were removed either by peeling or by segmentation or delamination. Air fluid exchange was performed followed by Air-Silicone oil exchange. In eyes with only vitreous hemorrhage without the presence of retinal detachment, only pars plana vitrectomy was performed (Group III, n = 12). An encircling element of style 240 (Labtician Ophthalmics, Inc., Oakville, Canada) was used in all these eyes to counter the anterior traction that could not be fully released by vitrectomy in order to avoid lens damage. The intraoperative details including the nature of surgery, size of the buckle, encircling element, drainage of subretinal fluid, vitrectomy & use of silicone oil or gas, were noted. Postoperative treatment included topical ciprofloxacin 0.3% QID, topical dexamethasone 0.1% QID and topical Homatropine 2% QID. The patients were evaluated at 12 weeks following surgery on similar (preoperative) parameters. Statistical analysis The data of all the patients were managed on an excel spreadsheet. All the entries were checked for any possible keyboard error. Preoperative and postoperative measurements in the three retinal surgery groups were summarized by mean and standard deviation. Changes following surgery within each group were assessed using paired 't' test. Preoperative and postoperative values in the three groups were compared using one way analysis of variance (ANOVA), followed by bon ferroni correction for multiple comparison. For the three retinal surgery groups, median was computed for increase in various parameters due to surgery. Kruskal Wallis one way analysis of variance was used to compare median increase in the three groups. STATA 7.0 statistical software was used for data analysis. In this study, p-value smaller than 0.05 was considered as statistically significant. Results The mean age of the patients was 45.96 ± 15.17 (range: 18–78) years and majority (83.87%) of the patients (N = 31) were males. Of these, right eye was operated in 19 (61.29%) patients. The mean preoperative best-corrected visual acuity (BCVA) was hand motion close to face in 26 eyes; counting finger near to face in 4 eyes and 1/60 on snellen's acuity chart in 1 eye. The mean decimal postoperative BCVA was 0.20 ± 0.12 at 12 weeks follow-up after surgery. The mean preoperative anterior corneal elevation as recorded by Orbscan II topography system in group I was 0.006 ± 0.007 mm, which increased to 0.024 ± 0.013 mm at 12 weeks after surgery (p= 0.003). In group II, it increased from 0.009 ± 0.006 mm preoperatively to 0.021 ± 0.010 mm at 12 weeks (p= 0.008) and in group III, it increased from 0.003 ± 0.004 mm preoperatively to 0.012 ± 0.007 mm at 12 weeks follow-up (p = 0.003). On comparative evaluation between the groups, the change in anterior corneal elevation was significant between group I and III (p = 0.04). The mean posterior elevation in group I increased from a preoperative value of 0.016 ± 0.010 mm to 0.043 ± 0.007 mm at 12 weeks after surgery (p= 0.0000). In group II, it increased from 0.014 ± 0.006 mm preoperatively to 0.043 ± 0.007 mm at 12 weeks (p= 0.0001) and in group III it increased from a preoperative value of 0.012 ± 0.005 mm to 0.029 ± 0.006 mm at 12 weeks after surgery (p = 0.0001). A comparative analysis between the groups indicated that the increase in posterior corneal elevation between groups I & III and groups II & III were found to be highly significant (I vs III: p= 0.001; II vs III: p= 0.001). Again, the increase in the posterior corneal elevation was greater than the increase in the anterior elevation in all the 3 groups and on comparative evaluation, the difference in the increase in posterior and anterior elevation was significant statistically in each group (group I: p = 0.02; group II: p = 0.01; group III: p = 0.008). The mean corneal astigmatism in group I increased from 0.89 ± 0.54D preoperatively to 2.50 ± 1.39D at 12 weeks follow-up (p= 0.004). In group II, the average corneal astigmatism increased from 0.87 ± 0.30D to 3.38 ± 2.15D at 12 weeks (p= 0.01) and in group III, the mean preoperative and postoperative corneal astigmatism was 0.85 ± 0.55D and 1.37 ± 0.87D respectively (p= 0.02). A comparative analysis of the change in corneal astigmatism following surgery between groups II & III was significant statistically (p= 0.02). The mean preoperative axial length in group I was 23.27 ± 0.79 mm which increased to 23.98 ± 0.76 mm at 12 weeks after surgery (p= 0.009). The mean preoperative and postoperative (12 weeks follow-up) axial length in group II were 23.92 ± 1.32 mm and 25.94 ± 2.96 mm respectively (p= 0.03). The mean preoperative and postoperative axial length in group III were 22.69 ± 0.87 mm and 22.71 ± 0.83 mm respectively (p= 0.79). Comparative analysis of increase in axial length following surgery between groups I & III and groups II & III were found to be significant statistically (I & III: p = 0.003; II & III: p = 0.003). Discussion Retinal surgery with or without the use of encircling and buckling elements for external tamponade can alter the shape of the globe. This may cause changes in the refractive status of the eye. Scleral buckling is known to cause a change in the shape of the sclera and can cause induced refractive changes, including astigmatic and nonastigmatic changes [5-10]. We have used Orbscan slit scanning system II to evaluate the corneal topographic changes following retinal/ vitreoretinal surgeries. The data accumulated by Orbscan may be limited by factors such as the accuracy of the system which is ± 20 μm, the measurement noise which leads to both positive and negative difference in the height of the posterior corneal surface and the necessity of aligning the posterior surface before and after surgery which may be a source of error[11,12]. However, this is the best tool available to study the posterior corneal elevation. In the present study, there was a significant increase in both anterior and posterior corneal elevation as detected by scanning slit topography (Orbscan II topography system) following surgery. This increase in the anterior and posterior corneal elevation is probably due to the use of encircling element and/ or buckle in retinal surgeries resulting in corneal steepening. We noted that the change in the posterior elevation was more significant than anterior elevation. A comparative analysis between the three groups indicated that there was no significant difference in the anterior elevation; however the posterior elevation was significantly more in eyes with buckle. It is possible that the buckle and the encircling element have a greater effect on the posterior corneal surface. The increase in the anterior and posterior corneal elevation might be one of the contributing factors for the non improvement of visual acuity in an eye that has undergone retinal/ vitreoretinal surgery. This change might escape detection by routine videokeratography. The anterior protrusion of the corneal back surface induces an increase in the negative power of the corneal surface. Assessing the corneal surface by keratometry or placido disc videokeratography may provide inadequate information regarding refractive change caused by corneal surface alteration that results in retinal/ vitreoretinal surgery. There was an increase in mean corneal astigmatism following surgery in all the groups. This is due to the effect of encircling element or buckle on the corneal surface. Studies have reported that induced astigmatism has been associated with radial scleral buckles[5,13], circumferential buckles[14], medial rectus disinsertion[15], anterior location of the scleral buckle[13], and use of sponge material rather than hard silicone[1]. In our study, a comparative analysis between the groups indicated that buckle causes more astigmatic changes than encircling element. In retinal/ vitreoretinal surgeries, the encircling band creates a circular indentation of the eye, thereby increasing its anteroposterior axial length; the myopic shift may be upto 3 diopters (D)[9,10,13,16]. An increase in axial length by 0.54 mm[9] and 1.7 mm[14] has been reported following scleral buckling in two studies. In the present study, there was an increase in the mean axial length of the eyes in all the three groups (Table 1). This increase in axial length may be attributed to an anteroposterior elongation of the eyeball secondary to the transverse compression by the buckle and/ or an encircling element. The postoperative increase in axial length was found to be more pronounced in eyes with buckle. Buckle being wider and thicker results in greater indentation and thereby a greater increase in axial length than encircling element. Conclusions Retinal/ vitreoretinal surgeries result in an increase in the elevation of the corneal surfaces. These changes are more pronounced on posterior corneal surface. Declaration of competing interest None declared. Individual contribution of authors RS designed the study and performed the data collection. NS wrote the manuscript. LKV performed the retinal surgeries. RMP performed the statistical analysis and RBV followed up the patients. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here: ==== Refs Mensher JH Burton TC Blodi FC Corneal curvature changes after scleral buckling. In Current concepts in ophthalmology 1974 St Louis: Mosby 38 45 Opauszky A Berksik P Geli K Astigmatism after retinal detachment surgery. Twelfth Pan Hellenic Ophthalmological Congress 1979 47 505 13 Goel R Crewdson J Chignell AH Astigmatism following retinal detachment surgery. Br J Ophthalmol 1983 67 327 9 6838807 Fiore JV JrNewton JC Anterior segment changes following the scleral buckling procedure. Arch Ophthalmol 1970 84 284 7 5457480 Burton TC Irregular astigmatism following episcleral buckling procedure with the use of silicone rubber sponges. Arch Ophthalmol 1973 90 447 448 4759429 Mensher JH Burton TC Blodi F Corneal curvature changes after scleral buckling. Current Concepts in Ophthalmology 1974 St. Louis, MO: C. V. Mosby Co v. IV, chap. 4 Watanabe K Emi K Hamano T Corneal topographic evaluation of retinal detachment surgery. Nippon Ganka Gakai Zasshi 1988 92 367 371 Hayashi H Hayashi K Nakao F Hayashi F Corneal shape changes after scleral buckling surgery. Ophthalmology 1997 104 831 7 9160030 Burton TC Herron BE Ossoinig KC Axial length changes after retinal detachment surgery. Am J Ophthalmol 1977 83 59 62 835668 Smiddy WE Loupe DN Michels RG Refractive changes after retinal detachment surgery. Arch Ophthalmol 1989 107 1469 71 2803094 Maloney RK Discussion. Ophthalmology 1999 106 409 10 Comment on: Ophthalmology 1999; 106: 406-9 10.1016/S0161-6420(99)90087-8 Quintela EH Samapunphong S Khan BF Posterior corneal surface changes after refractive surgery. Ophthalmology 2001 108 1415 22 11470692 10.1016/S0161-6420(01)00634-0 Rubin ML The induction of refractive errors by retinal detachment surgery. Trans Am Ophthalmol Soc 1976 73 452 90 Feki J Mlik M Ould El Hassan M Ben Ayed H Fourati M Zribi W Sellami A Chaabouni M Effect of scleral indentation on the corneal topography and the axial length after retinal detachment surgery. A prospective study in 30 cases. J Fr Ophthalmol 2000 23 351 354 Bivner I Karlin D Alterations in refraction and their clinical significance. Ear Nose Throat J 1958 37 676 678 13586331 Larsen JS Syrdalen P Ultrasonographic study on changes in axial eye dimensions after encircling procedure in retinal detachment surgery. Acta Ophthalmol (copenh) 1979 57 337 43 474079

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BMC Ophthalmol. 2004 Aug 3; 4:10

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BMC Ophthalmol

10.1186/1471-2415-4-10

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==== Front Ann Gen Hosp PsychiatryAnnals of General Hospital Psychiatry1475-2832BioMed Central London 1475-2832-3-131528386710.1186/1475-2832-3-13Primary ResearchBrain choline concentrations may not be altered in euthymic bipolar disorder patients chronically treated with either lithium or sodium valproate Wu Ren H 1wurh20000@sina.comO'Donnell Tina 2tina@gpu.srv.ualberta.caUlrich Michele 2mulrich@ualberta.caAsghar Sheila J 2sheila_canada@yahoo.comHanstock Christopher C 1chris.hanstock@ualberta.caSilverstone Peter H 2peter.silverstone@ualberta.ca1 Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada2 Department of Psychiatry, University of Alberta, Edmonton, Alberta, Canada2004 30 7 2004 3 13 13 30 9 2003 30 7 2004 Copyright © 2004 Wu et al; licensee BioMed Central Ltd.2004Wu et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background It has been suggested that lithium increases choline concentrations, although previous human studies examining this possibility using 1H magnetic resonance spectroscopy (1H MRS) have had mixed results: some found increases while most found no differences. Methods The present study utilized 1H MRS, in a 3 T scanner to examine the effects of both lithium and sodium valproate upon choline concentrations in treated euthymic bipolar patients utilizing two different methodologies. In the first part of the study healthy controls (n = 18) were compared with euthymic Bipolar Disorder patients (Type I and Type II) who were taking either lithium (n = 14) or sodium valproate (n = 11), and temporal lobe choline/creatine (Cho/Cr) ratios were determined. In the second part we examined a separate group of euthymic Bipolar Disorder Type I patients taking sodium valproate (n = 9) and compared these to controls (n = 11). Here we measured the absolute concentrations of choline in both temporal and frontal lobes. Results The results from the first part of the study showed that bipolar patients chronically treated with both lithium and sodium valproate had significantly reduced temporal lobe Cho/Cr ratios. In contrast, in the second part of the study, there were no effects of sodium valproate on either absolute choline concentrations or on Cho/Cr ratios in either temporal or frontal lobes. Conclusions These findings suggest that measuring Cho/Cr ratios may not accurately reflect brain choline concentrations. In addition, the results do not support previous suggestions that either lithium or valproate increases choline concentrations in bipolar patients. Bipolar disorderlithiumsodium valproatemagnetic resonance spectroscopycholine ==== Body Background Bipolar disorder is a chronic severe mental illness affecting approximately 1% of the adult population. The most widely used mood stabilizer for this condition is lithium [1], although the exact mechanism by which it is clinically effective remains undetermined. One suggestion is that it acts via effects on choline metabolism. This is based upon findings that lithium can inhibit the membrane transport of choline in both animals [2], and human post-mortem brain tissue [3]. It also increases the accumulation of erythrocyte choline in lithium-treated patients [4-7]. Also of note is that choline concentrations increase significantly in rats following electroconvulsive shock [8]. Based upon this data choline has been used to treat mania in a some small pilot studies [9], with one open label study reporting that choline augmentation of lithium treatment helped rapid-cyclers [10]. Patients treated with choline also had increased basal ganglia concentrations of choline, suggesting that externally administered choline could alter brain concentrations [11,12]. The most appropriate method to measure brain choline concentrations in vivo utilizes proton magnetic resonance spectroscopy (1H-MRS). Previous studies of bipolar patients utilizing this methodology have had mixed findings. Overall, while some studies have suggested there may be increased choline concentrations in specific situations [13-18], more have found no changes [19-27], and one found a trend towards a decrease in concentrations [28]. In both patients and volunteers lithium also doesn't appear to alter choline/creatine peak ratios concentrations [29,30]. Nonetheless, two reviews concluded that the evidence to date suggests that lithium increases brain choline concentrations [31,32], although as noted in these reviews previous studies have varied considerably in terms of patient populations, brain region studied, medications administered, and MRS methodology. Many studies have also examined differing patients (Type I and Type II) in differing mood states (mixed, depressed, manic, and euthymic). This may partially explain the varied results. Sodium valproate is also widely used as a mood stabilizer, both alone and in combination with lithium [33]. To date there have been few studies which have examined the effects of sodium valproate on choline concentrations or activity. An in-vitro study suggested that valproate may inhibit choline acetyltransferase activity [34]. In one study 9 patients taking either lithium or valproate were examined [35], and increased Cho/Cr ratios were seen in the bipolar patients compared to controls. There were no differences between the lithium and valproate treatment groups, although the sample sizes were small. However, another study in epilepsy patients treated with valproate found no changes in choline concentrations [36]. Nonetheless, given the lack of studies to date, the possibility that valproate and lithium may both increase choline concentrations warrants further investigation. Most of the previous studies have examined Cho/Cr ratios. However, it should be noted that the "choline" resonance peak seen in 1H-MRS spectra is composed primarily of phosphocholine and glycerophosphocholine, along with free choline, acetylcholine, and cytidine diphosphate choline. Also, we have shown in animal studies that both lithium and valproate can both decrease creatine concentrations [37]. Therefore, when using Cho/Cr ratios it is not possible to be certain that any changes in this peak represent changes in brain choline concentrations. We were therefore interested to determine if there were any differences in results when using different methodologies, and more specifically to determine if studies using a ratio methodology may have different results from studies utilizing metabolite concentrations. Methods In the first part of the study patients taking either lithium or valproate were examined using the Cho/Cr ratio method, and both Bipolar Type I and Bipolar Type II patients were included who could also be taking other medications. In the second part of this study only Bipolar Type I patients on valproate monotherapy were included, and quantification of choline concentrations was made. Some of the data from the first part of this study has been reported previously [38]. Subjects and Study Design All subjects gave full informed consent, and both studies were approved by the ethics committee at the University of Alberta. Healthy controls were examined using a detailed, but non-standardized, psychiatric interview. They were excluded if there was any personal history, or immediate family history, of psychiatric disorder. For patients, diagnoses were made using DSM-IV criteria for Bipolar Disorder Type I or Type II following detailed psychiatric interview, with additional information being available in almost all cases from long-term psychiatric clinic records. They also had to be taking a dose of either lithium or valproate which maintained their blood levels within the ranges of 0.4–1.2 mmol/l for lithium and 200–700 μmol/l for sodium valproate. Serum lithium and valproate levels were also measured on the day of MRS scanning. Other medications taken by the patient were noted. In the second part of the study the same criteria were used, except that only patients meeting diagnostic criteria for Bipolar Disorder Type I were included, and they had to be on sodium valproate monotherapy. This was done to examine Bipolar Type I patients in more detail, and to remove a possible confounding variable. All patients had to be euthymic for the previous 3 months, as determined by interviews with the patient, and additional interviews with their relatives and bipolar clinic records when available. MRS scans were carried out within 24 hours of this interview. Magnetic Resonance Spectroscopy Methodology For both studies magnetic resonance experiments were performed using a Magnex 3 T scanner with 80 cm bore equipped with actively shielded gradient, and spectrometer control was provided by an Surrey Medical Imaging System (SMIS) console. The subjects head was immobilized with a restraint system. Signal transmission and reception were achieved using a quadrature birdcage resonator for 1H measurements. Part 1 - Magnetic Resonance Spectroscopy Initially, MRI data were acquired using gradient echo imaging sequences to produce multiple slice images along both coronal and transverse planes. This allowed registration of a 2 × 2 × 3 cm volume-of-interest (VOI) to be selected in the temporal lobe. 1H MR spectra were acquired using the PRESS localization method [39,40], with TE = 32 ms, TR = 3 s, and with 128 averages. Baseline correction and deconvolution of the spectra was accomplished using the Peak Research (PERCH) spectrum analysis software package. The metabolite peaks of interest [choline (Cho) and creatine (Cr)] in each spectrum were fitted to a Gaussian line-shape for peak area estimation. To determine changes in choline concentrations we examined the Cho/Cr ratio. Figure 1 shows an individual 1H MRS spectra in which all the major metabolite peaks can be seen. Figure 1 A typical 1H-MRS spectrum of the human brain at 3.0 T. A number of metabolites can be seen. 1: creatine (methylene) + phosphocreatine, 2: glutamate + glutamine, 3: myo-inositol + glycine, 4: taurine, 5: total choline compounds, 6: creatine (methyl) + phosphocreatine, 7: N-acetylaspartate. Study 2 - Magnetic Resonance Spectroscopy To accurately quantify the brain concentration of creatine we used a 125 ml glass sphere containing a solution of 4 mmol creatine as an external standard. The PRESS sequence was used to acquire proton MRS data with TE1 = 25 msec, TE2 = 25 msec, TR = 3000 msec, and 128 scan averages. The MRS data were acquired from three 2 × 2 × 2 cm3 voxels placed in the cortex of the left frontal lobe, the cortex of the left temporal lobe, and in the external standard solution. The average coordinates [41,42] of the centers of the two brain voxels were determined: x = 0.5 mm (SD = 1.6), y = 63.5 mm (SD = 12.1), z = -25.5 mm (SD = 4.2) in the frontal lobe, and x= 32.2 mm (SD = 6.3), y = 20.5 mm (SD = 3.9), z = 10.7 mm (SD = 2.6) in the temporal lobe. In order to measure T1 and T2 values of the metabolites in the brain and external standard solution, MRS data were collected with different TE values at a constant TR and different TR values at a constant TE both for the healthy volunteers and the patients and also from external standard solution [42]. However, due to these constraints, the fact that the two studies used different populations at different times, and the size of the external 125 ml container (which limited voxel size to 2 × 2 × 2 cm3), it was not possible to exactly match the voxel size or location between the two studies. MRS Data Analysis For quantitative measurement of brain metabolite concentrations we used previously described methodology [42,43]. In this, [Met]b, in millimoles per kg of wet brain, the CSF volume fraction, fcsf, in the spectroscopic voxels must be corrected. Thus, brain metabolite concentrations were calculated as described in the following equation: where Vvoxel is the volume of a 8 cm3 spectroscopic voxel [43], and Nb represents the number of metabolite molecules per unit voxel in brain. Statistical Analysis for both MRS studies Means ± SEM were used in the statistical analysis. Sex differences were analyzed using chi-squared, and age differences with ANOVA with post-hoc Tukey tests. The MRS data was analyzed using Student's unpaired t-test using a significance level of p < 0.05 comparing diagnostic groups (patients vs controls) in each brain region (frontal and temporal). Results Study 1 Subjects A total of 18 healthy controls, 14 bipolar patients taking lithium, and 11 bipolar patients taking valproate completed this study. Of the 14 bipolar patients taking lithium, 7 were Type I and 7 were Type II. In the valproate group, 7 were Type I and 4 were Type II. These groups were studied both separately and together, but as there were no statistically significant differences between the Type I and Type II patients, the results for both types are presented together. Of the 14 bipolar patients taking lithium 12 patients were taking other psychotropic medications: these were benzodiazepines (7 patients), antidepressants (5 patients), and antipsychotics (2 patients). Of the 11 patients taking sodium valproate 10 patients were taking other psychotropic medications: these were benzodiazepines (5 patients), antidepressants (5 patients), and antipsychotics (4 patients). The mean age for the lithium group was 40.43 ± 2.96 years, for the valproate group 35.47 ± 2.27 years, and for the control group was 31.35 ± 2.89 years. These differences were statistically significant (F = 3.68, df = 2, p = <0.05), which was attributable to the lithium group being significantly older than the control group (Tukey post hoc, p < 0.05). There were no gender differences within the groups: 10 females and 8 males in the control group (χ2 = 0.167, df 1, p > 0.05), 5 females and 9 males in the lithium group (χ2 = 1.143, df 1, p > 0.05), and 6 females and 5 males in the valproate group (χ2 = 0.474, df 1, p > 0.05). Mean serum lithium levels were 0.79 ± 0.06 mmol/l, and the range was 0.46–1.08 mmol/l. The mean serum valproate levels were 508 ± 42 μmol/l, and the range was 210–912 μmol/l. MRS Data 1H MRS We utilized the ratio of the choline peak to creatine peak (Cho/Cr) as a primary correlate of Choline concentrations. This result has been reported briefly in a previous publication [38]. The mean Cho/Cr ratio with this measure was 1.46 ± 0.04 for controls, 1.18 ± 0.07 for lithium-treated patients, and 1.12 ± 0.08 for valproate-treated patients. These were statistically significant, with a reduction in ratios occurring in both the control vs. lithium comparison (t = 3.628, df = 30, p = 0.001) and the control vs. valproate comparison (t = 4.248, df = 27, p = 0.002). Study 2 Subjects A total of 11 healthy controls and 9 Bipolar Type I patients taking valproate as monotherapy were entered into this study. The mean age for the control group was 37.3 ± 2.2 years, and for the valproate patients 42.4 ± 3.0 years. These differences were not statistically significant (F = 1.49, df = 1, p = 0.27). There were no gender differences within the groups: 7 females and 2 males in the valproate group and 5 females and 6 males in the control group (χ2 = 0.474, df 1, p > 0.05). The mean serum valproate levels were 472 ± 36 μmol/l, and the range was 284–728 μmol/l. In the frontal lobe the mean choline concentration for the healthy controls was 2.21 ± 0.17 mmol/kg wet brain and for the patients was 2.38 ± 0.12 mmol/kg wet brain. In the temporal lobe the mean choline concentration for the healthy controls was 2.35 ± 0.14 mmol/kg wet brain and for the patients was 2.40 ± 0.19 mmol/kg wet brain. There were no statistically significant differences between the controls and patients in either the frontal (t = 0.78, df = 18, p = 0.44) or temporal (t = 0.203 df = 18, p = 0.84) lobes (Table 1). Table 1 Concentrations (mmol/kg wet brain) and ratios (Cho/Cre) in frontal and temporal lobes in healthy volunteers and in patients chronically treated with valproate (Study #2) Choline (Cho) Creatine (Cre) Cho/Cre Frontal Temporal Frontal Temporal Frontal Temporal Healthy Controls Age Sex 1 50 M 3.51 2.95 6.67 8.53 0.53 0.35 2 45 M 2.19 3.03 10.1 9.11 0.22 0.33 3 43 F 3.01 2.31 9.97 9.52 0.30 0.24 4 39 M 2.11 2.72 7.94 7.60 0.27 0.24 5 37 F 2.47 2.34 9.98 9.89 0.25 0.24 6 36 F 1.91 1.76 8.28 8.19 0.23 0.22 7 35 M 1.76 2.36 7.93 8.36 0.22 0.28 8 32 F 1.88 1.51 9.56 9.56 0.2 0.16 9 32 M 1.94 2.14 7.04 7.79 0.28 0.28 10 30 F 1.82 2.52 7.8 8.63 0.23 0.29 11 28 M 1.72 2.23 7.16 8.51 0.24 0.26 Mean 37.00 2.21 2.35 8.40 8.70 0.27 0.26 Valproate Treated Patients 1 58 F 2.72 2.1 9.16 10.13 0.30 0.21 2 50 M 2.61 3.42 8.17 10.53 0.32 0.33 3 49 F 2.03 1.79 8.56 7.48 0.24 0.24 4 48 F 2.44 1.88 9.93 8.19 0.25 0.23 5 36 M 2.60 2.53 7.84 7.51 0.33 0.34 6 35 F 2.07 2.77 9.26 10.39 0.22 0.27 7 35 F 2.78 1.89 8.35 9.79 0.33 0.19 8 34 F 1.76 2.93 7.26 8.01 0.24 0.37 9 34 F 2.43 2.27 7.75 7.23 0.31 0.31 Mean 42.11 2.38 2.40 8.48 8.81 0.28 0.28 The Cho/Cr ratios in the frontal lobes were 0.27 ± 0.028 in controls and 0.28 ± 0.015 in patients. In the temporal lobes the Cho/Cr ratios were 0.26 ± 0.021 in controls and 0.28 ± 0.016 in patients. There were no statistically significant differences between the controls and patients in either the frontal (t = 0.367, df = 18, p = 0.72) or temporal (t = 0.539, df = 18, p = 0.59) lobes (Table 1). Discussion The results from the present study vary considerably between the two sections utilizing differing methodologies. This is despite the fact that both studies were carried out by the same group on the same scanner with bipolar patients coming from the same patient pool. This strongly suggests that the methodology used to determine choline concentrations can considerably alter the results. In the first part of the study we found that both the lithium-treated and valproate-treated patients had significantly reduced Cho/Cr peak ratios compared to controls. This is similar to the findings from one previous study which also suggested that there may be a trend towards decreased choline in grey matter [28]. This study was a frontal lobe study that measured metabolite concentrations in a 1.5 T scanner in bipolar type I patients hospitalized for manic (n = 9) or mixed (n = 8) states. In this study most patients were being treated with valproate and an atypical antipsychotic. These findings, however, differ from those in the second part of the present study in which we found no differences in choline concentrations between valproate-treated patients and controls in either frontal or temporal lobes. This second part of the study was much better controlled in terms of the patients receiving valproate monotherapy, only including bipolar Type I patients, and in using an external choline solution to accurately quantify choline concentrations. This finding of a lack of change is also in keeping with most previous studies. Several studies which have also previously measured metabolite concentrations with 1.5 T scanners also found no changes. These include a study of the hippocampus in 15 euthymic bipolar type 1 patients, of whom 10 were taking either lithium or valproate [19], a study of basal ganglia in 8 rapid cycling patients on lithium [22], a study of the anterior cingulate in 10 bipolar children [23], and a study in frontal lobes of 23 euthymic bipolar patients of whom 13 were on lithium [25]. Several other studies have examined metabolite ratios, mostly in patients on lithium, and those also found no changes in choline concentrations [20,21,26,27]. In a study using metabolite ratios in bipolar children who were off medication for at least one week there was also no change in choline concentrations [24]. In a double-blind placebo-controlled human volunteer study before and after one week of lithium administration we also found no changes in cholinein 10 volunteers [30], which is similar to a patient study which compared 7 patients on lithium to 6 non-lithium treated controls and in which no differences were seen [29]. In contrast, animal studies have suggested that lithium may increase brain choline concentrations, and in lithium-treated patients it also increases the accumulation of choline within erythrocytes [4-7]. Nonetheless, 1H-MRS studies in patients examining this possibility is mixed. To date 6 studies have suggested some support for this [13-18], but in none of these studies were metabolite concentrations measured, and most of the studies measured choline/creatine ratios [14-18], the other one measuring metabolite intensity/tissue volume [13]. The first study to examine brain choline in basal ganglia studied only 4 patients, all of whom were on lithium [18]. Another study examined 19 euthymic inpatients and found increased choline/creatine ratios in basal ganglia, but only 10 of these patients were receiving lithium [17]. The third study to report an increase in this ratio (in this case in the left subcortical region) was in a mixed group of patients receiving a wide range of medications [16]. Two other studies have reported increased choline concentrations, but only in limited circumstances. In one study in 11 bipolar children patients were examined before and after lithium administration [14]. There were no significant findings before or after lithium administration, although there was a trend towards increased choline/creatine ratios in the patients before lithium treatment. This latter finding does not suggest that in patients lithium significantly alters the choline/creatine ratio. The final study examined 15 euthymic males who were on either lithium or valproate [13]. This study found that thalamic choline concentrations, determined by measuring metabolite intensity/tissue volume ratios, were significantly increased only if the right and left hemisphere were compared separately, but not if they were compared together. It is also conceivable that both lithium and valproate may increase Choline concentrations, but that the differences were not large enough for us to detect, or that without lithium or valproate treatment patients would have lower Choline concentrations. The cross-sectional nature of this study does not allow this to be examined. It is also important to recognize other limitations of the present study. Firstly, these MRS studies are not pre- and post-treatments, so may not accurately reflect changes that occur in individual patients. Secondly, part of the study used a ratio-method to assess choline concentrations, the limitations of which are increasingly clear (particularly since creatine concentrations may be altered by medication [37]). Thirdly, the sizes of all groups are small and it therefore possible that a larger study may have been fully powered to identify differences between groups. Fourthly, several patients in the first study (but not the second study) were on other drugs which may have affected the results of this study. Fifthly, we have not determined if age affects the results, and in the first part the groups were not all matched for age. In addition, the voxel locations were not the same in both studies due to the reasons discussed in the methodology section. Nonetheless, despite these limitations we believe the results add significantly to the literature in this under-researched area. We conclude that, taking all current evidence together including the findings from the present study, it is unlikely that either lithium or valproate significantly alter brain choline concentrations. However, given the large differences in patients populations, medications received, and MRS methodologies it is difficult to directly compare all these studies. In addition, the methodology used to measure choline concentrations can significantly alter the results. Future MRS studies in bipolar patients should, therefore, examine metabolite concentrations rather than a ratio of choline compared to other metabolites. Competing interests None declared. Acknowledgements This work was supported in part by peer-reviewed grants from the Canadian Institutes of Health Research (CIHR) and the Alberta Heritage Foundation for Medical Research (AHFMR). ==== Refs Vestergaard P Licht RW 50 Years with lithium treatment in affective disorders: present problems and priorities World J Biol Psychiatry 2001 2 18 26 12587181 Lingsch C Martin K An irreversible effect of lithium administration to patients Br J Pharmacol 1976 57 323 7 974314 Uney JB Marchbanks RM Reynolds GP Perry RH Lithium prophylaxis inhibits choline transport in post-mortem brain Lancet 1986 2 458 2874439 10.1016/S0140-6736(86)92162-8 Jope RS Jenden DJ Ehrlich BE Diamond JM Choline accumulates in erythrocytes during lithium therapy N Engl J Med 1978 299 833 834 692570 Brinkman SD Pomara N Barnett N Block R Domino EF Gershon S Lithium-induced increases in red blood cell choline and memory performance in Alzheimer-type dementia Biol Psychiatry 1984 19 157 64 6424733 Domino EF Sharp RR Lipper S Ballast CL Delidow B Bronzo MR NMR chemistry analysis of red blood cell constituents in normal subjects and lithium-treated psychiatric patients Biol Psychiatry 1985 20 1277 1283 4063417 10.1016/0006-3223(85)90112-X Stoll AL Cohen BM Hanin I Erythrocyte choline concentrations in psychiatric disorders Biol Psychiatry 1991 29 309 321 2036475 10.1016/0006-3223(91)90216-9 Sartorius A Neumann-Haefelin C Bollmayr B Hoehn M Henn FA Choline rise in the rat hippocampus induced by electroconvulsive shock treatment Biol Psychiat 2003 53 620 623 12679241 10.1016/S0006-3223(02)01600-1 Leiva DB The neurochemistry of mania: a hypothesis of etiology and rationale for treatment Prog Neuropsychopharmacol Biol Psychiatry 1990 14 423 9 2193316 10.1016/0278-5846(90)90030-K Stoll AL Sachs GS Cohen BM Lafer B Christensen JD Renshaw PF Choline in the treatment of rapid-cycling bipolar disorder: clinical and neurochemical findings in lithium-treated patients Biol Psychiat 1996 40 382 8 8874839 10.1016/0006-3223(95)00423-8 Stoll AL Renshaw PF De Micheli E Wurtman R Pillay SS Cohen BM Choline ingestion increases the resonance of choline-containing compounds in human brain: an in vivo proton magnetic resonance study Biol Psychiat 1995 37 170 4 7727625 10.1016/0006-3223(94)00120-R Cohen BM Renshaw PF Stoll AL Wurtman RJ Yurgelun-Todd D Babb SM Decreased brain choline uptake in older adults. An in vivo proton magnetic resonance spectroscopy study JAMA 1995 274 902 7 7674505 10.1001/jama.274.11.902 Deicken RF Eliaz Y Feiwell R Schuff N Increased thalamic N -acetylaspartate in male patients with familial bipolar I disorder Psychiatry Res 2001 106 35 45 11231098 10.1016/S0925-4927(00)00083-4 Davanzo P Thomas MA Yue K Oshiro T Belin T Strober M McCracken J Decreased anterior cingulated myo-inositol/creatine spectroscopy resonance with lithium treatment in children with bipolar disorder Neuropsychopharmacology 2001 24 359 369 11182531 10.1016/S0893-133X(00)00207-4 Moore CM Breeze JL Gruber SA Babb SM deB Frederick B Villafuerte RA Stoll AL Hennen J Yurgelun-Todd DA Cohen BM Renshaw PF Choline, myo-inositol and mood in bipolar disorder: a proton magnetic resonance spectroscopic imaging study of the anterior cingulate cortex Bipolar Disord 2000 2 207 216 11249799 10.1034/j.1399-5618.2000.20302.x Hamakawa H Kato T Murashita J Kato N Quantitative proton magnetic resonance spectroscopy of the basal ganglia in patients with affective disorders Eur Arch Psychiatry Clin Neurosci 1998 248 53 58 9561353 10.1007/s004060050017 Kato T Hamakawa H Shioiri T Murashita J Takahashi Y Takahashi S Inubushi T Choline-containing compounds detected by proton magnetic resonance spectroscopy in the basal ganglia in bipolar disorder J Psychiatry Neurosci 1996 21 248 254 8754593 Sharma R Venkatasubramanian PN Barany M Davis JM Proton magnetic resonance spectroscopy of the brain in schizophrenic and affective patients Schizophr Res 1992 8 43 49 1329928 10.1016/0920-9964(92)90059-E Deicken RF Pegues MP Anzalone S Feiwell R Soher B Lower concentration of hippocampal N-acetylaspartate in familial bipolar I disorder Am J Psychiat 2003 160 873 882 12727690 10.1176/appi.ajp.160.5.873 Bertolino A Frye M Callicott JH Mattay VS Rakow R Shelton-Repella J Post R Weinberger DR Neuronal pathology in the hippocampal area of patients with bipolar disorder: a study with proton magnetic resonance spectroscopic imaging Biol Psychiat 2003 53 906 913 12742678 10.1016/S0006-3223(02)01911-X Chang K Adleman N Dienes K Barnea-Goraly N Reiss A Ketter T Decreased N-acetylaspartate in children with familial bipolar disorder Biol Psychiat 2003 53 1059 1065 12788251 10.1016/S0006-3223(02)01744-4 Lyoo IK Demopulos CM Hirashima F Ahn KW Renshaw PF Oral choline decreases brain purine levels in lithium-treated subjects with rapid-cycling bipolar disorder: a double-blind trial using proton and lithium magnetic resonance spectroscopy Bipolar Disord 2003 5 300 306 12895208 10.1034/j.1399-5618.2003.00041.x Davanzo P Yue K Thomas MA Belin T Mintz J Venkatraman TN Santoro E Barnett S McCracken J Proton magnetic spectroscopy of bipolar disorder versus intermittent explosive disorder in children and adolescents Am J Psychiatry 2003 160 Castillo M Kwock L Courvoisie H Hooper SR Proton MR spectroscopy in children with bipolar affective disorder: preliminary observations Am J Neuroradiol 2000 21 832 838 10815657 Hamakawa H Kato T Shioiri T Inubushi T Kato N Quantitative proton magnetic resonance spectroscopy of the bilateral frontal lobes in patients with bipolar disorder Psychological Med 1999 29 639 644 10.1017/S0033291799008442 Ohara K Isoda H Suzuki Y Takehara Y Ochiai M Takeda H Igarashi Y Ohara K Proton magnetic resonance spectroscopy of the lenticular nuclei in bipolar I affective disorder Psych Res Neuroimag Sect 1998 84 55 60 10.1016/S0925-4927(98)00050-X Bruhn H Stoppe G Staedt J Merboldt KD Hänicke W Frahm J Quantitative proton MRS in vivo shows cerebral myo -inositol and cholines to be unchanged in manic-depressive patients treated with lithium [abstract] Proc Soc Mag Res Med 1993 1543 Cecil KM DelBello MP Morey R Strakowski SM Frontal lobe differences in bipolar disorder as determined by proton MR spectroscopy Bipolar Dis 2002 4 357 365 10.1034/j.1399-5618.2002.02235.x Stoll AL Renshaw PF Sachs GS Guimaraes AR Miller C Cohen BM Lafer B Gonzalez RG The human brain resonance of choline-containing compounds is similar in patients receiving lithium treatment and controls: an in vivo proton magnetic resonance spectroscopy study Biol Psychiatry 1992 32 944 949 1467379 10.1016/0006-3223(92)90184-2 Silverstone PH Hanstock CC Rotzinger S Lithium does not alter the choline/creatine ratio in the temporal lobe of human volunteers as measured by proton magnetic resonance spectroscopy J Psychiatry Neurosci 1999 24 222 226 10354656 Stoll AL Renshaw PF Yurgelun-Todd DA Cohen BM Neuroimaging in bipolar disorder: what have we learned? Biol Psychiatry 2000 48 505 517 11018223 10.1016/S0006-3223(00)00982-3 Strakowski SM DelBello MP Adler C Cecil KM Saz KW Neuroimaging in bipolar disorder Bipolar Disord 2000 2 148 164 11256682 10.1034/j.1399-5618.2000.020302.x Pies R Combining lithium and anticonvulsants in bipolar disorder: a review Ann Clin Psychiatry 2002 14 223 232 12630658 10.1023/A:1021969001231 Sher PK Neale EA Graubard BI Habig WH Fitzgerald SC Nelson PG Differential neurochemical effects of chronic exposure of cerebral cortical cell culture to valproic acid, diazepam, or ethosuximide Pediatr Neurol 1985 1 232 7 3939744 Moore CM Breeze JL Gruber SA Babb SM deB Frederick B Villafuerte RA Stoll AL Hennen J Yurgelun-Todd DA Cohen BM Renshaw PF Choline, myo-inositol and mood in bipolar disorder: a proton magnetic resonance spectroscopic imaging study of the anterior cingulate cortex Bipolar Disord 2000 2 207 216 11249799 10.1034/j.1399-5618.2000.20302.x Simister RJ McLean MA Barker GJ Duncan JS Proton MRS reveals frontal lobe metabolite abnormalities in idiopathic generalized epilepsy Neurology 2003 61 897 902 14557556 O'Donnell T Rotzinger S Nakashima TT Hanstock CC Ulrich M Silverstone PH Chronic lithium and sodium valproate both decrease the concentration of myo-inositol and increase the concentration of inositol monophosphates in rat brain Brain Research 2000 880 84 91 11032992 10.1016/S0006-8993(00)02797-9 Silverstone PH Asghar SJ O'Donnell T Ulrich M Hanstock CC Lithium protects against dextro-amphetamine induced brain choline concentration changes in bipolar disorder patients World J Biol Psychiat 2004 5 35 41 Gordon RE Ordidge RJ Volume selection for high resolution NMR studies [abstract] Proc Soc Magn Reson Med 1984 272 Bottomley PA Spatial localization in NMR spectroscopy in vivo Ann NY Acad Sci 1987 508 333 348 3326459 Talairach J Tournoux P Co-planar stereotaxic atlas of the human brain New York: Thieme Medical 1988 51 110 Huang W Alexander GE Daly EM Shetty HU Krasuski JS Rapoport SI Schapiro MB High brain myo -inositol levels in the predementia phase of Alzheimer's disease in adults with Down's syndrome: a 1H MRS study Am J Psychiatry 1999 156 1879 1886 10588400 Vermathen P Capizzano AA Maudsley AA Administration and (1)H MRS detection of histidine in human brain: application to in vivo pH measurement Magn Reson Med 2000 43 665 675 10800031 10.1002/(SICI)1522-2594(200005)43:5<665::AID-MRM8>3.3.CO;2-V

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Ann Gen Hosp Psychiatry. 2004 Jul 30; 3:13

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Ann Gen Hosp Psychiatry

10.1186/1475-2832-3-13

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==== Front Ann Gen Hosp PsychiatryAnnals of General Hospital Psychiatry1475-2832BioMed Central London 1475-2832-3-131528386710.1186/1475-2832-3-13Primary ResearchBrain choline concentrations may not be altered in euthymic bipolar disorder patients chronically treated with either lithium or sodium valproate Wu Ren H 1wurh20000@sina.comO'Donnell Tina 2tina@gpu.srv.ualberta.caUlrich Michele 2mulrich@ualberta.caAsghar Sheila J 2sheila_canada@yahoo.comHanstock Christopher C 1chris.hanstock@ualberta.caSilverstone Peter H 2peter.silverstone@ualberta.ca1 Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada2 Department of Psychiatry, University of Alberta, Edmonton, Alberta, Canada2004 30 7 2004 3 13 13 30 9 2003 30 7 2004 Copyright © 2004 Wu et al; licensee BioMed Central Ltd.2004Wu et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background It has been suggested that lithium increases choline concentrations, although previous human studies examining this possibility using 1H magnetic resonance spectroscopy (1H MRS) have had mixed results: some found increases while most found no differences. Methods The present study utilized 1H MRS, in a 3 T scanner to examine the effects of both lithium and sodium valproate upon choline concentrations in treated euthymic bipolar patients utilizing two different methodologies. In the first part of the study healthy controls (n = 18) were compared with euthymic Bipolar Disorder patients (Type I and Type II) who were taking either lithium (n = 14) or sodium valproate (n = 11), and temporal lobe choline/creatine (Cho/Cr) ratios were determined. In the second part we examined a separate group of euthymic Bipolar Disorder Type I patients taking sodium valproate (n = 9) and compared these to controls (n = 11). Here we measured the absolute concentrations of choline in both temporal and frontal lobes. Results The results from the first part of the study showed that bipolar patients chronically treated with both lithium and sodium valproate had significantly reduced temporal lobe Cho/Cr ratios. In contrast, in the second part of the study, there were no effects of sodium valproate on either absolute choline concentrations or on Cho/Cr ratios in either temporal or frontal lobes. Conclusions These findings suggest that measuring Cho/Cr ratios may not accurately reflect brain choline concentrations. In addition, the results do not support previous suggestions that either lithium or valproate increases choline concentrations in bipolar patients. Bipolar disorderlithiumsodium valproatemagnetic resonance spectroscopycholine ==== Body Background Bipolar disorder is a chronic severe mental illness affecting approximately 1% of the adult population. The most widely used mood stabilizer for this condition is lithium [1], although the exact mechanism by which it is clinically effective remains undetermined. One suggestion is that it acts via effects on choline metabolism. This is based upon findings that lithium can inhibit the membrane transport of choline in both animals [2], and human post-mortem brain tissue [3]. It also increases the accumulation of erythrocyte choline in lithium-treated patients [4-7]. Also of note is that choline concentrations increase significantly in rats following electroconvulsive shock [8]. Based upon this data choline has been used to treat mania in a some small pilot studies [9], with one open label study reporting that choline augmentation of lithium treatment helped rapid-cyclers [10]. Patients treated with choline also had increased basal ganglia concentrations of choline, suggesting that externally administered choline could alter brain concentrations [11,12]. The most appropriate method to measure brain choline concentrations in vivo utilizes proton magnetic resonance spectroscopy (1H-MRS). Previous studies of bipolar patients utilizing this methodology have had mixed findings. Overall, while some studies have suggested there may be increased choline concentrations in specific situations [13-18], more have found no changes [19-27], and one found a trend towards a decrease in concentrations [28]. In both patients and volunteers lithium also doesn't appear to alter choline/creatine peak ratios concentrations [29,30]. Nonetheless, two reviews concluded that the evidence to date suggests that lithium increases brain choline concentrations [31,32], although as noted in these reviews previous studies have varied considerably in terms of patient populations, brain region studied, medications administered, and MRS methodology. Many studies have also examined differing patients (Type I and Type II) in differing mood states (mixed, depressed, manic, and euthymic). This may partially explain the varied results. Sodium valproate is also widely used as a mood stabilizer, both alone and in combination with lithium [33]. To date there have been few studies which have examined the effects of sodium valproate on choline concentrations or activity. An in-vitro study suggested that valproate may inhibit choline acetyltransferase activity [34]. In one study 9 patients taking either lithium or valproate were examined [35], and increased Cho/Cr ratios were seen in the bipolar patients compared to controls. There were no differences between the lithium and valproate treatment groups, although the sample sizes were small. However, another study in epilepsy patients treated with valproate found no changes in choline concentrations [36]. Nonetheless, given the lack of studies to date, the possibility that valproate and lithium may both increase choline concentrations warrants further investigation. Most of the previous studies have examined Cho/Cr ratios. However, it should be noted that the "choline" resonance peak seen in 1H-MRS spectra is composed primarily of phosphocholine and glycerophosphocholine, along with free choline, acetylcholine, and cytidine diphosphate choline. Also, we have shown in animal studies that both lithium and valproate can both decrease creatine concentrations [37]. Therefore, when using Cho/Cr ratios it is not possible to be certain that any changes in this peak represent changes in brain choline concentrations. We were therefore interested to determine if there were any differences in results when using different methodologies, and more specifically to determine if studies using a ratio methodology may have different results from studies utilizing metabolite concentrations. Methods In the first part of the study patients taking either lithium or valproate were examined using the Cho/Cr ratio method, and both Bipolar Type I and Bipolar Type II patients were included who could also be taking other medications. In the second part of this study only Bipolar Type I patients on valproate monotherapy were included, and quantification of choline concentrations was made. Some of the data from the first part of this study has been reported previously [38]. Subjects and Study Design All subjects gave full informed consent, and both studies were approved by the ethics committee at the University of Alberta. Healthy controls were examined using a detailed, but non-standardized, psychiatric interview. They were excluded if there was any personal history, or immediate family history, of psychiatric disorder. For patients, diagnoses were made using DSM-IV criteria for Bipolar Disorder Type I or Type II following detailed psychiatric interview, with additional information being available in almost all cases from long-term psychiatric clinic records. They also had to be taking a dose of either lithium or valproate which maintained their blood levels within the ranges of 0.4–1.2 mmol/l for lithium and 200–700 μmol/l for sodium valproate. Serum lithium and valproate levels were also measured on the day of MRS scanning. Other medications taken by the patient were noted. In the second part of the study the same criteria were used, except that only patients meeting diagnostic criteria for Bipolar Disorder Type I were included, and they had to be on sodium valproate monotherapy. This was done to examine Bipolar Type I patients in more detail, and to remove a possible confounding variable. All patients had to be euthymic for the previous 3 months, as determined by interviews with the patient, and additional interviews with their relatives and bipolar clinic records when available. MRS scans were carried out within 24 hours of this interview. Magnetic Resonance Spectroscopy Methodology For both studies magnetic resonance experiments were performed using a Magnex 3 T scanner with 80 cm bore equipped with actively shielded gradient, and spectrometer control was provided by an Surrey Medical Imaging System (SMIS) console. The subjects head was immobilized with a restraint system. Signal transmission and reception were achieved using a quadrature birdcage resonator for 1H measurements. Part 1 - Magnetic Resonance Spectroscopy Initially, MRI data were acquired using gradient echo imaging sequences to produce multiple slice images along both coronal and transverse planes. This allowed registration of a 2 × 2 × 3 cm volume-of-interest (VOI) to be selected in the temporal lobe. 1H MR spectra were acquired using the PRESS localization method [39,40], with TE = 32 ms, TR = 3 s, and with 128 averages. Baseline correction and deconvolution of the spectra was accomplished using the Peak Research (PERCH) spectrum analysis software package. The metabolite peaks of interest [choline (Cho) and creatine (Cr)] in each spectrum were fitted to a Gaussian line-shape for peak area estimation. To determine changes in choline concentrations we examined the Cho/Cr ratio. Figure 1 shows an individual 1H MRS spectra in which all the major metabolite peaks can be seen. Figure 1 A typical 1H-MRS spectrum of the human brain at 3.0 T. A number of metabolites can be seen. 1: creatine (methylene) + phosphocreatine, 2: glutamate + glutamine, 3: myo-inositol + glycine, 4: taurine, 5: total choline compounds, 6: creatine (methyl) + phosphocreatine, 7: N-acetylaspartate. Study 2 - Magnetic Resonance Spectroscopy To accurately quantify the brain concentration of creatine we used a 125 ml glass sphere containing a solution of 4 mmol creatine as an external standard. The PRESS sequence was used to acquire proton MRS data with TE1 = 25 msec, TE2 = 25 msec, TR = 3000 msec, and 128 scan averages. The MRS data were acquired from three 2 × 2 × 2 cm3 voxels placed in the cortex of the left frontal lobe, the cortex of the left temporal lobe, and in the external standard solution. The average coordinates [41,42] of the centers of the two brain voxels were determined: x = 0.5 mm (SD = 1.6), y = 63.5 mm (SD = 12.1), z = -25.5 mm (SD = 4.2) in the frontal lobe, and x= 32.2 mm (SD = 6.3), y = 20.5 mm (SD = 3.9), z = 10.7 mm (SD = 2.6) in the temporal lobe. In order to measure T1 and T2 values of the metabolites in the brain and external standard solution, MRS data were collected with different TE values at a constant TR and different TR values at a constant TE both for the healthy volunteers and the patients and also from external standard solution [42]. However, due to these constraints, the fact that the two studies used different populations at different times, and the size of the external 125 ml container (which limited voxel size to 2 × 2 × 2 cm3), it was not possible to exactly match the voxel size or location between the two studies. MRS Data Analysis For quantitative measurement of brain metabolite concentrations we used previously described methodology [42,43]. In this, [Met]b, in millimoles per kg of wet brain, the CSF volume fraction, fcsf, in the spectroscopic voxels must be corrected. Thus, brain metabolite concentrations were calculated as described in the following equation: where Vvoxel is the volume of a 8 cm3 spectroscopic voxel [43], and Nb represents the number of metabolite molecules per unit voxel in brain. Statistical Analysis for both MRS studies Means ± SEM were used in the statistical analysis. Sex differences were analyzed using chi-squared, and age differences with ANOVA with post-hoc Tukey tests. The MRS data was analyzed using Student's unpaired t-test using a significance level of p < 0.05 comparing diagnostic groups (patients vs controls) in each brain region (frontal and temporal). Results Study 1 Subjects A total of 18 healthy controls, 14 bipolar patients taking lithium, and 11 bipolar patients taking valproate completed this study. Of the 14 bipolar patients taking lithium, 7 were Type I and 7 were Type II. In the valproate group, 7 were Type I and 4 were Type II. These groups were studied both separately and together, but as there were no statistically significant differences between the Type I and Type II patients, the results for both types are presented together. Of the 14 bipolar patients taking lithium 12 patients were taking other psychotropic medications: these were benzodiazepines (7 patients), antidepressants (5 patients), and antipsychotics (2 patients). Of the 11 patients taking sodium valproate 10 patients were taking other psychotropic medications: these were benzodiazepines (5 patients), antidepressants (5 patients), and antipsychotics (4 patients). The mean age for the lithium group was 40.43 ± 2.96 years, for the valproate group 35.47 ± 2.27 years, and for the control group was 31.35 ± 2.89 years. These differences were statistically significant (F = 3.68, df = 2, p = <0.05), which was attributable to the lithium group being significantly older than the control group (Tukey post hoc, p < 0.05). There were no gender differences within the groups: 10 females and 8 males in the control group (χ2 = 0.167, df 1, p > 0.05), 5 females and 9 males in the lithium group (χ2 = 1.143, df 1, p > 0.05), and 6 females and 5 males in the valproate group (χ2 = 0.474, df 1, p > 0.05). Mean serum lithium levels were 0.79 ± 0.06 mmol/l, and the range was 0.46–1.08 mmol/l. The mean serum valproate levels were 508 ± 42 μmol/l, and the range was 210–912 μmol/l. MRS Data 1H MRS We utilized the ratio of the choline peak to creatine peak (Cho/Cr) as a primary correlate of Choline concentrations. This result has been reported briefly in a previous publication [38]. The mean Cho/Cr ratio with this measure was 1.46 ± 0.04 for controls, 1.18 ± 0.07 for lithium-treated patients, and 1.12 ± 0.08 for valproate-treated patients. These were statistically significant, with a reduction in ratios occurring in both the control vs. lithium comparison (t = 3.628, df = 30, p = 0.001) and the control vs. valproate comparison (t = 4.248, df = 27, p = 0.002). Study 2 Subjects A total of 11 healthy controls and 9 Bipolar Type I patients taking valproate as monotherapy were entered into this study. The mean age for the control group was 37.3 ± 2.2 years, and for the valproate patients 42.4 ± 3.0 years. These differences were not statistically significant (F = 1.49, df = 1, p = 0.27). There were no gender differences within the groups: 7 females and 2 males in the valproate group and 5 females and 6 males in the control group (χ2 = 0.474, df 1, p > 0.05). The mean serum valproate levels were 472 ± 36 μmol/l, and the range was 284–728 μmol/l. In the frontal lobe the mean choline concentration for the healthy controls was 2.21 ± 0.17 mmol/kg wet brain and for the patients was 2.38 ± 0.12 mmol/kg wet brain. In the temporal lobe the mean choline concentration for the healthy controls was 2.35 ± 0.14 mmol/kg wet brain and for the patients was 2.40 ± 0.19 mmol/kg wet brain. There were no statistically significant differences between the controls and patients in either the frontal (t = 0.78, df = 18, p = 0.44) or temporal (t = 0.203 df = 18, p = 0.84) lobes (Table 1). Table 1 Concentrations (mmol/kg wet brain) and ratios (Cho/Cre) in frontal and temporal lobes in healthy volunteers and in patients chronically treated with valproate (Study #2) Choline (Cho) Creatine (Cre) Cho/Cre Frontal Temporal Frontal Temporal Frontal Temporal Healthy Controls Age Sex 1 50 M 3.51 2.95 6.67 8.53 0.53 0.35 2 45 M 2.19 3.03 10.1 9.11 0.22 0.33 3 43 F 3.01 2.31 9.97 9.52 0.30 0.24 4 39 M 2.11 2.72 7.94 7.60 0.27 0.24 5 37 F 2.47 2.34 9.98 9.89 0.25 0.24 6 36 F 1.91 1.76 8.28 8.19 0.23 0.22 7 35 M 1.76 2.36 7.93 8.36 0.22 0.28 8 32 F 1.88 1.51 9.56 9.56 0.2 0.16 9 32 M 1.94 2.14 7.04 7.79 0.28 0.28 10 30 F 1.82 2.52 7.8 8.63 0.23 0.29 11 28 M 1.72 2.23 7.16 8.51 0.24 0.26 Mean 37.00 2.21 2.35 8.40 8.70 0.27 0.26 Valproate Treated Patients 1 58 F 2.72 2.1 9.16 10.13 0.30 0.21 2 50 M 2.61 3.42 8.17 10.53 0.32 0.33 3 49 F 2.03 1.79 8.56 7.48 0.24 0.24 4 48 F 2.44 1.88 9.93 8.19 0.25 0.23 5 36 M 2.60 2.53 7.84 7.51 0.33 0.34 6 35 F 2.07 2.77 9.26 10.39 0.22 0.27 7 35 F 2.78 1.89 8.35 9.79 0.33 0.19 8 34 F 1.76 2.93 7.26 8.01 0.24 0.37 9 34 F 2.43 2.27 7.75 7.23 0.31 0.31 Mean 42.11 2.38 2.40 8.48 8.81 0.28 0.28 The Cho/Cr ratios in the frontal lobes were 0.27 ± 0.028 in controls and 0.28 ± 0.015 in patients. In the temporal lobes the Cho/Cr ratios were 0.26 ± 0.021 in controls and 0.28 ± 0.016 in patients. There were no statistically significant differences between the controls and patients in either the frontal (t = 0.367, df = 18, p = 0.72) or temporal (t = 0.539, df = 18, p = 0.59) lobes (Table 1). Discussion The results from the present study vary considerably between the two sections utilizing differing methodologies. This is despite the fact that both studies were carried out by the same group on the same scanner with bipolar patients coming from the same patient pool. This strongly suggests that the methodology used to determine choline concentrations can considerably alter the results. In the first part of the study we found that both the lithium-treated and valproate-treated patients had significantly reduced Cho/Cr peak ratios compared to controls. This is similar to the findings from one previous study which also suggested that there may be a trend towards decreased choline in grey matter [28]. This study was a frontal lobe study that measured metabolite concentrations in a 1.5 T scanner in bipolar type I patients hospitalized for manic (n = 9) or mixed (n = 8) states. In this study most patients were being treated with valproate and an atypical antipsychotic. These findings, however, differ from those in the second part of the present study in which we found no differences in choline concentrations between valproate-treated patients and controls in either frontal or temporal lobes. This second part of the study was much better controlled in terms of the patients receiving valproate monotherapy, only including bipolar Type I patients, and in using an external choline solution to accurately quantify choline concentrations. This finding of a lack of change is also in keeping with most previous studies. Several studies which have also previously measured metabolite concentrations with 1.5 T scanners also found no changes. These include a study of the hippocampus in 15 euthymic bipolar type 1 patients, of whom 10 were taking either lithium or valproate [19], a study of basal ganglia in 8 rapid cycling patients on lithium [22], a study of the anterior cingulate in 10 bipolar children [23], and a study in frontal lobes of 23 euthymic bipolar patients of whom 13 were on lithium [25]. Several other studies have examined metabolite ratios, mostly in patients on lithium, and those also found no changes in choline concentrations [20,21,26,27]. In a study using metabolite ratios in bipolar children who were off medication for at least one week there was also no change in choline concentrations [24]. In a double-blind placebo-controlled human volunteer study before and after one week of lithium administration we also found no changes in cholinein 10 volunteers [30], which is similar to a patient study which compared 7 patients on lithium to 6 non-lithium treated controls and in which no differences were seen [29]. In contrast, animal studies have suggested that lithium may increase brain choline concentrations, and in lithium-treated patients it also increases the accumulation of choline within erythrocytes [4-7]. Nonetheless, 1H-MRS studies in patients examining this possibility is mixed. To date 6 studies have suggested some support for this [13-18], but in none of these studies were metabolite concentrations measured, and most of the studies measured choline/creatine ratios [14-18], the other one measuring metabolite intensity/tissue volume [13]. The first study to examine brain choline in basal ganglia studied only 4 patients, all of whom were on lithium [18]. Another study examined 19 euthymic inpatients and found increased choline/creatine ratios in basal ganglia, but only 10 of these patients were receiving lithium [17]. The third study to report an increase in this ratio (in this case in the left subcortical region) was in a mixed group of patients receiving a wide range of medications [16]. Two other studies have reported increased choline concentrations, but only in limited circumstances. In one study in 11 bipolar children patients were examined before and after lithium administration [14]. There were no significant findings before or after lithium administration, although there was a trend towards increased choline/creatine ratios in the patients before lithium treatment. This latter finding does not suggest that in patients lithium significantly alters the choline/creatine ratio. The final study examined 15 euthymic males who were on either lithium or valproate [13]. This study found that thalamic choline concentrations, determined by measuring metabolite intensity/tissue volume ratios, were significantly increased only if the right and left hemisphere were compared separately, but not if they were compared together. It is also conceivable that both lithium and valproate may increase Choline concentrations, but that the differences were not large enough for us to detect, or that without lithium or valproate treatment patients would have lower Choline concentrations. The cross-sectional nature of this study does not allow this to be examined. It is also important to recognize other limitations of the present study. Firstly, these MRS studies are not pre- and post-treatments, so may not accurately reflect changes that occur in individual patients. Secondly, part of the study used a ratio-method to assess choline concentrations, the limitations of which are increasingly clear (particularly since creatine concentrations may be altered by medication [37]). Thirdly, the sizes of all groups are small and it therefore possible that a larger study may have been fully powered to identify differences between groups. Fourthly, several patients in the first study (but not the second study) were on other drugs which may have affected the results of this study. Fifthly, we have not determined if age affects the results, and in the first part the groups were not all matched for age. In addition, the voxel locations were not the same in both studies due to the reasons discussed in the methodology section. Nonetheless, despite these limitations we believe the results add significantly to the literature in this under-researched area. We conclude that, taking all current evidence together including the findings from the present study, it is unlikely that either lithium or valproate significantly alter brain choline concentrations. However, given the large differences in patients populations, medications received, and MRS methodologies it is difficult to directly compare all these studies. In addition, the methodology used to measure choline concentrations can significantly alter the results. Future MRS studies in bipolar patients should, therefore, examine metabolite concentrations rather than a ratio of choline compared to other metabolites. Competing interests None declared. Acknowledgements This work was supported in part by peer-reviewed grants from the Canadian Institutes of Health Research (CIHR) and the Alberta Heritage Foundation for Medical Research (AHFMR). ==== Refs Vestergaard P Licht RW 50 Years with lithium treatment in affective disorders: present problems and priorities World J Biol Psychiatry 2001 2 18 26 12587181 Lingsch C Martin K An irreversible effect of lithium administration to patients Br J Pharmacol 1976 57 323 7 974314 Uney JB Marchbanks RM Reynolds GP Perry RH Lithium prophylaxis inhibits choline transport in post-mortem brain Lancet 1986 2 458 2874439 10.1016/S0140-6736(86)92162-8 Jope RS Jenden DJ Ehrlich BE Diamond JM Choline accumulates in erythrocytes during lithium therapy N Engl J Med 1978 299 833 834 692570 Brinkman SD Pomara N Barnett N Block R Domino EF Gershon S Lithium-induced increases in red blood cell choline and memory performance in Alzheimer-type dementia Biol Psychiatry 1984 19 157 64 6424733 Domino EF Sharp RR Lipper S Ballast CL Delidow B Bronzo MR NMR chemistry analysis of red blood cell constituents in normal subjects and lithium-treated psychiatric patients Biol Psychiatry 1985 20 1277 1283 4063417 10.1016/0006-3223(85)90112-X Stoll AL Cohen BM Hanin I Erythrocyte choline concentrations in psychiatric disorders Biol Psychiatry 1991 29 309 321 2036475 10.1016/0006-3223(91)90216-9 Sartorius A Neumann-Haefelin C Bollmayr B Hoehn M Henn FA Choline rise in the rat hippocampus induced by electroconvulsive shock treatment Biol Psychiat 2003 53 620 623 12679241 10.1016/S0006-3223(02)01600-1 Leiva DB The neurochemistry of mania: a hypothesis of etiology and rationale for treatment Prog Neuropsychopharmacol Biol Psychiatry 1990 14 423 9 2193316 10.1016/0278-5846(90)90030-K Stoll AL Sachs GS Cohen BM Lafer B Christensen JD Renshaw PF Choline in the treatment of rapid-cycling bipolar disorder: clinical and neurochemical findings in lithium-treated patients Biol Psychiat 1996 40 382 8 8874839 10.1016/0006-3223(95)00423-8 Stoll AL Renshaw PF De Micheli E Wurtman R Pillay SS Cohen BM Choline ingestion increases the resonance of choline-containing compounds in human brain: an in vivo proton magnetic resonance study Biol Psychiat 1995 37 170 4 7727625 10.1016/0006-3223(94)00120-R Cohen BM Renshaw PF Stoll AL Wurtman RJ Yurgelun-Todd D Babb SM Decreased brain choline uptake in older adults. An in vivo proton magnetic resonance spectroscopy study JAMA 1995 274 902 7 7674505 10.1001/jama.274.11.902 Deicken RF Eliaz Y Feiwell R Schuff N Increased thalamic N -acetylaspartate in male patients with familial bipolar I disorder Psychiatry Res 2001 106 35 45 11231098 10.1016/S0925-4927(00)00083-4 Davanzo P Thomas MA Yue K Oshiro T Belin T Strober M McCracken J Decreased anterior cingulated myo-inositol/creatine spectroscopy resonance with lithium treatment in children with bipolar disorder Neuropsychopharmacology 2001 24 359 369 11182531 10.1016/S0893-133X(00)00207-4 Moore CM Breeze JL Gruber SA Babb SM deB Frederick B Villafuerte RA Stoll AL Hennen J Yurgelun-Todd DA Cohen BM Renshaw PF Choline, myo-inositol and mood in bipolar disorder: a proton magnetic resonance spectroscopic imaging study of the anterior cingulate cortex Bipolar Disord 2000 2 207 216 11249799 10.1034/j.1399-5618.2000.20302.x Hamakawa H Kato T Murashita J Kato N Quantitative proton magnetic resonance spectroscopy of the basal ganglia in patients with affective disorders Eur Arch Psychiatry Clin Neurosci 1998 248 53 58 9561353 10.1007/s004060050017 Kato T Hamakawa H Shioiri T Murashita J Takahashi Y Takahashi S Inubushi T Choline-containing compounds detected by proton magnetic resonance spectroscopy in the basal ganglia in bipolar disorder J Psychiatry Neurosci 1996 21 248 254 8754593 Sharma R Venkatasubramanian PN Barany M Davis JM Proton magnetic resonance spectroscopy of the brain in schizophrenic and affective patients Schizophr Res 1992 8 43 49 1329928 10.1016/0920-9964(92)90059-E Deicken RF Pegues MP Anzalone S Feiwell R Soher B Lower concentration of hippocampal N-acetylaspartate in familial bipolar I disorder Am J Psychiat 2003 160 873 882 12727690 10.1176/appi.ajp.160.5.873 Bertolino A Frye M Callicott JH Mattay VS Rakow R Shelton-Repella J Post R Weinberger DR Neuronal pathology in the hippocampal area of patients with bipolar disorder: a study with proton magnetic resonance spectroscopic imaging Biol Psychiat 2003 53 906 913 12742678 10.1016/S0006-3223(02)01911-X Chang K Adleman N Dienes K Barnea-Goraly N Reiss A Ketter T Decreased N-acetylaspartate in children with familial bipolar disorder Biol Psychiat 2003 53 1059 1065 12788251 10.1016/S0006-3223(02)01744-4 Lyoo IK Demopulos CM Hirashima F Ahn KW Renshaw PF Oral choline decreases brain purine levels in lithium-treated subjects with rapid-cycling bipolar disorder: a double-blind trial using proton and lithium magnetic resonance spectroscopy Bipolar Disord 2003 5 300 306 12895208 10.1034/j.1399-5618.2003.00041.x Davanzo P Yue K Thomas MA Belin T Mintz J Venkatraman TN Santoro E Barnett S McCracken J Proton magnetic spectroscopy of bipolar disorder versus intermittent explosive disorder in children and adolescents Am J Psychiatry 2003 160 Castillo M Kwock L Courvoisie H Hooper SR Proton MR spectroscopy in children with bipolar affective disorder: preliminary observations Am J Neuroradiol 2000 21 832 838 10815657 Hamakawa H Kato T Shioiri T Inubushi T Kato N Quantitative proton magnetic resonance spectroscopy of the bilateral frontal lobes in patients with bipolar disorder Psychological Med 1999 29 639 644 10.1017/S0033291799008442 Ohara K Isoda H Suzuki Y Takehara Y Ochiai M Takeda H Igarashi Y Ohara K Proton magnetic resonance spectroscopy of the lenticular nuclei in bipolar I affective disorder Psych Res Neuroimag Sect 1998 84 55 60 10.1016/S0925-4927(98)00050-X Bruhn H Stoppe G Staedt J Merboldt KD Hänicke W Frahm J Quantitative proton MRS in vivo shows cerebral myo -inositol and cholines to be unchanged in manic-depressive patients treated with lithium [abstract] Proc Soc Mag Res Med 1993 1543 Cecil KM DelBello MP Morey R Strakowski SM Frontal lobe differences in bipolar disorder as determined by proton MR spectroscopy Bipolar Dis 2002 4 357 365 10.1034/j.1399-5618.2002.02235.x Stoll AL Renshaw PF Sachs GS Guimaraes AR Miller C Cohen BM Lafer B Gonzalez RG The human brain resonance of choline-containing compounds is similar in patients receiving lithium treatment and controls: an in vivo proton magnetic resonance spectroscopy study Biol Psychiatry 1992 32 944 949 1467379 10.1016/0006-3223(92)90184-2 Silverstone PH Hanstock CC Rotzinger S Lithium does not alter the choline/creatine ratio in the temporal lobe of human volunteers as measured by proton magnetic resonance spectroscopy J Psychiatry Neurosci 1999 24 222 226 10354656 Stoll AL Renshaw PF Yurgelun-Todd DA Cohen BM Neuroimaging in bipolar disorder: what have we learned? Biol Psychiatry 2000 48 505 517 11018223 10.1016/S0006-3223(00)00982-3 Strakowski SM DelBello MP Adler C Cecil KM Saz KW Neuroimaging in bipolar disorder Bipolar Disord 2000 2 148 164 11256682 10.1034/j.1399-5618.2000.020302.x Pies R Combining lithium and anticonvulsants in bipolar disorder: a review Ann Clin Psychiatry 2002 14 223 232 12630658 10.1023/A:1021969001231 Sher PK Neale EA Graubard BI Habig WH Fitzgerald SC Nelson PG Differential neurochemical effects of chronic exposure of cerebral cortical cell culture to valproic acid, diazepam, or ethosuximide Pediatr Neurol 1985 1 232 7 3939744 Moore CM Breeze JL Gruber SA Babb SM deB Frederick B Villafuerte RA Stoll AL Hennen J Yurgelun-Todd DA Cohen BM Renshaw PF Choline, myo-inositol and mood in bipolar disorder: a proton magnetic resonance spectroscopic imaging study of the anterior cingulate cortex Bipolar Disord 2000 2 207 216 11249799 10.1034/j.1399-5618.2000.20302.x Simister RJ McLean MA Barker GJ Duncan JS Proton MRS reveals frontal lobe metabolite abnormalities in idiopathic generalized epilepsy Neurology 2003 61 897 902 14557556 O'Donnell T Rotzinger S Nakashima TT Hanstock CC Ulrich M Silverstone PH Chronic lithium and sodium valproate both decrease the concentration of myo-inositol and increase the concentration of inositol monophosphates in rat brain Brain Research 2000 880 84 91 11032992 10.1016/S0006-8993(00)02797-9 Silverstone PH Asghar SJ O'Donnell T Ulrich M Hanstock CC Lithium protects against dextro-amphetamine induced brain choline concentration changes in bipolar disorder patients World J Biol Psychiat 2004 5 35 41 Gordon RE Ordidge RJ Volume selection for high resolution NMR studies [abstract] Proc Soc Magn Reson Med 1984 272 Bottomley PA Spatial localization in NMR spectroscopy in vivo Ann NY Acad Sci 1987 508 333 348 3326459 Talairach J Tournoux P Co-planar stereotaxic atlas of the human brain New York: Thieme Medical 1988 51 110 Huang W Alexander GE Daly EM Shetty HU Krasuski JS Rapoport SI Schapiro MB High brain myo -inositol levels in the predementia phase of Alzheimer's disease in adults with Down's syndrome: a 1H MRS study Am J Psychiatry 1999 156 1879 1886 10588400 Vermathen P Capizzano AA Maudsley AA Administration and (1)H MRS detection of histidine in human brain: application to in vivo pH measurement Magn Reson Med 2000 43 665 675 10800031 10.1002/(SICI)1522-2594(200005)43:5<665::AID-MRM8>3.3.CO;2-V

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2021-01-04 16:05:46

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Microb Cell Fact. 2004 Aug 2; 3:10

latin-1

Microb Cell Fact

10.1186/1475-2859-3-10

oa_comm

==== Front Health Qual Life OutcomesHealth and Quality of Life Outcomes1477-7525BioMed Central London 1477-7525-2-381527967610.1186/1477-7525-2-38ResearchSimilar group mean scores, but large individual variations, in patient-relevant outcomes over 2 years in meniscectomized subjects with and without radiographic knee osteoarthritis Paradowski Przemyslaw T 12przemek.paradowski@ort.lu.seEnglund Martin 1martin.englund@ort.lu.seRoos Ewa M 1ewa.roos@ort.lu.seStefan Lohmander L 1stefan.lohmander@ort.lu.se1 Department of Orthopedics, Lund University Hospital, SE-221 85 Lund, Sweden2 Department of Orthopedics, Medical University Hospital, Zeromskiego 113, 90-549 Lodz, Poland2004 27 7 2004 2 38 38 7 5 2004 27 7 2004 Copyright © 2004 Paradowski et al; licensee BioMed Central Ltd.2004Paradowski et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background Epidemiological studies have, so far, identified factors associated with increased risk for incident or progressive OA, such as age, sex, heredity, obesity, and joint injury. There is, however, a paucity of long-term data that provide information on the nature of disease progression on either group or individual levels. Such information is needed for identification of study cohorts and planning of clinical trials. The aim of the study was, thus, to assess the variation in pain and function on group and individual level over 2 years in previously meniscectomized individuals with and without radiographic knee osteoarthritis (OA). Methods 143 individuals (16% women, mean age at first assessment 50 years [range 27–83]) were assessed twice; approximately 14 and 16 years after isolated meniscectomy, with a median interval of 2.3 years (range 2.3–3.0). Radiographic OA (as assessed at the time of second evaluation) was present in the operated knee in 40%, and an additional 19% had a single osteophyte grade 1 in one or both of the tibiofemoral compartments. Subjects completed the self-administered and disease-specific Knee injury and Osteoarthritis Outcome Score (KOOS). Results There were no significant changes in the group mean KOOS subscale scores over the 2-year period. However, a great variability over time was seen within individual subjects. Out of 143 subjects, 16% improved and 12% deteriorated in the subscale Pain, and 13% improved and 14% deteriorated in the subscale ADL ≥ 10 points (the suggested threshold for minimal perceptible clinical change). Similar results were seen for remaining subscales. Conclusion Group mean scores for this study cohort enriched in incipient and early-stage knee OA were similar over 2 years, but pain, function and quality of life changed considerably in individuals. These results may be valid also for other at risk groups with knee OA, and motivate further careful examination of the natural history of OA, as well as properties of the OA outcome instruments used. Longitudinal outcome data in OA studies need to be analyzed both on an individual and a group level. osteoarthritiskneemeniscusfollow-uppatient-relevant outcome ==== Body Background Drugs that may slow or halt the breakdown of cartilage and other joint tissues in osteoarthritis (OA) and possibly improve symptoms and function are now being developed in the pharmaceutical industry. The potential availability of disease modifying OA drugs has focused attention on our relative lack of information on the 'natural disease history' of OA with regard to changes in symptoms, functional limitations, joint structure and other markers of disease change [1]. Epidemiological studies have identified factors associated with increased risk for incident or progressive OA, such as age, sex, heredity, obesity, and joint injury, pain, alignment, or laxity. There is, however, a paucity of long-term data that document the rate and nature of natural OA disease progression on either group or individual levels. Such information is needed for identification of study cohorts and planning of clinical trials of disease modifying OA drugs. Even more importantly, knowledge of natural disease progression in different patient groups will be needed to select those future groups that may benefit from such drugs. Only a few of the previously published studies have presented information on longitudinal variation in pain and function in the natural history of knee OA. The "Bristol 500 OA study" noted, that although pain changed little on a group level over a 3-year follow-up period, it varied greatly in individuals, with some subjects reporting marked improvements. Similarly, a minority improved functionally [2-4]. Yet another report suggested that most patients with OA attending rheumatology clinics do not deteriorate radiographically or symptomatically over an 11-year period [5]. A more recent report stated that 42–44% of community-recruited knee OA individuals did not change in physical functioning over a 3-year study [6]. Most investigations of the natural history of OA have been concerned with radiographic rather than clinical changes. For example, it was reported that the radiographic Kellgren and Lawrence classification score of 1 could represent incipient OA and be predictive of later development of more advanced radiographic features of OA [7]. MRI may be more responsive to change in early-stage OA than plain radiography [8]. However, outcome is usually heterogeneous: study subjects may report improvement or deterioration while they do not change radiographically over the time period assessed. It may also be that a few individuals alone generate much of any change detected at group level [9-11]. A further confounding factor in the longitudinal assessment of OA is the potential influence of the population from which the study group was recruited; a study group recruited from e.g. a specialist outpatient clinic is likely to have, on the average, more severe disease and may be at different risk to progress over time than a study group recruited from the community. The objective of this investigation was to assess both group and individual variation in knee pain, function and quality of life over two years in a study group enriched in incipient and early-stage radiographic knee OA. Methods Patients Approval was obtained from the Research Ethics Committee of the Medical Faculty of Lund University, Sweden. All patients who underwent meniscectomy between 1983 and 1985 were identified by searching the surgical records at the Department of Orthopedics, Lund University Hospital. In this period 552 meniscectomies were performed. Inclusion and exclusion criteria (Figure 1) were used to identify 264 former patients who, in 1998, were sent a self-administered questionnaire evaluating their knee-specific symptoms and knee function. Figure 1 Flow chart presenting the inclusion and exclusion criteria for patients. ACL = anterior cruciate ligament, PCL = posterior cruciate ligament, OA = osteoarthritis. Out of 211 individuals (80%) who returned the questionnaires, 6 were excluded because they matched one of the exclusion criteria. At 2 years after the first assessment 5 subjects had died, but the remaining 200 individuals were asked to provide a second evaluation using an identical questionnaire. Replies were received from 143 (72%). Of these 143 participants, 102 were meniscectomized by open surgery, and 41 by arthroscopy. Nineteen underwent an additional meniscus operation in the index knee. All re-operations were performed within 3 years after the original meniscectomy. Twenty-three participants were treated with subsequent meniscectomy of the contralateral knee. One of them underwent high tibial osteotomy and 1, because of OA, received a knee prosthesis in the contralateral knee. Data concerning subsequent surgeries were based on the medical records of Lund University Hospital and on self-reported information. Radiographic assessment At the time of the participants' second evaluation with questionnaires, standing anteroposterior (AP) radiographs of both knees were taken in 15 degrees of flexion using a CGR Phasix 60 generator at 70 kV, 16 mA, film-focus distance 1.5 m (CGR, Liège, Belgium). Ten out of the 143 participants (7%) declined the radiographic examination. All AP radiographs of the tibiofemoral joints from the follow-up were assessed for joint space narrowing (JSN) and osteophytes according to the atlas from Osteoarthritis Research Society International (OARSI) [12]. The presence of these features was graded on a 4-point scale (range 0–3, with 0 = no evidence of bony changes or JSN). We considered radiographic knee OA to be present if any of the following criteria was achieved in any of the 2 tibiofemoral compartments: JSN ≥ grade 2 or the sum of the 2 marginal osteophyte grades from the same compartment ≥ 2, or JSN grade 1 in combination with an osteophyte grade 1 in the same compartment [13,14]. This cut-off approximates grade 2 knee OA or worse based on the Kellgren and Lawrence scale [15]. Disease-specific questionnaire The Knee injury and Osteoarthritis Outcome Score (KOOS, Swedish version LK 1.0) is a 42-item self-administered knee-specific questionnaire based on the WOMAC Osteoarthritis Index [16,17]. KOOS was developed to be used for short- and long-term follow-up studies of knee injuries, and it comprises 5 subscales: Pain, Symptoms, Activities of Daily Living (ADL), Sports and Recreation Function (Sport/Rec) and knee-related Quality of Life (QOL). A separate score ranging from 0 to100, where 100 represents the best result, is calculated for each subscale. The questionnaire and scoring manual can be downloaded from . The KOOS is valid, reliable and responsive in follow-up of meniscectomy [17], anterior cruciate ligament reconstruction [18] and total knee replacement for OA [19]. The participants completed the KOOS questionnaire answering questions on their operated index knee. Change The minimal perceptible clinical improvement (MPCI) represents the difference on the measurement scale associated with the smallest change in the health status detectable by the individual. Since the KOOS questionnaire contains the full and original version of the WOMAC LK 3.0 index, we used the MPCI as described for WOMAC [20]. Thus, a level of 10 points or more of improvement or decline was operationally used as a cut-off representing a clinically perceptible difference. The sensitivity of the questionnaire has been established [21]. Data collection and statistics If questions were left unanswered in any part of the questionnaire, we returned the questionnaire to be completed. The questionnaires were then completed fully. The Mann-Whitney U-test was used to determine differences between the groups. P-values for categoric data were calculated with Fisher's exact test. All tests were 2-tailed and a P-value of ≤ 0.05 was considered statistically significant (SigmaStat, version 2.0, for Windows). Results Group level The study group comprised 143 individuals, of whom 23 (16%) were women. The participants' mean age at the first follow-up was 51 (range 27–83) years. The assessment was carried out twice: at approximately 14 and 16 years after the surgery, with a median interval of 2.3 (range 2.3 to 3.0) years. Fifty-three (40%) of the 133 individuals who had undergone radiographic examination had radiographic tibiofemoral OA in their index (operated) knee (21% women, age range 29–83, mean 53) and 80 were classified as non having OA (11% women, age range 27–82, mean 50). An additional 25 (19%) (not classified as radiographic OA) had a single osteophyte grade 1 in either one or both tibiofemoral compartments. Mean scores for the KOOS subscales at the first assessment did not change significantly over the 2-year study period (Table 1). Moreover, there were no significant changes in group mean subscale scores over 2 years when participants were divided into those with or without radiographic OA in the index knee (Table 1, Figure 2). However, individuals with radiographic OA scored worse at both examinations than did those without radiographic OA. The differences between those with and without OA were statistically significant for KOOS Pain Δ = 11 points (P = 0.004), other Symptoms Δ = 9 points (P = 0.013), ADL Δ = 10 points (P = 0.003), Sport/Rec Δ = 17 points (P = 0.005), and QOL Δ = 16 points (P = 0.003) assessed in 2000, and in the dimensions Sport/Rec Δ = 14 points (P = 0.020) and QOL Δ = 12 points (P = 0.041) evaluated in 1998. Table 1 KOOS scores overall and in patients without and with radiological signs of OA KOOS subscales Patients p-values Total group non-ROA ROA non-ROA vs. ROA n = 143 n = 80 n = 53 1998 2000 1998 2000 1998 2000 2000 pain mean 85 84 88 87 79 76 0.008 median 94 94 94 94 86 83 SD 20 21 16 18 24 25 range 19–100 25–100 39–100 25–100 19–100 25–100 symptoms mean 85 84 87 87 80 78 0.013 median 93 89 93 93 89 82 SD 19 18 17 16 23 21 range 14–100 14–100 25–100 18–100 14–100 14–100 ADL mean 88 88 90 91 83 81 0.004 median 99 97 99 99 94 90 SD 18 18 15 15 23 21 range 18–100 31–100 44–100 34–100 18–100 31–100 sports/rec mean 69 68 74 76 60 57 0.007 median 80 80 80 85 60 60 SD 31 32 28 28 34 34 range 0–100 0–100 0–100 0–100 0–100 0–100 QOL mean 75 73 78 78 67 63 0.005 median 81 81 81 84 69 63 SD 26 27 23 23 30 30 range 0–100 6–100 25–100 6–100 0–100 13–100 Mean, median, standard deviation and range of KOOS scores overall and in patients without and with radiological signs of OA. Note that 10 patients out of 143 did not undergo radiographic examination. P-values for comparison between KOOS subscale results in patients with and without OA in year 2000 are presented. Figure 2 Group mean KOOS scores for patients assessed in 1998 and 2000. Group mean KOOS scores for patients with (n = 53) and without (n = 80) radiographic osteoarthritis (ROA) assessed in 1998 and 2000. Possible score range 0 to 100, with 100 representing the best result. ADL – Activities of Daily Living, QOL – knee-related Quality of Life. Bars present ± 95% confidence intervals. The bars going upwards have wider caps. Note vertical axis break. We analyzed separately those subjects (N = 57) that did not participate in the second assessment. Their mean KOOS scores at the first examination did not differ significantly from the remainder of the study cohort, indicating little or no inclusion bias for the second follow-up (data not shown). The scores in the 5 patients that underwent additional surgery (e.g. osteotomy, knee arthroplasty) did not differ significantly from the rest of the group. Individual study subject changes In spite of the lack of change on a group level, we found substantial intra-individual variability in the questionnaire subscale scores measured 2 years apart. Out of the total 143 study subjects, 40 had either improved or deteriorated (n = 23 (16%) and n = 17 (12%), respectively) 10 points or more for the KOOS subscale Pain. Of the 23 subjects who had improved in their pain score by these criteria, 14 had also improved in the subscale Symptoms, 17 in ADL, 16 in Sports/Rec, and 17 in QOL. Only 1 of these subjects deteriorated in Symptoms, and 2 in Sports/Rec, none in the other subscales. Of the 17 subjects who deteriorated in Pain, 13 similarly deteriorated in Symptoms, 12 in ADL, 10 in Sports/Rec, and 10 in QOL. When evaluating those who had undergone radiographic examination, there were no significant differences in variability detected whether the subject had radiographic tibiofemoral OA or not (P = 0.24, Table 2). Table 2 The percentage of patients improving, not changing, or deteriorating for KOOS subscales over time non-ROA ROA KOOS subscales cut-off n = 80 n = 53 + no change -- + no change -- % % pain 10 13 76 11 21 66 13 20 6 88 6 8 87 6 symptoms 10 16 69 15 26 55 19 20 6 86 8 13 77 9 ADL 10 9 79 13 19 64 17 20 5 86 9 15 79 6 sports/rec 10 19 60 21 28 42 30 20 11 76 13 21 64 15 QOL 10 20 56 24 26 57 17 20 5 88 8 15 75 9 The percentage of patients, with and without radiographic osteoarthritis (ROA), improving, not changing, or deteriorating for KOOS subscales over the 2 year study period. For definition of ROA see methods. Two cut-offs for change (≥ 10 and ≥ 20 points) are presented. We also evaluated a stricter cut-off of 20 points or more as used for the OARSI responder criteria, as opposed to minimal clinically perceptible change [22]. With this cut-off, in total 19 patients fulfilled the criterion for improvement or deterioration (n = 9 (6%), n = 10 (7%), respectively) in KOOS Pain. Among the subjects with radiographic OA, 3 (6%) improved and 4 (7%) deteriorated by 20 points or more. Corresponding numbers for those without radiographic OA were 5 (6%) for both improvement and deterioration. In order to explore these changes in more detail, the subjects were divided into quartiles, according to KOOS Pain score at the first assessment (Figure 3). The most noticeable changes were found in the quartile representing the worst scores: 21 of 36 (58%) subjects showed a change of 10 points or more in either direction. A corresponding change was seen in 11 (31%) individuals from the second worst quartile and in only 9 (25%) from the second best and best quartiles (6 and 3 subjects, respectively). Comparable results were seen for the other subscales of KOOS (data not shown). Figure 3 KOOS Pain subscale. Patients are divided into 4 subgroups (quartiles) according to the score at entry. Each line represents one patient visualizing the score in 1998 (left endpoint of line) and in 2000 (right endpoint of the same line). Discussion We found no significant change over 2 years in the average patient-relevant outcome scores for this study group of individuals who had undergone meniscectomy about 15 years earlier, even though the group was highly enriched in early-stage and incipient radiographic knee OA. However, we found substantial change in the self-report for individual subjects over the same time period. The generally worse KOOS scores for the individuals with radiographic knee OA, compared to those without, are consistent with earlier reports. Thus, the Baltimore Longitudinal Study of Aging reported that patients with a Kellgren-Lawrence score of 1 were almost twice as likely to report ever having knee joint pain compared with those who had a score of zero. The strength of the association increased with increasing Kellgren and Lawrence score [23]. Similarly, there was in meniscectomized individuals evidence for a graded increase in pain and functional limitations with increasing severity of radiographic signs of OA [24]. However, a discrepancy between knee pain and radiographic features of knee OA has also been noted, both cross-sectionally and longitudinally [3,24,25]. Depression and lack of muscle strength have been shown to better explain pain than radiographic findings [26-28]. Individual vs. group analysis Few reports have explored OA symptom variation on an individual level [2-4]. A detailed comparison of our results with earlier reports is difficult, since they were conducted before validated and patient-relevant OA disease-specific measurement tools had been widely introduced. The "Bristol OA 500" were patients with advanced radiographic knee OA and a mean age of 65 years recruited from a hospital based rheumatology clinic. In contrast, the mean age of the present study cohort was 50 years, with 2/5 having mild-moderate radiographic OA, and another 1/5 incipient radiographic changes. Further, the cohort reported on here was recruited from a group of individuals that had undergone isolated meniscectomy 15 years earlier, but independent of their subsequent symptom level or disease history. The mean scores of our study group were relatively good and not representative of subjects with advanced OA seeking medical care. The rationale for investigating this particular cohort at this time after surgery was its enrichment in early-stage knee OA, and that it consequently may represent a study group suitable for future pharmacological disease-modifying intervention. We assessed our patients at an interval of 2 years; this period of time being suggested as a minimum for clinical trials of disease modification in OA to detect both structural and symptom change [29]. It could be that the findings reported here are valid only for post-injury, secondary OA, or for this particular cohort. However, the criteria and delimitations for posttraumatic OA compared to primary OA have recently been shown to be much less clear than thought [13,14,30], and meniscal pathology is common also in primary, garden-variety, knee OA [31]. Tibiofemoral OA was observed in 53 out of 133 patients who were underwent radiographic examination. Isolated patellofemoral OA was rare and, since it did not affect the final results, was not taken into account. A further argument favoring the general applicability of the present results is the concordance of our findings with other longitudinal studies on OA [2-5,32]. Methodological issues We applied the criteria for minimal perceptible clinical improvement (MPCI) obtained for the WOMAC; since KOOS contains the WOMAC items and is similar in format. The KOOS subscale ADL is equivalent to the WOMAC subscale Function, while new items have been added to the KOOS subscales Pain and Symptoms. The dimensions assessed by the KOOS subscales Sport and Recreation Function and knee-related Quality of Life are not assessed by the WOMAC. The MPCI for the WOMAC is in the range of 8 to 12 points on a 0–100 scale [20]. This threshold coincides with the change observed in KOOS scores between 3 and 6 months postoperatively when assessing rehabilitation following reconstruction of the anterior cruciate ligament and concurs with the OARSI definition of moderate improvement in the knee pain assessment for clinical trials in OA [18,22]. However, the OARSI responder criteria were designed for the evaluation of the patient's response to oral NSAID and intra-articular treatment and may differ for other interventions. It may be argued that the subject-related changes observed in this study represent inherent instrument instability. However, validation studies of KOOS support the reproducibility and stability of the KOOS instrument [17-19]. Test-retest data on the KOOS subscale pain obtained from 75 patients about to undergo knee arthroscopy [17] was used to determine the number of subjects improving, deteriorating or not changing over an average period of 5 days. The proportion of subjects changing over 5 days was approximately half of that changing over 2 years in the present study, in further support that the variation in the present study cannot be explained solely by instrument noise (data not shown). A 'frame shift' in the priorities of the individual patient may occur during long term studies. However, we suggest that a significant frame shift is unlikely to have occurred over this 2 year study period of a cohort with a mean age of 50 years. Significant change of KOOS scores over time were noted in 1/3 of the cohort studied. About half of those who changed clinically improved. This was true in particular for patients with lower (worse) baseline scores. It is thus possible that the lower proportion of 'changers' among those with better baseline scores may have been, at least in part, due to a ceiling effect. Conclusions We conclude that despite unchanged group mean scores over 2 years, pain, function and quality of life change considerably over time in individuals, in this study cohort enriched in incipient and early-stage knee OA. These findings may be applicable also to other at risk patient groups in different phases of OA development, and motivate further careful examination of the natural history of OA, as well as properties of the OA outcome instrument used. We suggest that longitudinal OA study data should be analyzed both on the individual and group level. Our findings may have further relevance to clinical trials of OA that seek to document long term benefit in the form of symptom improvement and structural improvement. It is clear that much additional effort will need to be spent on selection of groups at high risk of progression of symptoms and structural joint change, and the identification of predictors for deterioration. Our results also suggest that the use of responder criteria may be an important aspect of analyzing the outcome of such trials [22,33]. Authors' contributions EMR and LSL planned study and collected the data. PTP performed the statistical analysis and drafted the manuscript. ME formed the database of patients and participated in the statistical analysis. ME, EMR, LSL corrected the manuscript. All authors read and approved the manuscript Acknowledgements This work was supported by grants from the Swedish Institute, the Swedish Rheumatism Association, The Swedish National Center for Research in Sports, The Swedish Research Council, The King Gustaf V 80-year Birthday Fund, Zoega Foundation for Medical Research, Kock Foundations and Lund University Medical Faculty and Region Skane. The authors are indebted to Robert Foltyn for excellent assistance in the preparation of this manuscript. ==== Refs National Institute of Arthritis and Musculoskeletal and Skin Diseases. Osteoarthritis Initiative Massardo L Watt I Cushnaghan J Dieppe PA Osteoarthritis of the knee joint: an eight year prospective study Ann Rheum Dis 1989 48 893 897 2596881 Dieppe PA Cushnaghan J Shepstone L The Bristol 'OA500' study: progression of osteoarthritis (OA) over 3 years and the relationship between clinical and radiographic changes at the knee joint Osteoarthritis and Cartilage 1997 5 87 97 9135820 Dieppe PA Cushnaghan J Tucker M Browning S Shepstone L The Bristol 'OA500 study': progression and impact of the disease after 8 years Osteoarthritis and Cartilage 2000 8 63 68 10772234 10.1053/joca.1999.0272 Spector TD Dacre JE Harris PA Huskisson EC Radiological progression of osteoarthritis: An 11 year follow up study of the knee Ann Rheum Dis 1992 51 1107 1110 1444622 Sharma L Cahue S Song J Hayes K Pai Y-C Dunlop D Physical functioning over three years in knee osteoarthritis. Role of psychosocial, local mechanical, and neuromuscular factors Arthritis and Rheumatism 2003 48 3359 3370 14673987 10.1002/art.11420 Lachance L Sowers MF Jamada D Hochberg M The natural history of emergent osteoarthritis of the knee in women Osteoarthritis and Cartilage 2002 10 849 854 12435329 10.1053/joca.2002.0840 Jones G Ding C Scott F Glisson M Cicuttini F Early radiographic osteoarthritis is associated with substantial changes in cartilage volume and tibial bone surface area in both males and females Osteoarthritis and Cartilage 2004 12 169 174 14723876 10.1016/j.joca.2003.08.010 Pavelka K Gatterova J Altman RD Radiographic progression of knee osteoarthritis in a Czech cohort Clin Exp Rheumatol 2000 18 473 477 10949722 Dougados M Nguyen M Berdah L Mazieres B Vignon E Lequesne M Evaluation of the structure-modifying effects of diacerein in hip osteoarthritis: ECHODIAH, a three-year, placebo-controlled trial. Evaluation of the Chondromodulating Effect of Diacerein in OA of the Hip Arthritis Rheum 2001 44 2539 2547 11710710 10.1002/1529-0131(200111)44:11<2539::AID-ART434>3.0.CO;2-T Raynauld JP Martel-Pelletier J Berthiaume MJ Labonte F Beaudoin G de Guise JA Bloch DA Choquette D Haraoui B Altman RD Hochberg MC Meyer JM Cline GA Pelletier JP Quantitative magnetic resonance imaging evaluation of knee osteoarthritis progression over two years and correlation with clinical symptoms and radiologic changes Arthritis Rheum 2004 50 476 487 14872490 10.1002/art.20000 Altman R Brandt K Hochberg M Moskowitz R Design and conduct of clinical trials in patients with osteoarthritis. Recommendations from a task force of the Osteoarthritis Research Society Osteoarthritis and Cartilage 1995 3 3 70 8581752 Englund M Roos EM Lohmander LS Impact of type of meniscal tear on radiographic and symptomatic knee osteoarthritis. A 16-year follow-up of meniscectomy with matched controls Arthritis and Rheumatism 2003 48 2178 2187 12905471 10.1002/art.11088 Englund M Paradowski PT Lohmander LS Association of radiographic hand osteoarthritis with radiographic knee osteoarthritis after meniscectomy Arthritis and Rheumatism 2004 50 469 475 14872489 10.1002/art.20035 Kellgren J Lawrence J Radiological assessment of osteoarthrosis Annals of the Rheumatic Diseases 1957 16 494 502 13498604 Bellamy N Buchanan W Goldsmith CH Validation study of WOMAC: A health status instrument for measuring clinically important patient-relevant outcomes following total hip or knee arthroplasty in osteoarthritis Orthop Rheumatol 1988 1 95 108 Roos EM Roos HP Ekdahl C Lohmander LS Knee injury and Osteoarthritis Outcome Score (KOOS) - validation of a Swedish version Scand J Med Sci Sports 1998 8 439 448 9863983 Roos EM Roos HP Lohmander LS Ekdahl C Beynnon BD Knee injury and Osteoarthritis Outcome Score (KOOS) - development of a self-administered outcome measure J Orthop Sports Phys Ther 1998 28 88 96 9699158 Roos EM Toksvig-Larsen S Knee injury and Osteoarthritis Outcome Score (KOOS) - validation and comparison to the WOMAC in total knee replacement Health Qual Life Outcomes 2003 1 17 12801417 10.1186/1477-7525-1-17 Ehrich EW Davies GM Watson DJ Bolognese JA Seidenberg BC Bellamy N Minimal perceptible clinical improvement with the Western Ontario and McMaster Universities osteoarthritis index questionnaire and global assessments in patients with osteoarthritis Journal of Rheumatology 2000 27 2635 2641 11093446 Roos EM Lohmander LS The Knee injury and Osteoarthritis Outcome Score (KOOS): from joint injury to osteoarthritis Health Qual Life Outcomes 2003 1 64 14613558 10.1186/1477-7525-1-64 Dougados M LeClaire P van der Heijde D Bloch DA Bellamy N Altman RD Response criteria for clinical trials on osteoarthritis of the knee and hip. A report of the Osteoarthritis Research Society International Standing Committee for Clinical Trials Response Criteria Initiative Osteoarthritis and Cartilage 2000 8 395 403 11069723 10.1053/joca.2000.0361 Lethbridge-Cejku M Scott W.S.jr. Reichle R Ettinger WH Zonderman A Costa P Plato CC Tobin JD Hochberg MC Association of radiographic features of osteoarthritis of the knee with knee pain: data from the Baltimore Longitudinal Study of Aging Arthritis Care Res 1995 8 182 188 7654803 Roos EM Östenberg A Roos HP Ekdahl C Lohmander LS Long-term outcome of meniscectomy: symptoms, function, and performance tests in patients with or without radiographic osteoarthritis compared to matched controls Osteoarthritis and Cartilage 2001 9 316 324 11399095 10.1053/joca.2000.0391 Hannan MT Felson DT Pincus T Analysis of the discordance between radiographic changes and knee pain in osteoarthritis of the knee Journal of Rheumatology 2000 27 1513 1517 10852280 McAlindon T Zhang Y Hannan MT Naimark A Weissman B Castelli W Felson D Are risk factors for patellofemoral and tibiofemoral knee osteoarthritis different? Journal of Rheumatology 1996 23 332 337 8882042 O'Reilly SC Jones A Muir KR Doherty M Quadriceps weakness in knee osteoarthritis: the effect on pain and disability Ann Rheum Dis 1998 57 588 594 9893569 O'Reilly SC Muir KR Doherty M Knee pain and disability in the Nottingham community: association with poor health status and psychological distress British Journal of Rheumatology 1998 37 870 873 9734678 10.1093/rheumatology/37.8.870 Altman R Brandt K Hochberg M Moskowitz R Bellamy N Bloch DA Buckwalter J Dougados M Ehrlich G Lequesne M Lohmander S Murphy W.A.jr. Rosario-Jansen T Schwartz B Trippel S Design and conduct of clinical trials in patients with osteoarthritis: Recommendations from a task force of the Osteoarthritis Research Society Osteoarthritis and Cartilage 1996 4 217 243 11048620 Englund M Roos EM Roos HP Lohmander LS Patient-relevant outcomes fourteen years after meniscectomy: Influence of type of meniscal tear and size of resection Rheumatology 2001 40 631 639 11426019 10.1093/rheumatology/40.6.631 Bhattacharyya T Gale D Dewire P Totterman S Gale E McLaughlin S The clinical importance of meniscal tears demonstrated by magnetic resonance imaging in osteoarthritis of the knee J Bone Joint Surg [Am] 2003 85-A 4 9 12533565 Leffondre K Abrahamovicz M Hawker GA Badley EM Regeasse A McCusker J Belzile E Longitudinal patterns of change in disability in osteoarthritis (abstract) Arthritis Rheum 2003 48 (suppl) S664 Pham T van der Heijde D Altman RD Anderson JJ Bellamy N Hochberg M Simon L Strand V Woodworth T Dougados M OMERACT-OARSI initiative: Osteoarthritis Research Society International set of responder criteria for osteoarthritis clinical trials revisited Osteoarthritis Cartilage 2004 12 389 399 15094138 10.1016/j.joca.2004.02.001

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==== Front Cell Commun SignalCell communication and signaling : CCS1478-811XBioMed Central London 1478-811X-2-81529650810.1186/1478-811X-2-8ReviewThe STATs in cell stress-type responses Dudley Andrew C 1drew@medstv.unimelb.edu.auThomas David 2David.Thomas@petermac.orgBest James 1jdbest@medicine.unimelb.edu.auJenkins Alicia 1jenkinsa@medstv.unimelb.edu.au1 The Department of Medicine, St. Vincent's Hospital, The University of Melbourne, Melbourne, Australia2 The Peter McCallum Cancer Center, Melbourne, Australia2004 6 8 2004 2 8 8 12 5 2004 6 8 2004 Copyright © 2004 Dudley et al; licensee BioMed Central Ltd.2004Dudley et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In the early 1990's, a new cell signaling pathway was described. This new paradigm, now known as the JAK/STAT pathway, has been extensively investigated in immune-type cells in response to interferons and interleukins. However, recent evidence suggests that the JAK/STAT pathway also mediates diverse cellular responses to various forms of biological stress including hypoxia/reperfusion, endotoxin, ultraviolet light, and hyperosmolarity. The current literature describing the JAK/STAT pathway's role in cellular stress responses has been reviewed herein, but it is clear that our knowledge in this area is far from complete. ==== Body Review In multicellular organisms, every cell comprising every tissue, organ, or organ system constantly strives to maintain homeostasis in the face of destabilizing influences. Whether it is external stimuli such as toxic chemical exposure or changes in oxygen tension, or natural alterations in pH or osmolarity due to normal cellular metabolism, each cell in the body is equipped with the molecular machinery required to sense these environmental changes and respond to them. Because these stressful stimuli can impinge on normal cellular functioning, discrete cellular sensing mechanisms have evolved to maintain homeostasis. For example, ATP depletion caused by hypoxia activates AMPK which phosphorylates multiple downstream targets to switch the cell from a mainly anabolic to catabolic state [1]. Similarly, activation of SAPK/JNK by stressors such as ultraviolet (UV) light results in activation of well-defined molecular targets [reviewed in [2]]. One interesting question is how do cells translate diverse stressful stimuli into activation of specific molecular pathways? Cellular signaling from membrane to nucleus is typically accomplished through ligand/receptor activation of intracellular second messengers. In many cases these second messengers are kinases which phosphorylate substrates leading to a cascade by which successive macromolecules are triggered. Ultimately, a terminal transcription factor is activated which then translocates to the nucleus to activate specific target genes. This type of cellular signaling has been well-characterized following receptor activation by polypeptide ligands, but some forms of cellular stress such as hypoxia cause activation of specific molecular pathways in the apparent absence of ligand to receptor stimulation. Therefore, there must be alternative routes for direct activation of target genes that circumvents the canonical ligand/receptor/second messenger cascade. One such pathway that may transmit signals to the nucleus by this alternative route is the Janus Activated Kinase/Signal Transducer and Activator of Transcription family of transcription factors (JAK/STAT). The JAK/STAT pathway includes seven functionally related, latent transcription factors (STAT) and four non-receptor tyrosine kinases (JAK) [reviewed in [3]]. In the typical JAK/STAT paradigm, a cytokine binding to its receptor results in activation of receptor-associated JAKs. JAKs then phosphorylate the cytoplasmic receptor chains creating docking sites for recruited STATs. Finally, STATs are phosphorylated on tyrosine by JAKs, dimerize, and then translocate to the nucleus to activate specific target genes. Because the second messenger (STAT) is also the terminal transcription factor, in many ways the JAK/STAT pathway represents a streamlined apparatus for cellular signaling. Thus, the JAK/STAT pathway differs from many signaling cascades in that the usual system of multiple sequential signaling molecules is bypassed. While signaling through the canonical JAK/STAT pathway has been well-characterized in immune-type cells in response to interleukins and interferons, there is emerging evidence that STATs also mediate cellular responses to various forms of cellular stress. These findings, in addition to mounting evidence suggesting that some STATs are phosphorylated on serine by members of the MAPK family, imply that alternative mechanisms for STAT activation exist. Further, these alternative means of activation may lead to different outcomes with regards to STAT signaling. For example, STAT3 was recently shown to be serine phosphorylated by JNK during UV stress which had a predominately inhibitory role on STAT3 transcriptional activity [4]. Could these alternative routes of STAT activation account for STAT's "yin and yang" type properties whereby depending on the type of cell stressor, either cell death or cell survival pathways are activated? Although interferons themselves can regulate cellular responses to exogenous stressors such as infection through the canonical JAK/STAT pathway, this literature review will focus mainly on those alternative mechanisms of JAK/STAT signaling during cellular stress. STATs and cellular stress Some of the earliest studies implicating STATs in mediating cell stress responses were performed in cells exposed to UV light. In mouse embryonic fibroblasts (MEFs), UV light treatment resulted in phosphorylation of serine 727 in STAT1 via p38 MAPK [5,6]. Further analysis revealed that STAT1 could be phosphorylated directly by p38 MAPK in vitro. Thus, the MAPK and STAT pathways appear to converge during periods of cellular stress. In another study, UV light caused STAT1 tyrosine phosphorylation, nuclear accumulation, and DNA binding in keratinocytes [7]. Together, these studies raise the possibility that STATs can be activated in a ligand-independent manner during cellular stress, resulting in the activation of STAT-dependent target genes. Cellular stress can also occur in disease states such as diabetes, which is characterized by vascular dysfunction. For example, prolonged elevated glucose can act as a cell stressor through multiple pathways including hyperosmolarity [8], protein kinase C (PKC) activation [9], and oxidative damage [10]. Recent studies have determined that constitutive JAK/STAT phosphorylation was elevated in cultured smooth muscle-like mesangial cells treated with high glucose [11]. Furthermore, in these same cells, angiotensin stimulation of STATs was prolonged by high glucose treatment [12,13]. The authors of these studies related these findings to TGFβ-induced extracellular matrix accumulation because collagen and fibronectin secretion could be inhibited with STAT anti-sense RNAs. This implies that the JAK/STAT pathway may play a role in basement membrane thickening observed in diabetic nephropathy and retinopathy. These studies were some of the first to suggest that perturbed JAK/STAT signaling could play a role in disease states like diabetes and possibly link glucose-mediated cell stress and the JAK/STAT pathway with diabetic sequelae. Hyperosmotic stress can also activate STATs. For example, in the slime mold Dictyostelium, hyperosmotic stress leads to STAT1 phosphorylation without any known involvement of JAK or MAPK [14]. But mammalian cells also utilize STATs during hyperosmotic stress. In one report, sorbitol-induced hyperosmolarity was shown to cause JAK1, JAK2, and TYK2 phosphorylation and subsequent activation of STAT1 and STAT3 in various cell types; this led to the formation of STAT1/STAT3 complexes with the m67SIE oligonucleotide from the c-fos promoter [15]. Interestingly, these authors speculate that the hyperosmotic signal occurred independently of gp130. This suggests an alternative pathway by which JAKs may be activated beyond the canonical JAK/STAT route. In agreement with this study, hyperosmotic shock in COS-7 cells was shown to lead to tyrosine phosphorylation of STAT1 in a MKK6/p38-dependent pathway [16]. In this case, STAT1 but not JAK1 phosphorylation could be inhibited by genistein (a non-specific tyrosine kinase inhibitor) leading the authors to conclude that a tyrosine kinase distinct from JAK1 (possibly novel) represented the link between hypertonicity and STAT activation. The most well-investigated reports linking cellular stress with the JAK/STAT pathway are studies in cardiomyocytes undergoing hypoxia/reperfusion. Like UV light, hypoxia/reperfusion led to p38 MAPK phosphorylation followed by serine 727 phosphorylation of STAT1 which was associated with activation of pro-apoptotic FAS/FASL and caspase-1 [17]. It was concluded that Fas and caspase-1 expression were directly STAT-1 dependent because their expression could be inhibited by STAT1 anti-sense RNAs. Thus, STAT1-dependent FAS activation plays a leading role in cardiomyocyte death during hypoxia/reperfusion injury [18] and as the authors point out, inhibition of this pathway may prove to be cardioprotective following ischemic insult [19]. Interestingly, while these studies showed that both tyrosine 701 and serine 727 of STAT1 were phosphorylated in response to hypoxia/reperfusion, only phosphorylation on serine was required for FAS expression. Because serine phosphorylation alone is not sufficient for direct DNA binding, these results indicate alternative pathways by which STAT1 may activate target genes during stress. For example, serine phosphorylated STAT1 may associate with other scaffolding proteins as it does in the case of MCM5 [20], BRCA1 [21], or HSF [22] and act instead as a transcriptional co-activator, rather than a direct activator of target genes [23]. In vivo models of hypoxia/reperfusion also implicate STAT5 as a player in responses to cellular stress. But unlike STAT1, STAT5 is thought to be mainly protective by activating anti-apoptotic signals. For example, Yamaura et al. report that genetic deletion of STAT6 but not the STAT5A causes resistance to myocardial ischemia/reperfusion injury [24]. This resistance was thought to be related to two distinct STAT5A-mediated pathways: one involving a Src/STAT5/PI-3 kinase/Akt pathway, and the other a direct JAK2/STAT5A pathway. Like STAT5, STAT3 was also shown to be protective against cardiac ischemia/reperfusion injury through a JAK2/STAT3-dependent mechanism involving up-regulation of anti-apoptotic Bcl2 and down-regulation of pro-apoptotic Bax [25,26]. Studies in our laboratory indicate that in microvascular endothelial cells, hypoxia caused an increased tyrosine phosphorylation of JAK2, down-regulation of FAS/FASL, and that AG490 (a JAK2 inhibitor) de-repressed FAS transcription (unpublished observations). This may suggest a possible mechanism whereby activated JAK2 could mediate protection during ischemia in endothelial cells by repressing pro-apoptotic FAS transcription through downstream STAT3 or STAT5. Intriguingly, a complex of STAT3 and c-Jun was recently shown to be a FAS repressor [27,28] but it remains to be determined if STAT5 or other STATs can behave like STAT3 and act as transcriptional repressors of pro-apoptotic genes during cellular stress. STAT5 nuclear translocation and DNA binding to the GAS (γ-activated site) implicates STAT5 in hypoxic stress responses, but the biological significance of this observation is not yet clear [29]. Although not as well studied as hypoxia/reperfusion or osmotic stress, reactive oxygen species have also been shown to activate the JAK/STAT pathway. Oxidative stress, such as might occur in diabetes and cardiovascular disease, was shown to activate HSP70 in smooth muscle cells in a JAK-dependent manner [30]. This response is thought to aid in adapting these cells to oxidative damage. Recently it was shown that STAT1 forms a complex with HSF-1 to activate the HSP promoter while STAT3 filled just the opposite role [22,31]. Thus, it appears that STAT1 and STAT3 can perform entirely different functions with regard to cellular stress-type responses. Other studies have determined that peroxide treatment resulted in STAT3 tyrosine phosphorylation and nuclear translocation [32] and JAK2, STAT1, and STAT3 were activated by oxidized LDL [33]. Taken together, the studies reviewed herein support a role for the JAK/STAT pathway in various forms of cellular stress and relate perturbed JAK/STAT signaling to potential disease states. However, consistent with some of the current ideas about STAT biology, it is clear that cellular stress seems to activate STATs in ways that can be both detrimental to and supportive of cell survival. For example, STAT1 activation by hypoxia-reperfusion injury activates cell death pathways, while STAT5 activation by the same type of stressor seems to promote cell survival pathways. Thus, STATs may have evolved to fulfil both sides of a "yin and yang" type mechanism where either death or survival pathways can be activated depending on the strength or type of cellular stressor [34]. This may be especially true in endothelial cells, which seem to be able to resist short-term hypoxic-stress compared to other cell types but die by apoptosis following prolonged exposure to hypoxia [35]. The most intriguing aspect of many cellular stress-activated pathways is the apparent absence of ligand-to-receptor stimulation. But the cell must somehow "sense" changes in the external milieu and transmit these signals to the nucleus. How does it do this? Two such examples of this type of cellular sensing are activation of a well-described transcription factor known as HIF-1α (hypoxia-inducible factor), and another is the cellular thermostat called HSF (heat shock factor). In the case of HIF, enzymatic modification by an enzyme requiring oxygen as a cofactor is responsible for HIF activation and switching on of target genes when cells are stressed by low oxygen [36]. For HSF multiple stressors such as ATP depletion, ischemia, and intracellular acidosis lead to HSF phosphorylation, unfolding, and its translocation to the nucleus to activate target genes [37]. So these powerful signal transducing pathways are somehow activated directly presumably without ligand stimulation. This is probably the most speedy and efficient way of activating downstream target genes to promote cell survival. Conclusions Is it possible that STATs can also act as a cellular rheostat of various stressors? Recent suggestions that STATs can be post-translationally modified in ways other than phosphorylation (e.g. acetylation, methylation, and ubiquitination) make this a possibility [38]. For example, changes in the intracellular redox environment by low oxygen tension may modify STAT conformation leading to enhanced availability of its active centers [15]. This change may facilitate interactions with other STAT-modifying proteins such as p38 MAPK. Alternatively, other previously unknown STAT pathways may be activated during cellular stress, altering its transcriptional capacity. These might include STAT association with other second messengers such as PI-3 kinase and Akt but also STAT upstream activation by molecules like Src [24]. Figure 1 summarizes the potential role of STATs in cellular stress. Figure 1 Role of STATs in cell stress responses. (A) Autocrine IFN may activate JAK/STAT through the canonical pathway. This activation would involve tyrosine phosphorylation of STAT by JAK resulting in STAT dimers which are 20% transcriptionally active. This process is thought to "prime" STATs for serine phosphorylation by an IFN-inducible serine kinase (possibly PKC) [42]. Both tyrosine and serine phosphorylation results in a 100% transcriptionally active STAT1 dimer. (B) Hypoxia-reperfusion injury may directly activate p38 MAPK which phosphorylates STAT1 on SER727. Serine phosphorylated STAT could then participate in protein-protein interactions with other STAT binding proteins and activate the expression of pro-apoptotic genes like FAS. (C) In this case, hypoxia-reperfusion may activate STAT5 resulting in activation of cell survival pathways. STAT5 activation by hypoxia may be mediated by JAK2 and a STAT5/cSrc/PI-3 kinase/Akt pathway. (D) STAT3 may act as a constitutive FAS repressor, but FAS is de-repressed during UV stress which may involve STAT3 inhibition by PI3-kinase/Akt. Finally, while our understanding of a stress-related p38/STAT1 (pSER) pathway seems to be taking shape, very few studies have investigated the role of serine phosphorylation of other STATs and what the upstream kinase (s) may be during cellular stress. Future studies might focus on identifying whether serine phosphorylation is common to other STATs during cellular stress and how this might relate to activation or inactivation of target genes. Other questions to be answered are what is the function of unphosphorylated STAT dimers found in the nucleus of unstimulated cells and how might other STAT post-translational modifications (other than phosphorylation) mediate STAT signaling beyond the canonical JAK/STAT pathways [39-41]. Answers to these questions may help to begin to unravel the complex nature of STAT signaling and how some of the alternative routes of STAT activation are related to cellular stress-activated pathways. Ultimately, modulation of the JAK/STAT pathway in vivo may prove to be of therapeutic value. ==== Refs Hardie DG Roles of the AMP-activated/SNF1 protein kinase family in the response to cellular stress Biochem Soc Symp 1999 64 13 27 10207618 Minden A Karin M Regulation and function of the JNK subgroup of MAP kinases Biochim Biophys Acta 1997 1333 F85 104 9395283 10.1016/S0304-419X(97)00018-8 Kisseleva T Bhattacharya S Braunstein J Schindler CW Signaling through the JAK/STAT pathway, recent advances and future challenges Gene 2002 285 1 24 12039028 10.1016/S0378-1119(02)00398-0 Lim CP Cao X Serine phosphorylation and negative regulation of Stat3 by JNK J Biol Chem 1999 274 31055 61 10521505 10.1074/jbc.274.43.31055 Kovarik P Stoiber D Eyers PA Menghini R Neininger A Gaestel M Cohen P Decker T Stress-induced phosphorylation of STAT1 at Ser727 requires p38 mitogen-activated protein kinase whereas IFN-gamma uses a different signaling pathway Proc Natl Acad Sci U S A 1999 96 13956 61 10570180 10.1073/pnas.96.24.13956 Ramsauer K Sadzak I Porras A Pilz A Nebreda AR Decker T Kovarik P p38 MAPK enhances STAT1-dependent transcription independently of Ser-727 phosphorylation Proc Natl Acad Sci U S A 2002 99 12859 64 12232043 10.1073/pnas.192264999 Maziere C Dantin F Dubois F Santus R Maziere J Biphasic effect of UVA radiation on STAT1 activity and tyrosine phosphorylation in cultured human keratinocytes Free Radic Biol Med 2000 28 1430 7 10924861 10.1016/S0891-5849(00)00264-1 McGinn S Poronnik P King M Gallery ED Pollock CA High glucose and endothelial cell growth: novel effects independent of autocrine TGF-beta 1 and hyperosmolarity Am J Physiol Cell Physiol 2003 284 C1374 86 12540377 Mandarino LJ Current hypotheses for the biochemical basis of diabetic retinopathy Diabetes Care 1992 15 1892 901 1464244 Nishikawa T Edelstein D Du XL Yamagishi S Matsumura T Kaneda Y Yorek MA Beebe D Oates PJ Hammes HP Normalizing mitochondrial superoxide production blocks three pathways of hyperglycaemic damage Nature 2000 404 787 90 10783895 10.1038/35008121 Wang X Shaw S Amiri F Eaton DC Marrero MB Inhibition of the Jak/STAT signaling pathway prevents the high glucose-induced increase in tgf-beta and fibronectin synthesis in mesangial cells Diabetes 2002 51 3505 9 12453907 Amiri F Venema VJ Wang X Ju H Venema RC Marrero MB Hyperglycemia enhances angiotensin II-induced janus-activated kinase/STAT signaling in vascular smooth muscle cells J Biol Chem 1999 274 32382 6 10542280 10.1074/jbc.274.45.32382 Amiri F Shaw S Wang X Tang J Waller JL Eaton DC Marrero MB Angiotensin II activation of the JAK/STAT pathway in mesangial cells is altered by high glucose Kidney Int 2002 61 1605 16 11967010 10.1046/j.1523-1755.2002.00311.x Araki T Tsujioka M Abe T Fukuzawa M Meima M Schaap P Morio T Urushihara H Katoh M Maeda M A STAT-regulated, stress-induced signalling pathway in Dictyostelium J Cell Sci 2003 116 2907 15 12771188 10.1242/jcs.00501 Gatsios P Terstegen L Schliess F Haussinger D Kerr IM Heinrich PC Graeve L Activation of the Janus kinase/signal transducer and activator of transcription pathway by osmotic shock J Biol Chem 1998 273 22962 8 9722518 10.1074/jbc.273.36.22962 Bode JG Gatsios P Ludwig S Rapp UR Haussinger D Heinrich PC Graeve L The mitogen-activated protein (MAP) kinase p38 and its upstream activator MAP kinase kinase 6 are involved in the activation of signal transducer and activator of transcription by hyperosmolarity J Biol Chem 1999 274 30222 7 10514514 10.1074/jbc.274.42.30222 Stephanou A Scarabelli TM Brar BK Nakanishi Y Matsumura M Knight RA Latchman DS Induction of apoptosis and Fas receptor/Fas ligand expression by ischemia/reperfusion in cardiac myocytes requires serine 727 of the STAT-1 transcription factor but not tyrosine 701 J Biol Chem 2001 276 28340 7 11309387 10.1074/jbc.M101177200 Stephanou A Brar BK Scarabelli TM Jonassen AK Yellon DM Marber MS Knight RA Latchman DS Ischemia-induced STAT-1 expression and activation play a critical role in cardiomyocyte apoptosis J Biol Chem 2000 275 10002 8 10744676 10.1074/jbc.275.14.10002 Stephanou A Activated STAT-1 pathway in the myocardium as a novel therapeutic target in ischaemia/reperfusion injury Eur Cytokine Netw 2002 13 401 3 12517719 DaFonseca CJ Shu F Zhang JJ Identification of two residues in MCM5 critical for the assembly of MCM complexes and Stat1-mediated transcription activation in response to IFN-gamma Proc Natl Acad Sci U S A 2001 98 3034 9 11248027 10.1073/pnas.061487598 Ouchi T Lee SW Ouchi M Aaronson SA Horvath CM Collaboration of signal transducer and activator of transcription 1 (STAT1) and BRCA1 in differential regulation of IFN-gamma target genes Proc Natl Acad Sci U S A 2000 97 5208 13 10792030 10.1073/pnas.080469697 Stephanou A Isenberg DA Nakajima K Latchman DS Signal transducer and activator of transcription-1 and heat shock factor-1 interact and activate the transcription of the Hsp-70 and Hsp-90beta gene promoters J Biol Chem 1999 274 1723 8 9880553 10.1074/jbc.274.3.1723 Stephanou A Latchman DS STAT-1: a novel regulator of apoptosis Int J Exp Pathol 2003 84 239 44 14748743 10.1111/j.0959-9673.2003.00363.x Yamaura G Turoczi T Yamamoto F Siddqui MA Maulik N Das DK STAT signaling in ischemic heart: a role of STAT5A in ischemic preconditioning Am J Physiol Heart Circ Physiol 2003 285 H476 82 12860560 Hattori R Maulik N Otani H Zhu L Cordis G Engelman RM Siddiqui MA Das DK Role of STAT3 in ischemic preconditioning J Mol Cell Cardiol 2001 33 1929 36 11708838 10.1006/jmcc.2001.1456 Booz GW Day JN Baker KM Interplay between the cardiac renin angiotensin system and JAK-STAT signaling: role in cardiac hypertrophy, ischemia/reperfusion dysfunction, and heart failure J Mol Cell Cardiol 2002 34 1443 53 12431443 10.1006/jmcc.2002.2076 Ivanov VN Bhoumik A Krasilnikov M Raz R Owen-Schaub LB Levy D Horvath CM Ronai Z Cooperation between STAT3 and c-jun suppresses Fas transcription Mol Cell 2001 7 517 28 11463377 10.1016/S1097-2765(01)00199-X Ivanov VN Krasilnikov M Ronai Z Regulation of Fas expression by STAT3 and c-Jun is mediated by phosphatidylinositol 3-kinase-AKT signaling J Biol Chem 2002 277 4932 44 11733515 10.1074/jbc.M108233200 Joung YH Park JH Park T Lee CS Kim OH Ye SK Yang UM Lee KJ Yang YM Hypoxia activates signal transducers and activators of transcription 5 (STAT5) and increases its binding activity to the GAS element in mammary epithelial cells Exp Mol Med 2003 35 350 7 14646587 Madamanchi NR Li S Patterson C Runge MS Reactive oxygen species regulate heat-shock protein 70 via the JAK/STAT pathway Arterioscler Thromb Vasc Biol 2001 21 321 6 11231909 Stephanou A Latchman DS Transcriptional regulation of the heat shock protein genes by STAT family transcription factors Gene Expr 1999 7 311 9 10440232 Carballo M Conde M El Bekay R Martin-Nieto J Camacho MJ Monteseirin J Conde J Bedoya FJ Sobrino F Oxidative stress triggers STAT3 tyrosine phosphorylation and nuclear translocation in human lymphocytes J Biol Chem 1999 274 17580 6 10364193 10.1074/jbc.274.25.17580 Maziere C Conte MA Maziere JC Activation of JAK2 by the oxidative stress generated with oxidized low-density lipoprotein Free Radic Biol Med 2001 31 1334 40 11728804 10.1016/S0891-5849(01)00649-9 Chin YE Kitagawa M Kuida K Flavell RA Fu XY Activation of the STAT signaling pathway can cause expression of caspase 1 and apoptosis Mol Cell Biol 1997 17 5328 37 9271410 Stempien-Otero A Karsan A Cornejo CJ Xiang H Eunson T Morrison RS Kay M Winn R Harlan J Mechanisms of hypoxia-induced endothelial cell death. Role of p53 in apoptosis J Biol Chem 1999 274 8039 45 10075703 10.1074/jbc.274.12.8039 Jaakkola P Mole DR Tian YM Wilson MI Gielbert J Gaskell SJ Kriegsheim A Hebestreit HF Mukherji M Schofield CJ Targeting of HIF-alpha to the von Hippel-Lindau ubiquitylation complex by O2-regulated prolyl hydroxylation Science 2001 292 468 72 11292861 Chi NC Karliner JS Molecular determinants of responses to myocardial ischemia/reperfusion injury: focus on hypoxia-inducible and heat shock factors Cardiovasc Res 2004 61 437 47 14962475 10.1016/j.cardiores.2003.11.033 Schindler CW Series introduction. JAK-STAT signaling in human disease J Clin Invest 2002 109 1133 7 11994400 10.1172/JCI200215644 Braunstein J Brutsaert S Olson R Schindler C STATs dimerize in the absence of phosphorylation J Biol Chem 2003 278 34133 40 12832402 10.1074/jbc.M304531200 Chatterjee-Kishore M Wright KL Ting JP Stark GR How Stat1 mediates constitutive gene expression: a complex of unphosphorylated Stat1 and IRF1 supports transcription of the LMP2 gene Embo J 2000 19 4111 22 10921891 10.1093/emboj/19.15.4111 Mowen KA Tang J Zhu W Schurter BT Shuai K Herschman HR David M Arginine methylation of STAT1 modulates IFNalpha/beta-induced transcription Cell 2001 104 731 41 11257227 Uddin S Sassano A Deb DK Verma A Majchrzak B Rahman A Malik AB Fish EN Platanias LC Protein kinase C-delta (PKC-delta) is activated by type I interferons and mediates phosphorylation of Stat1 on serine 727 J Biol Chem 2002 277 14408 16 11839738 10.1074/jbc.M109671200

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==== Front J Transl MedJournal of Translational Medicine1479-5876BioMed Central London 1479-5876-2-271528580710.1186/1479-5876-2-27ResearchEvaluation of in vivo labelled dendritic cell migration in cancer patients Ridolfi Ruggero 1r.ridolfi@ausl.fo.itRiccobon Angela 1a.riccobon@ausl.fo.itGalassi Riccardo 2mednucle@ausl.fo.itGiorgetti Gianluigi 3g.giorgetti@ausl.fo.itPetrini Massimiliano 1m.petrini@ausl.fo.itFiammenghi Laura 4l.fiammenghi@ausl.fo.itStefanelli Monica 4m.stefanelli@ausl.fo.itRidolfi Laura 1lridolfi1973@libero.itMoretti Andrea 2andreamorek@libero.itMigliori Giuseppe 5m.giuseppe@libero.itFiorentini Giuseppe 2g.fiorentini@ausl.fo.it1 Department of Medical Oncology, Morgagni-Pierantoni Hospital, Via Forlanini 34, 47100 Forlì, Italy2 Nuclear Medicine Unit, Morgagni-Pierantoni Hospital, Via Forlanini 34, 47100 Forlì, Italy3 Health Physics Unit, Morgagni-Pierantoni Hospital, Via Forlanini 34, 47100 Forlì, Italy4 Istituto Oncologico Romagnolo, Corso Mazzini 65, 47100 Forlì, Italy5 Blood Transfusion Unit, Morgagni-Pierantoni Hospital, Via Forlanini 34, 47100 Forlì, Italy2004 30 7 2004 2 27 27 8 6 2004 30 7 2004 Copyright © 2004 Ridolfi et al; licensee BioMed Central Ltd.2004Ridolfi et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background Dendritic Cell (DC) vaccination is a very promising therapeutic strategy in cancer patients. The immunizing ability of DC is critically influenced by their migration activity to lymphatic tissues, where they have the task of priming naïve T-cells. In the present study in vivo DC migration was investigated within the context of a clinical trial of antitumor vaccination. In particular, we compared the migration activity of mature Dendritic Cells (mDC) with that of immature Dendritic Cells (iDC) and also assessed intradermal versus subcutaneous administration. Methods DC were labelled with 99mTc-HMPAO or 111In-Oxine, and the presence of labelled DC in regional lymph nodes was evaluated at pre-set times up to a maximum of 72 h after inoculation. Determinations were carried out in 8 patients (7 melanoma and 1 renal cell carcinoma). Results It was verified that intradermal administration resulted in about a threefold higher migration to lymph nodes than subcutaneous administration, while mDC showed, on average, a six-to eightfold higher migration than iDC. The first DC were detected in lymph nodes 20–60 min after inoculation and the maximum concentration was reached after 48–72 h. Conclusions These data obtained in vivo provide preliminary basic information on DC with respect to their antitumor immunization activity. Further research is needed to optimize the therapeutic potential of vaccination with DC. ==== Body Background Dendritic Cell (DC) vaccination is one of the most promising tools of immunological therapy for cancer. Administration of DC, generated and loaded with tumor antigens ex vivo, can be used to circumvent tumor immunotolerance [1,2]. A large number of immature DC (iDC) can be produced by culturing peripheral blood monocytes with GM-CSF and IL-4 in vitro. These iDC possess functional characteristics typical of this maturation status, such as phagocytosis, macropinocytosis, receptor-mediated endocytosis and antigen processing [3,4]. After antigen uptake and processing, under inflammatory stimuli, iDC undergo functional changes that result in their maturation (mDC) [5]. Following the up-regulation of HLA class I and II and costimulatory molecules (CD80, CD86) and other specific markers such as CD83, DC-LAMP and CCR7, mDC migrate to the T-cell zone of lymphoid tissue, where they have an optimal stimulatory capacity [6,7]. The migration of DC to regional lymph nodes therefore represents one of the most important requirements for lymphocyte priming. Migration probably occurs through lymphatic pathways, but it is not known whether it is active or passive. Furthermore, factors such as PGE2 may considerably increase migration, inducing CCR7 expression on the surface of DC. Penetration may be limited to the peripheral zones of lymphoid tissue when the DC are still immature, or may reach the deeper T-cell zones, where a greater number of naïve T-cells are present, when DC are mature and activated. Surface antigen CCR7, present on the cell membrane of DC, strongly influences migratory capacity through its interaction with transporter molecules, TREM-2, LTC4, LTD4, etc. [8-10]. The mDC that reach lymph nodes prime naïve T-cells for a limited time and then exhaust their active functions. This can be verified by measuring IL-12 production, which rapidly decreases, and by determining the presence of IL-10, previously absent. Special conditions such as the linkage with lymphocyte ligand CD40 may prolong the active phase of mDC [11-13]. Recent studies on cancer patients evaluating the efficacy of in vitro-generated vaccines have shown that mature, but not immature DC, induce an effective antitumor response [14-18]. Animal studies have provided direct evidence that subcutaneously injected DC preferentially migrate to draining lymph nodes to induce a measurable antitumor effect [18,19]. Similarly, the use of radiolabelled DC in humans demonstrates the ability of these cells to migrate to draining lymph nodes. It has also been observed that migration efficiency is linked to their maturation status or administration route (intravenous, subcutaneous, or intradermal) [20-23]. In the course of a vaccination trial using DC pulsed with autologous tumor lysate (ATL) in cancer patients, we evaluated the in vivo migration ability of DC by labelling them with 99mTc-HMPAO or 111In-Oxine. In particular, migratory activity was assessed in iDC and mDC in terms of time required for migration to lymph nodes, duration of activity, and number of cells that migrated. Migratory capacity was further evaluated by comparing subcutaneous and intradermal administration. Materials and methods Patients The case series consisted of a subset of the 19 patients enrolled onto a phase I/II vaccination trial for advanced melanoma and renal cell carcinoma in which the first 9 patients were treated with iDC and the remaining 10 received mDC, both pulsed with autologous tumor lysate and keyhole limpet hemocyanin (Biosyn, Fellbach, Germany). In the present study 8 patients were analyzed (7 melanoma, 1 renal carcinoma) for a total of 11 treatments. In vivo migration was assessed using a part of the DC obtained for one of the therapy cycles. Three of the 8 patients were evaluated twice. Two melanoma patients were treated with iDC (one of whom twice), while 4 other patients with melanoma and 1 with renal cell carcinoma (treated twice) received mDC. The remaining melanoma patient was treated with iDC and subsequently with mDC. The clinical trial was approved by the Italian Ministry of Health and by the Ethical Committee of Forlì Health and Social Services (Azienda USL – Forlì, Italy). All patients gave written informed consent. Tumor lysate Tumor samples surgically removed from the patients were immediately placed in PBS. Adjacent non malignant tissue was removed by scalpel and tumor cells were dispersed to create a single-cell suspension. Cells were lysed by incubation in sterile distilled water. Lysis was monitored by light microscope. Larger particles were removed by centrifugation (10 min at 600 g) and the supernatant was passed through a 0.2-μm filter. Protein contents were determined and aliquots were stored at -80°C until use. Treatment Patients were generally vaccinated intradermally with DC (4–6 inoculations at the base of the thigh, about 10 cm from the groin, in the absence of visible disease). From days 2–6, IL-2 (Chiron, Milan, Italy) was administered subcutaneously at a dose of 3 million IU/die. This procedure was repeated after two weeks and once a month until progression occurred. DC generation DC were prepared from peripheral blood monocytes (PBMC) obtained by leukapheresis without previous mobilization. 5–9 liters of blood were processed in each collection. PBMC were purified on Ficoll-Paque. An aliquot of PBMC was utilized immediately for DC generation and the rest was frozen in bags for use at a later date (4–5 bags/1 collection). PBMC were incubated in tissue culture flasks with CellGro DC Medium (Cell Genix, Freiburg, Germany) at 10 × 106 cells/ml for 2 h. The non-adherent cells were discarded and the adherent cells were incubated in CellGro DC Medium containing 1000 IU/ml rhIL-4 (Cell Genix) and 1000 IU/ml rhGM-CSF (Shering Plough, Milan, Italy) for 7 days to generate a DC-enriched cell population. On day 6 DC were pulsed with autologous tumor lysate (100 mg/ml) and with KLH (50 mg/ml) and incubated overnight. On day 7, they were defined as iDC. After eliminating the previous culture medium, pulsed iDC were cultured for a further 2 days with a cocktail of cytokines (TNFα, IL-1β, IL-6, Endogen, Pierce Biotechnology, Rockford, USA; PGE2, Cayman Chemical, Ann Arbor, MI, USA). On day 9 they were defined as mDC. iDC or mDc were removed, washed and suspended in sterile saline for therapeutic infusion into the patient. DC labelling and migration evaluation Labelling of DC was performed according to the methods described for leucocyte radiolabelling [24-26]. A part of both iDC and mDC destined for vaccination (about 9.106) were resuspended in platelet-poor autologous plasma (CFP1) and incubated for 15 min at room temperature with 99mTc-HMPAO (20 mCi) (Nycomed Amersham plc, Little Chalfont, UK) 111In-Oxine (1 mCi) (Altana Pharma, Milan, Italy). After two washes to eliminate the unbound isotope, the cells were resuspended in a total volume of 1.5 ml of CFP1. Radiolabelling of the DC and of the culture supernatant was evaluated with a gamma counter, after which DC were inoculated intradermally into the patient near healthy lymph nodes and in the contralateral zone not used for therapeutic vaccination (3 inoculations at 10 cm from inguinal or axillary lymph nodes). The patient then underwent serial acquisitions with gamma-camera positioned at the site of inoculation, with a field of view that included all the lymphatic regions of interest. The first acquisition was performed with a dynamic study of 20 min, followed by 10-min static acquisitions carried out every 30 min for the first 4–6 h and from 18 to 28 h. Other static determinations were made at 36, 48 and 72 h. The maximum duration of observation of DC migratory activity, which depended on the half-life of the radioisotope used, was 72 h for 111In-Oxine and 36 h for 99mTc-HMPAO. The identification of lymph node stations involved in the migratory activity was initially visual, after which we carried out a semiquantitative evaluation of the percentage of DC that migrated to lymph nodes from the inoculation site and an assessment of the speed of DC migration, expressed by activity/time curves obtained through the compartmental mathematical model. Evaluation of labelling stability DC obtained from the culture of frozen PBMC were divided into two parts: one was labelled with 99mTc-HMPAO and the other was labelled with 111In-Oxine. The labelled cells were then suspended in CellGro DC Medium, divided into 4–5 culture flasks for each labelling molecule and incubated for 0 h, 4 h, 21 h, 24 h (99mTc-HMPAO) and 0 h, 4 h, 21 h, 24 h, 48 h (111In-Oxine). The DC from one flask were removed and centrifuged. The supernatant containing the free molecule, and the pellet containing the labelled cells, were then measured with a gamma counter. Phenotype analysis iDC and mDC phenotypes were determined by single or two-color fluorescence analysis. 3–5·105 cells were suspended in 100 μl of buffer (PBS, 2% FCS, 1% sodium azide) and incubated for 30 min at 4°C with 10 μl of appropriate fluorescein isothiocyanate or phycoerythrin-labelled monoclonal antibodies (mAbs). The cells were then washed twice and resuspended in 500 μl of assay buffer. The fluorescence was analyzed by a FACS Vantage flow cytometer (Becton Dickinson, Milan, Italy). mAbs specific for human CD1a, CD14, CD80, CD86, (Becton Dickinson) CD83 (Immunotech, Marseille, France) and CCR7 (BD Pharmingen, Milan, Italy) were used. Cytokine production At each pre-set time the supernatant was collected and stored at -80°C until analysis was carried out using commercially available ELISA Kit (Biosource, Nivelles, Belgium) to measure the production of IL-12 + p40 (bioactive heterodimer of IL-12) and IL-10 by DC. Endocytosis evaluation Single cell-based measurement of endocytosis was carried out as described (27). Dendritic cells were incubated for 30 min at 37°C with 0.5 mg/ml FITC-Dextran (40S DX-FITC Sigma, Milan, Italy). DX-FITC (average MW 42,000) was centrifuged before use to remove aggregates. As negative control, cells were incubated with DX-FITC at 4°C. The cells were washed with cold PBS containing 2% FCS and 2 nM sodium azide to exclude dead cells and were then analyzed on a FACS Vantage flow cytometer (Becton Dickinson) [27]. Results Patient characteristics All the patients (6 males, 2 females) had advanced disease and all but one had undergone previous treatment. Median age was 49 years (range 46–52 years). Three patients were HLA-A1, 3 were HLA-A3, 1 was HLA-A2 and 1 was HLA-A11 (Table 1). Two melanoma patients were treated with iDC, while 2 other patients with melanoma and 1 with renal cell carcinoma received mDC. The remaining 3 melanoma patients were treated with iDC and subsequently with mDC (Table 1). The 8 patients received a total of 73 therapeutic vaccination cycles (20 with DC obtained from fresh PBMC and 53 from frozen PBMC) and 11 labelled DC evaluations were carried out. Table 1 Patient characteristics Patients Sex/Age Pathology Site of Metastasis Previous Treatment i/mDC HLA 1 M/47 Mel Liver, mediastinal lymph nodes IFN iDC A1A2B8B35Bw6Cw4Cw7 2 M/52 Mel Liver BIOCT iDC A3A28B35B53Cw4 3 M/49 Mel Liver, adrenal glands No treatment iDC + mDC A11A31B14B60Bw6Cw3 4 M/42 Mel Liver, mediastinal and axillary lymph nodes BIOCT iDC+ mDC A1A9B17Bw4Bw6Cw3Cw4 5 F/49 Mel Lung, lymph nodes, skin, peritoneum BIOCT iDC+ mDC A1A9B7B44Bw4Bw6Cw4Cw7 6 M/50 Renal ca. Skin, adrenal glands BIOCT mDC A2A3B7B51Bw4Bw6Cw1Cw7 7 F/52 Mel Lung, liver HdIFN + CT mDC A3A29B44Bw4 8 M/46 Mel Abdominal lymph nodes IFN+BIOCT mDC A3A28B21B35Cw4 IFN, alpha interferon; BIOCT, biochemotherapy; CT, chemotherapy; HdIFN, high-dose adjuvant alpha interferon (ECOG 1684) DC characteristics The characteristics of iDC and mDC used to evaluate migration activity were similar to those of the DC utilized by us for therapeutic vaccination and to results published in the literature. Data on the purity and vitality of DC, the presence of surface markers and DC functional features (endocytosis and production of IL-12 and IL-10) are reported in Table 2. Table 2 Biological characteristics of dendritic cells used for vaccination iDC median % (range) mDC median % (range) DC surface markers:  CD 1a 20 (4–58) 2 (0–8)  CD 14 3 (0–7) 2 (0–11)  CD 80 3 (1–23) 37 (27–87)  CD 86 30 (10–55) 81 (15–94)  HLA-DR 45 (17–82) 78 (56–88)  CD 83 2 (0–13) 55 (34–73)  CCR7 4 (2–5) 86 (48–92) Endocytosis % of positive cells 70 (39–91) 15 (1–42) IL-12 production pg/ml 49 (17–225) > 1350 IL-10 production pg/ml 0 0 % purity * 74 (66–98) 59 (31–100) % vitality ** 75 (68–79) 82 (66–89) * viable DC/viable DC + viable lymphocytes ** viable DC + viable lymphocytes/total cells DC labelling efficiency and stability The in vitro stability of DC labelled with 99mTc-HMPAO and 111In-Oxine was evaluated using DC cultured from frozen PBMC. 99mTc-HMPAO-labelled DC showed a 75% loss of activity 4–24 h after the beginning of in vitro culture. 111In-Oxine-labelled DC showed a higher labelling stability (50%) that lasted for up to 24 h (Fig. 1). This accounts for the differences in lymph node uptake percentages observed in our migration studies. More accurate information on the linkage stability of 111In-Oxine-labelled DC over time would permit the opportune correction of the uptake percentage and would enable data to be compared with those obtained using indium. Figure 1 A sample of mature dendritic cells cultured in vitro for vaccination was divided into two parts, one labelled with 99mTc-HMPAO and the other with 111In-Oxine. The DC were then suspended in DC medium and cultured in vitro for 24 h (99mTc-HMPAO) and 48 h (111In-Oxine). At 0, 4, 21, 24, and 48 h, the activity of the supernatant containing the free molecule and of the pellet containing labelled cells was measured. After 24 h, a 75% and 50% loss of activity was observed for 99mTc-HMPAO-and 111In-Oxine-labelled DC, respectively. Administration routes The migration activity of mDC administered simultaneously by intradermal and subcutaneous injection in the arms of two patients (nos. 7 and 8) was evaluated by comparing radioactive uptake in axillary lymph nodes. The intradermal route showed a threefold higher migration than that observed for the subcutaneous route (Table 3). Evaluations were made at intervals from 0 to 44 h after inoculation. The sites of inoculation showed an exponential type washout that was virtually identical for both routes of administration (data not shown). The final migration percentage ratio (measured after 44 h) was fairly similar in both patients, but was obviously not statistically significant (Fig. 2A,2B,3). Table 3 Different vaccine administration routes: intradermal vs. subcutaneous lymph node uptake Patients mDC × 106 Administration route Isotope Max uptake (%) * R.L. (no. 7) 4 Intradermal 99mTc-HMPAO 0.95 G.D. (no. 8) 4 Intradermal 99mTc-HMPAO 1.02 R.L. (no. 7) 4 Subcutaneous 99mTc-HMPAO 0.30 G.D. (no. 8) 4 Subcutaneous 99mTc-HMPAO 0.37 UPTAKE RATIO: intradermal/subcutaneous average: 3 *Maximum uptake = maximum lymph node activity/inoculation site activity at 0 h Figure 2 In patients no. 7 (A) and 8 (B), the same number of 99mTc-HMPAO-labelled DC were administered simultaneously: subcutaneously (sc) in the left axilla and intradermally in the right axilla (id). The acquisition times with gamma camera are reported along the X-axis and the Y-axis shows the counts per 10 min. In both patients intradermal administration presents a greater concentration of labelled cells in lymph nodes than the subcutaneous route. Figure 3 In patient no. 7 the same number of 99mTc-HMPAO-labelled DC were administered simultaneously: subcutaneously (s.c.) in the left axilla and intradermally (i.d.) in the right axilla. The figure shows acquisition images with gamma camera at 0, 3, 5, and 18 h after inoculation. Greater migration capacity after intradermal administration is clearly visible. (IS, inoculation site: LN, lymph node). iDC/mDC migration iDC and mDC migration was evaluated in all 8 patients (4 iDC and 7 mDC treatments) (Table 4). The data presented refer to 4 groups of patients treated with mature or immature cells labelled with 111In-Oxine or 99mTc-HMPAO. A simple numerical analysis shows that the maximum uptake ratio between 99mTc-HMPAO-labelled mDC and iDC varies from 2 to 35, with an average of 8.4. The same ratio for 111In-Oxine-labelled cells varies from 4 to 7, with an average of 6. 99mTc-HMPAO labelling is influenced by the very low iDC uptake due to its greater binding instability and to the short half-life of the radioisotope, which does not permit the acquisition of reliable counts beyond 24–36 h. Table 4 Comparison between iDC and mDC lymph node uptake Patients DC i/m × 106 Isotope Max uptake (%) * G.C. (no. 1) i 6 99mTc-HMPAO 0.22 G.C. (no. 1) i 6.9 99mTc-HMPAO 0.05 G.L. (no. 2) i 9 99mTc-HMPAO 0.05 P.A.M. (no. 3) i 6 111In-Oxine 0.42 T.N. (no. 5) m 5.6 99mTc-HMPAO 1.75 P.I.M. (no. 4) m 12 99mTc-HMPAO 0.53 PA.M. (no. 3) m 7 111In-Oxine 3.14 S.G. (no. 6) m 6.4 99mTc-HMPAO 0.39 S.G. (no. 6) m 6.7 111In-Oxine 1.88 R.L. (no. 7) m 4 99mTc-HMPAO 0.95 G.D. (no. 8) m 4 99mTc-HMPAO 1.02 UPTAKE RATIO: mDC/iDC 111In-Oxine average: 6 (range 4–7) 99m Tc-HMPAO average: 8.4 (range 2–35) *Maximum uptake = maximum lymph node activity/ inoculation site activity at 0 h A lymph node uptake can be observed in all patients within the first two hours of inoculation, reaching a maximum uptake after 12 h in 7 patients (Fig. 4A,4B,5). In the last 4 experiments in which a more accurate temporal analysis was performed, the uptake percentage continued to increase for the entire temporal range studied (24–30 h with 99mTc-HMPAO and 48–60 h with 111In-Oxine). A curve fitting analysis also seemed to indicate a progressive increase in uptake after the first 60 h, but the number of patients evaluated is too low for any definitive conclusions to be drawn. Figure 4 This figure shows the migration activity of mDC (patient no. 5) and iDC (patient no. 2) labelled with 99mTc-HMPAO (A) and of mDC and iDC (patient no. 3) labelled with 111In-Oxine (B). The acquisition times with gamma camera are reported along the X-axis and the Y-axis shows the counts per 10 min. mDC migrating to regional lymph node are always higher than iDC. 99mTc-HMPAO-labelled DC were detected in lymph nodes within 1 h of administration and the maximum concentration was reached within 60 min for iDC and between 18 and 20 h after inoculation for mDC. Figure 5 The figure shows static acquisition images with gamma camera 2, 24, and 48 h, and 2, 24, 48 and 72 h after inoculation with 111In-Oxine-labelled iDC and mDC, respectively, for patient no. 3. Greater migration activity of mDC is clearly visible. (IS, inoculation site: LN, lymph node). Pure 99mTc-HMPAO injection After injection of 99mTc-HMPAO alone in the same inoculation sites used for the study, no labelled hot spots were observed. This would seem to suggest that pure tracers move through lymphatic vessels without accumulating inside lymph nodes. Discussion DC-based immunotherapy has undergone a remarkable transformation in its development from basic research to clinical application [10,28]. However, many issues remain to be clarified to improve functionality and therapeutic effects and to insure a powerful and wide-ranging antitumor response by T-cells. Two stages of fundamental importance in the therapeutic use of DC are the optimization of the maturation stimulus and the induction of an effective migration to regional lymph nodes to guarantee powerful and long-lasting priming of naïve T-cells [5,29]. Migration activity is therefore one of the functional characteristics of DC that warrants further investigation in an attempt to increase their potential [30]. Recent published data have shown that the choice of maturation stimulus may be crucial for therapeutic success. In particular, it has been seen that PGE2 is essential for activating DC chemotaxis through the expression of CCR7 on the cell surface [31,32]. This receptor permits migration through a concentration gradient of its ligands CCL19 and CCL21 inside lymphoid organs. The use of PGE2 may therefore prove to be important for increasing migration activity and DC efficacy. However, it has also been observed that PGE2 inhibits IL-12 production, resulting in a weaker in vivo activation of T-cells [33,34]. These contradictory research data obviously require validation by in vivo experimentation. In the present study we aimed to clarify some issues concerning DC migration activity in a clinical vaccination trial utilizing radiolabelled (99mTc-HMPAO and 111In-Oxine) iDC and mDC [20,35]. Technetium has a high labelling intensity and a short half-life, while indium, despite having a lower intensity, has a longer half-life, which enabled us to monitor the migration activity of labelled DC for up to 72 h. The first step was to evaluate whether radioactive tracer would be scintigraphically visualized in lymph nodes. For this purpose technetium alone was injected intradermally and its progression followed. At the same time labelled DC were administered in the contralateral zone. It was seen that the tracer was not entrapped in lymph node stations and this confirmed that the radioactive molecule detected in contralateral regional lymph nodes was undoubtedly the expression of labelled DC that had migrated to that site. One of the simplest analyses carried out was the evaluation of mDC migration activity using two different routes of administration: subcutaneous and intradermal. We chose two patients at random and compared migration activity simultaneously in both arms (right intradermal and left subcutaneous); it was observed that intradermal administration had a threefold higher migration to lymph nodes than the subcutaneous route. Although it remains to clarify the extent to which this migratory capacity is active or passive, it is clear that DC must be administered intradermally to obtain a higher migration. A crucial phase of the study was the comparison between the migratory activity of iDC (used in the first part of the clinical trial) and that of mDC (used in the second half of our ongoing study). The result was once again unequivocal, showing a greater progressive concentration of mDC that was, on average, six-eightfold higher than that of iDC, in accordance with data reported by other authors [20,23] and in contrast to results published by Blocklet [17], who probably used iDC. The phenotype obtained in our study bears witness to the fact that mDC exhibit a much higher CCR7 surface expression than iDC (86% vs. 4%) (Table 2). Furthermore, mDC have an extremely high IL-12 production, which confirms a marked stimulatory activity. Notwithstanding the results obtained from the present study, many issues remain to be clarified. It has yet to be determined whether the increased activity detected in lymph nodes corresponds to an effectively greater migratory capacity or whether it is the result of a more effective adhesion capacity between surface molecules. Both hypotheses could even prove to be correct. We also do not know how long DC remain in lymph nodes. The increase in activity in lymph nodes is high in the first few determinations but tends to diminish or stabilize after around 36 h. It remains to be seen whether this presumed stabilization is the result of a sort of saturation or whether it can be attributed to the attainment of a dynamic equilibrium. The former hypothesis would indicate the need for an optimization of the number of DC to administer, as only a limited number would be functionally active. The latter would highlight the importance of the timing of administration and perhaps also the degree of DC maturation. To further investigate this, we plan to administer 111In-Oxine-and 99mTc-HMPAO-labelled DC in succession and in the same site, to follow their migratory course. Finally, we aim to assess the migratory capacity of in vitro transiently stimulated DC (semimature DC). The therapeutic use of this type of DC, which have already begun the process of maturation and may be capable of reaching lymph nodes before their functional exhaustion, could increase the duration of their activation and stimulation. If these semimature DC prove to be equipped with a good migratory capacity, further improvement in the therapeutic use of DC may be possible. Conclusions The migration activity of DC to regional lymph nodes is one of the many critical factors that influence the therapeutic result of antitumor vaccination. In the present study we used radioisotope-labelled DC and demonstrated that a better migration activity is obtained using intradermal than subcutaneous administration and that mDC show, on average, a six-to eightfold higher migration than iDC. Numerous other issues on DC functionality have yet to be clarified before antitumor therapeutic efficacy can be improved. The next important step will be to closely monitor the quantity and quality of responses observed in T-cells, and it is hoped that a consensus will be reached on standardized criteria for the definition and validation of clinical results obtained. Abbreviations DC, dendritic cell; iDC, immature dendritic cell; mDC, mature dendritic cell; ATL, autologous tumor lysate; PBMC, peripheral blood monocytes. Authors's contributions RR and LR participated in the design of the study and were responsible for the clinical side of the study. AR, MP, LF and MS participated in the design of the study and were responsible for the biological part of the study. GM performed the apheresis collections. RG, AM and GF carried out DC labelling and migration evaluation. GG performed the mathematical and statistical analysis. All authors read and approved the final manuscript. Competing interests None declared. Acknowledgements The authors wish to thank Gráinne Tierney for editing the manuscript. 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distinct dendritic cell (DC) populations induced by physiologic stimuli: prostaglandin E(2) regulates the migratory capacity of specific DC subsets Blood 2002 100 1362 1372 12149219 10.1182/blood-2001-12-0360 Scandella E Men Y Gillessen S Forster R Groettrup M Prostaglandin E2 is a key factor for CCR7 surface expression and migration of monocyte-derived dendritic cells Blood 2002 100 1354 1361 12149218 10.1182/blood-2001-11-0017 Kalinski P Schuitemaker JH Hilkens CM Kapsenberg ML Prostaglandin E2 induces the final maturation of IL-12-deficient CD1a+CD83+ dendritic cells: the levels of IL-12 are determined during the final dendritic cell maturation and are resistant to further modulation J Immunol 1998 161 2804 2809 9743339 Barrat-Boyes SM Watkins SC Finn OJ In vivo migration of dendritic cells differentiated in vitro: a chimpanzee model J Immunol 1997 158 4543 4547 9144465

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==== Front BMC MedBMC Medicine1741-7015BioMed Central London 1741-7015-2-281528798310.1186/1741-7015-2-28Research ArticleOptimizing the HIV/AIDS informed consent process in India Sastry J 1gowri@jhumitpune.comPisal H 1hema@jhumitpune.comSutar S 1savita@jhumitpune.comKapadia-Kundu N 2ihmp@vsnl.comJoshi A 1aparna@jhumitpune.comSuryavanshi N 1nishi@jhumitpune.comBharucha KE 3drbharucha@jhumitpune.comShrotri A 3drshrotri@jhumitpune.comPhadke MA 4drphadke@jhumitpune.comBollinger RC 5rcb@jhmi.eduShankar AV 6avshanka@jhsph.edu1 Johns Hopkins University, Pune, India2 Institute for Health Management, Pachod (IHMP), India3 BJ Medical College and Sassoon Hospitals, Pune, India4 Directorate of Medical Education and Research, Mumbai, India5 Johns Hopkins University, School of Medicine, Baltimore, USA6 Johns Hopkins University, Bloomberg School of Public Health, Baltimore, USA2004 2 8 2004 2 28 28 17 3 2004 2 8 2004 Copyright © 2004 Sastry et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background While the basic ethical issues regarding consent may be universal to all countries, the consent procedures required by international review boards which include detailed scientific and legal information, may not be optimal when administered within certain populations. The time and the technicalities of the process itself intimidate individuals in societies where literacy and awareness about medical and legal rights is low. Methods In this study, we examined pregnant women's understanding of group education and counseling (GEC) about HIV/AIDS provided within an antenatal clinic in Maharashtra, India. We then enhanced the GEC process with the use of culturally appropriate visual aids and assessed the subsequent changes in women's understanding of informed consent issues. Results We found the use of visual aids during group counseling sessions increased women's overall understanding of key issues regarding informed consent from 38% to 72%. Moreover, if these same visuals were reinforced during individual counseling, improvements in women's overall comprehension rose to 96%. Conclusions This study demonstrates that complex constructs such as informed consent can be conveyed in populations with little education and within busy government hospital settings, and that the standard model may not be sufficient to ensure true informed consent. ==== Body Background It is estimated that nearly 7.2 million people in Asia and the Pacific region are now living with HIV/AIDS, one million of whom acquired the virus in 2002 [1]. Of these, more than 2.4 million are women (ages 15–45) [1]. India's national HIV prevalence rate of less than 1% offers little indication of the serious situation facing the country. An estimated 3.97 million people were living with HIV in India at the end of 2001, ranking it second only to South Africa in numbers of people infected. Although recent data suggest that prevention efforts directed at high-risk populations has resulted in greater HIV/AIDS knowledge and condom use [2,3], the prevalence of HIV/AIDS continues to rise. For HIV-positive pregnant women who have the additional risk of transmitting the disease to their unborn child, fewer prevention efforts are in place and are acutely needed. In some states in India such as Andhra Pradesh, Karnataka, Maharashtra, Manipur, Nagaland and Tamil Nadu prevalence rates are greater than 1% [1], underlining the need for well-planned and sustained interventions on a large scale. In most industrialized countries, voluntary HIV counseling and testing services are a major component of HIV and AIDS control programs targeted toward pregnant women, although such programs are only now being advocated in developing countries [4,5]. Voluntary counseling and testing involves two basic components–an educational component on HIV/AIDS and an informed consent component related to an individual's choice to be HIV tested or not. The primary motivations for conducting voluntary HIV counseling and testing in lower risk populations such as pregnant women are that i) immediate knowledge of the woman's status can help reduce risk of HIV transmission to the unborn child; ii) if not infected, education at this point can help both the husband and wife to reduce risk behaviors to prevent transmission; and iii) testing of the partner can be encouraged [6]. Because voluntary HIV counseling and testing is the principal entry point for both prevention and care, it is critical that the content of the counseling is well understood and that procedures to ensure true informed consent are in place [7,8]. The basic ethical issues regarding consent may be universal to all countries. One of the potential limitations with the current approach is that consent has been reduced to a technical issue and is often removed from wider ethical considerations. The consent procedures required by international review boards include having to provide detailed scientific and legal information to participants. Although the intent is to increase knowledge, these messages may lose their meaning when administered within certain populations. The challenge then becomes one of how to balance the requirements of providing complete information while also obtaining true informed consent. To begin establishing voluntary counseling and testing for pregnant women in India, the Indian National AIDS Control Organization (NACO) in 2001 started voluntary HIV counseling and testing for women attending government-run antenatal clinics in 11 sites throughout the country. This study was conducted in one of these sites, Pune, Maharashtra, in order to develop tools to enhance, standardize and improve the communication of messages during the group education and counseling (GEC) sessions, and to enhance the informed consent process. Methods This study was conducted in the antenatal clinic of an urban government hospital in Pune. Eligible patients were newly registered pregnant women between 18 and 44 years of age who were less than 36 weeks gestation and had no physical or mental disabilities (as determined by a physician). After each eligible woman registered in the antenatal clinic and met with the attending physician, they were offered the opportunity to attend the HIV/AIDS GEC sessions. The eight major topics covered in the education component of the GEC included general transmission modes of HIV, sexual transmission, mother-to-infant HIV transmission, precautions to avoid HIV transmission, ways through which HIV does not transmit, identification of HIV in an individual, detection of HIV in the body, and symptoms of AIDS. In addition, nine major topics related to HIV testing and informed consent were covered, including procedural risks of HIV screening, social risks of HIV screening, availability of the report, the right to say no, repercussions of refusing to take the test, confidentiality of the testing procedures, the right to consult others, the benefits of HIV screening, what one's signature means, specific procedures of the HIV ELISA test and, if applicable, specific procedures of the rapid HIV test. Baseline data We conducted structured observations of 30 GEC sessions over the period from December 2000 to January 2001 to assess how well the information was being covered. The GEC sessions were chosen so that every clinic day (Monday-Saturday) and session time would be equally represented (there were, on average, four GEC sessions during the clinic hours of 9:30 am to 1:00 pm). The structured observation tool included a comprehensive checklist of each of the specific points for each main topic covered during the GEC. A topic would be considered adequately covered if the counselor conveyed all the specific points for the topic. Overall session adequacy was assigned if at least 80% of all topics were presented adequately during the session. To assess women's understanding of the key issues covered we interviewed 136 consecutively consenting women immediately after they attended one of the 30 sessions (89% of the total number of women who attended these sessions). Informed consent was obtained from each woman prior to the interview. After the interview, the women met briefly with an individual counselor, where they chose whether to have HIV testing and, if so, signed the appropriate informed consent form. The women's understanding of the GEC sessions was determined through structured interviews containing 17 questions covering each of the main topics discussed in the GEC. Their answers were scored as either adequate or inadequate based on predetermined criteria. Based in part on these observational and interview data we developed and enhanced the content of the GEC sessions. We also developed a comprehension test to evaluate women's understanding of key issues related to informed consent. The key enhancements to the GEC sessions were as follows: • Areas with greater privacy for both group counseling and individual counseling were established. • Posters illustrating the main topics were created and placed in the GEC rooms. • Similar visuals were made into a flipchart and used by the counselor during individual counseling to reinforce the messages. • All visuals developed included substantial input from the counselors. • The visuals were simple, using bold colors and conveying only one message each. • The posters were created to provide informational cues to the counselor to promote and maintain regularity and standardization in presentation. • The counselors completed further training in the use of the visuals. Development of the comprehension test of key informed consent issues Current standards for ethical treatment of human participants in a study do not require that participants demonstrate comprehension of the study prior to giving informed consent. However, given the volume and complexity of information conveyed during the GEC sessions, we felt it necessary to develop a concise yet complete comprehension test that could be used in HIV screening programs and adapted for future clinical trial enrollments. The questionnaire was developed by choosing eight of the 17 questions from the previous questionnaire used during the baseline evaluation. The eight questions were identified by the field team of counselors, physicians, and behavioral scientists as key issues related to informed consent. The questionnaires were administered by the hospital counselor. Adequacy of women's understanding for any topic was determined if the woman correctly answered the question based on pre-determined criteria. If a woman scored adequately on at least 80%, or six out of eight, questions she became eligible to sign the informed consent form and proceed with the HIV screening. Prior to signing the form, the counselor had the opportunity to clarify any previously misunderstood issues with the woman. The eight questions used to assess comprehension of informed consent issues were as follows: 1. What are the modes by which HIV germs are transmitted? 2. Can you say "No" to taking the HIV test? 3. What happens if you decide not to take the HIV test? 4. What do we mean by "the result of the test will be kept confidential"? 5. Do you have the right to consult your husband or other family members before taking the test? 6. What do you think are the benefits of finding out your HIV status? 7. What problems can a woman face on finding out her HIV-positive status? 8. What does your signature on the consent form mean? Post-intervention evaluation After the enhancements to the GEC were put into place and the comprehension test developed, we conducted structured observations of 40 GEC sessions from May-June 2001. We performed the comprehension test on 224 women who attended one of these 40 sessions (89% of the total women attending). These same women were re-interviewed after the completion of individual counseling. The time between the interview after group counseling and the re-interview after individual counseling was, on average, one-two hours. Analysis We compared the adequacy of GEC topic coverage prior to (baseline 30 GEC sessions) and after (40 GEC sessions) the inclusion of the enhancements. Also, improvements in the women's comprehension were assessed through a comparison of their responses to the eight key informed consent questions before GEC enhancements (N = 136) and after (N = 224). In addition, we examined the added improvements in knowledge when the second group of women (N = 224) were tested after their individual counseling. Analysis of the improvements in topic coverage and women's understanding of topics covered was determined by a chi-square test of proportions or Z-scores (for changes in knowledge in the same population) using SPSS version 10 [9]. This research was approved by the Institutional Review Boards (IRB) at Johns Hopkins University, Baltimore, USA, the local IRBs in Pune, the local medical institutions involved in the research and the National Institutes of Health, USA, which funded this study. Results Coverage of topics in GEC sessions Topics related to informed consent and HIV testing were not well covered during the GEC sessions. Only three topics–availability of a report, the right to say no, and the benefits of screening–were covered in 90% or more of the sessions. The procedural and social risks of HIV screening, the right to consult others, and confidentiality were discussed in less than 10% of the sessions. The impact of refusing to be screened and what a signature means were discussed in 40% and 70% of the sessions, respectively. Coverage of informed consent issues with the use of visuals Focusing only on the eight key issues related to understanding informed consent (see previously listed questions), we compared topic coverage before (Group A) and after (Group B) the improvements were made to the GEC sessions (Table 1). With the use of visuals, there were improvements in coverage in nearly all topic areas. The coverage of "the meaning of the signature" increased significantly from 70% to 90% (P < 0.01). Coverage of "social risk" during sessions showed a statistically significant increase from 7% to 23% (P < 0.05), yet the overall coverage was still very low. Similarly, the coverage of "the right to consult others" showed a statistically significant increase (P < 0.001), however, it was still only covered in 35% of the sessions. Non-significant improvements occurred in the area of "consequences of refusal", increasing from 40% to 55%. Overall, the use of visuals resulted in a statistically significant improvement in adequacy of coverage of the counselling sessions from 30% to 68% of all GEC sessions. Women's understanding of informed consent issues with the use of visuals Table 2 shows both women's topic-specific and overall comprehension of informed consent issues. We compare improvements in comprehension in two groups of women, Group A (without use of visual) and Group B (with use of visuals). We then examine improvements in comprehension in the same group of women (Group B), after enhanced group counselling and with the addition of enhanced individual counselling. There was significantly better understanding in three critical areas of appropriate informed consent when visuals were used, namely, "the right to refuse", "consequences of refusal", and "the meaning of the signature." "The right to refuse" rose from 54% at baseline to 79% and 96% (P < 0.01) with enhanced group counseling and enhanced individual counseling, respectively. It should be noted that this topic was well covered in all sessions with or without the addition of visual aids. On the other hand, the discussion of "social risk if found to be HIV-positive" or "the right to consult others" was rarely covered in any of the counseling sessions. In spite of this, a considerable majority of women understood both these issues. Women's understanding of "consequences of refusal" showed marked improvements with use of visuals, rising from 19% at baseline to 75% with enhanced group counselling (P < 0.01) and further to 96% (P < 0.01) with enhanced individual counselling. Overall, based on adequately answering six out of eight questions, women's knowledge of informed consent topics in enhanced group counselling improved dramatically, from 38% to 72% (P < 0.01). With the addition of individual counselling with visuals, women's overall understanding showed a statistically significant increase in all eight aspects of informed consent, and an overall increase from 72% to 96% (P < 0.01). Conclusions There were two primary objectives of this study. The first was to enhance the communication of key concepts within the HIV/AIDS GEC setting and the second was to develop a simple tool to evaluate women's comprehension of informed consent issues. Many international health education and prevention programs have developed and tested creative and culturally appropriate communication strategies to provide information on issues as sensitive and diverse as family planning and changing defecation behaviors. However, innovation in, and evaluation of, the process of delivering the often complex information necessary for informed consent has been limited [10]. The use of simplified visuals and text as a means of communicating messages to populations with little or no literacy has commonly been used to convey information on family planning, health, nutrition and public health activities [11,12]. However, such visuals must be developed with the specific population in mind and by community members in order to ensure their positive impact on understanding [13]. There is very little evidence demonstrating that individuals in resource-poor countries cannot understand the basics of research design or biomedical treatment options just because they have little education or different views about health and illness. It may be difficult to communicate the purposes, conditions and risks of research, but the difficulty of doing so should not detract from the importance of obtaining individual informed consent. In fact, several researchers [10,14] have established that, with some effort, acceptable levels of information can be communicated. This study indicates that the full informed consent process (including both group and individual counselling), when combined with enhanced education and counselling materials, can lead to excellent comprehension of informed consent issues. The dramatic improvement we found in the women's comprehension of informed consent issues, despite their varying socioeconomic and educational backgrounds, is encouraging. Caution should be exercised, however, in interpreting the improvements in comprehension as being a result of the individual counseling and visuals. The second interview was done within one-two hours of the first, and the women may have had time to reconsider their responses to the previous questionnaire. The major limitation in this study was the experimental design, in that we did not have the opportunity to measure the impact of individual counseling without the use of visuals. This was mainly because during baseline data collection we were interested in comprehension immediately after the GEC session; interaction with the counselor for individual counseling directly following the GEC was very brief and, therefore, was not expected to have improved women's knowledge considerably. Moreover, by the time we tested the visuals we had developed, the counselors had gained a lot more experience in HIV counseling and the women might have received more information from various media about HIV. Despite these limitations, we can assert from our data that simple didactic group education on HIV/AIDS and testing issues is not sufficient to help women in this setting to understand the complexities of informed consent for HIV testing. The use of visuals in the form of posters and flipcharts provided structure and uniformity to the GEC sessions, thereby reinforcing the messages for these women and enhancing the overall informed consent process. Obtaining proper informed consent in the case of HIV screening is not a discrete action, but a process that can be enhanced through effective communication, repetition and reflection. Although the intent is to increase knowledge, information regarding informed consent may lose its meaning when administered within certain populations. The time and the technicalities of the process itself may intimidate women in societies where literacy and awareness about medical and legal rights is low. It has been argued that complicated concepts conveyed in a consent form, often to fulfill the requirements of funding agency for institutional and policy purposes, may in themselves be unethical and, indeed, pose the biggest barrier to the informed consent process [15]. It should also be recognized that implementing counseling and informed consent procedures is considerably more difficult in certain settings in India where facilities, supplies, personnel, and time are at a premium. In addition, educational levels for women in this population are low, where 36% have a primary school education or less and another 33% are illiterate [16]. Generally, for HIV screening, an individual reads or is read a prepared statement that includes detailed scientific and legal information on the aims and biological significance of the test, the risks and benefits of testing, and the individual's rights. The participant is expected to understand the main components of what is written within the document and make an autonomous decision on whether or not to be tested for HIV. This is further complicated by the fact that, in some studies, the original consent document is composed in English and then translated nearly verbatim into the local language, making the communication of already complex topics even more difficult. Typically, informed consent for pregnant women in most Indian hospitals and clinics is for operative procedures such as cesarean section or laparotomy. It is usual for the doctor or resident on duty to put down in his or her own handwriting the text of the consent on a patient's case papers. The content of this consent gives blanket permission to the hospital and doctors to undertake all procedures on the patient that are indicated in order to maintain the good health of the mother and her fetus, while at the same time absolving the attending physician and hospital of any blame in the event of a mishap. This is signed (or a thumbprint given) by the patient, her husband or an accompanying relative, and is generally considered to serve as legal consent; therefore, it is not interpreted as voluntary. Most often, due to time constraints, very little is explained to the patient about the procedure, risks, and benefits, or what her signature actually means. As found in other regions in India, there is a general perception by clinicians and other healthcare workers that women are "unable" to understand any of the procedures even if explained, because they are illiterate or have no medical background [17,18]. It is implicit in the physician-patient relationship that any treatment or procedures recommended by the physician will benefit the patient [19-21]. By de-mystifying the content and process of informed consent through standardization with structured visual cues and reiteration, we feel that these difficulties could be overcome. In creating the modifications to the GEC, we focused on improving communication of those concepts that were the most unfamiliar to these women. For example, for most women in India, there is relatively little sense of autonomy [22]. For many, the woman's role is defined first by her father; after marriage, her husband's decision-making and the wishes of his parents or the elders in his home prevails. For such a woman, when an incurable disease like HIV/AIDS is presented to her in terms of her "autonomy" and "power" with reference to the disease, this could be confusing and even frightening. The prevailing practice of obtaining familial input on such decisions was demonstrated through women's knowledge of this topic despite the fact that it was hardly mentioned during the counseling sessions. On the other hand, our data show that by enhancing the GEC and reinforcing its messages through individual counseling, a significantly greater number of women can correctly understand the idea of their "right to refuse", indicating that even complex constructs such as autonomy can be conveyed. The understanding of the "meaning of the signature" was clearly enhanced with the use of visuals, because the improvements in women's knowledge directly followed the increase in coverage during the counseling sessions. Clearly, some of the concepts related to informed consent may already be understood by these women. Women's understanding of "consequences of refusal" showed marked improvements in the second group of women studied. Although some of this improvement may be attributed to the individual counselling and visuals, the fact that only 55% of the GEC sessions actually adequately covered this topic indicates that other factors may have contributed to the women's knowledge of this topic. This process of refining and evaluating the informed consent process can benefit the clinic and research settings in both developed and developing countries. Data from clinics in the USA, Belgium, and France report that even under well suited environments, informed consent for HIV screening was generally only obtained in about 70–85% of cases, and documentation of consent was substantially less [23,24]. In research settings, studies suggest that, despite having signed a consent form, participants may not fully understand critical aspects of research participation or their individual rights [25,26]. We have modified the standard model of informed consent by adapting it to suit the population that was served, and have documented subsequent improvements in patient understanding of the informed consent process. This study shows that culturally appropriate enhancement of the standard informed consent process moves the process towards its goal of being one that is truly informed and voluntary. Thus it not only fulfills the ethical requirements, but, most importantly, helps to assure that women's rights are preserved. This last point is critical because previous research has pointed out that, although women may be fully informed, they still may not feel their choice is fully voluntary [14]. We suggest that the current requirements of informed consent procedures are inadequate and that it should be a process that communicates information in an effective manner, allows for reiteration of information and includes an evaluation of the woman's knowledge prior to signing the informed consent document. In an effort to allow all interested organizations involved in HIV counseling and testing to use or modify our visuals for their own programs, we are have created a downloadable version available for public access at our website . It is hoped that these types of visuals will become an integral part of all voluntary counseling and testing programs throughout India and elsewhere. Competing interests None declared. Author's contributions JS was involved in developing the research and visuals, implementing the study and preparing the manuscript. HP participated in the design of the visuals and in the analysis and coordination of the study. SS and AJ were involved in data collection and analysis. NK-K participated in the design of the visuals and in the analysis of the study. NS participated in the design of the study and the visuals. KEB, AS and MAP participated in the design and assisted in the implementation of the study. RCB assisted in all aspects of the study design and implementation. AVS participated in the design, conducted the analysis and wrote the manuscript. All authors read and approved the final manuscript. Pre-publication history The pre-publication history for this paper can be accessed here: Acknowledgements The investigators are grateful to the participants for giving their time and information. A special thanks goes to Abhay Kadam for his photographic and computer work on the visuals. We are thankful to all members of the study team at BJ Medical College, especially the counseling staff, physicians and nurses at the Sassoon General Hospital, Pune, for their assistance and cooperation in conducting this work. This research was supported by the National Institutes of Health, grant number 1R01 AI45462-04. Figures and Tables Table 1 Coverage of selected components of informed consent during counseling sessions, with and without the use of visuals Topic covered Coverage in 30 group education sessions without visuals (Group A) Coverage in 40 group education sessions with visuals (Group B) Chi square χ2 statistic and significance level N % N % Mother-to-infant HIV transmission 30 100 40 100 ___ Confidentiality 30 100 38 95 0.2 Right to refuse 29 97 39 98 0.0 Consequences of refusal to test 12 40 22 55 1.4 Social risk 2 7 9 23 4.0* Benefits of HIV testing 30 100 39 98 0.0 Meaning of signature 21 70 36 90 6.8** Right to consult 0 0 14 35 12.6*** 80% coverage in sessions 9 30 27 68 13.4*** * = P < 0.05, ** = P < 0.01, *** = P < 0.001 Table 2 Relative improvement in women's understanding of components of informed consent after use of visuals in group education and counseling (GEC) and individual counseling (IDC) Topic covered Group A: Women's understanding after GEC without visuals (posters) (N = 136) Group B: Women's understanding after GEC with visuals (posters) (N = 224) Chi square χ2 statistic Group A vs Group B Group B: retested after IDC with visuals (flipcharts) (N = 224) Z Score statistic Group B (GEC) vs Group B (GEC+IDC) N % N % N % Mother-to-infant HIV transmission 128 94 213 95 0.03 221 99 2.17** Confidentiality 130 76 174 78 0.09 219 98 6.47*** Right to refuse 73 54 176 79 23.43*** 215 96 5.52*** Consequences of refusal to test 26 19 167 75 102.35*** 214 96 6.22*** Social risk 86 63 153 68 0.76 194 87 4.63*** Benefits of HIV testing 39 29 88 39 3.72 155 69 6.35*** Meaning of signature 80 59 169 75 10.19*** 215 96 6.21*** Right to consult 123 90 203 91 0.02 216 96 2.49** Overall adequate understanding of women (6/8 questions) 52 38 162 72 39.38*** 216 96 7.02*** * = P < 0.1, ** = P < 0.05, *** = P < 0.01 ==== Refs UNAIDS AIDS Epidemic Update 2002 Joint United Nations Programme on HIV/AIDS (UNAIDS) and World Health Organization (WHO) Accessed 20.01.03 Bentley ME Spratt K Shepherd ME Gangakhedkar RR Thilikavathi S Bollinger RC Mehendale SM HIV testing and counseling among men attending sexually transmitted disease clinics in Pune, India: changes in condom use and sexual behavior over time AIDS 1998 12 1869 1877 9792388 10.1097/00002030-199814000-00019 Singh YN Malaviya AN Experience of HIV prevention interventions among female sex workers in Delhi, India Int J STD AIDS 1994 5 56 57 8142530 Campbell CH JrMarum ME Alwano-Edyegu M Dillon BA Moore M Gumisiriza E The role of HIV counseling and testing in the developing world AIDS Educ Prev 1997 Suppl B 92 104 Meursing K Sibindi F HIV counseling – a luxury or necessity? Health Policy Plan 2000 15 17 23 10731231 10.1093/heapol/15.1.17 Faden R Gielen AC Kass N O'Campo P Anderson J Chaisson R Sheon A Prenatal HIV-antibody testing and the meaning of consent AIDS Public Policy J 1994 9 151 159 11654177 Valdiserri RO HIV counseling and testing: its evolving role in HIV prevention AIDS Educ Prev 1997 Suppl B 2 13 Coreil J Losikoff P Pincu R Mayard G Ruff AJ Hausler HP Desormeau J Davis H Boulos R Halsey N Cultural feasibility studies in preparation for clinical trials to reduce maternal-infant HIV transmission in Haiti AIDS Educ Prev 1998 10 46 62 9505098 Statistical Package for Social Sciences (SPSS) SPSS Base 100 Users Guide Chicago, Illinois, USA 2000 Fitzgerald DW Marotte C Verdier RI Johnson WD JrPape JW Comprehension during informed consent in a less-developed country Lancet 2002 360 1301 1302 12414207 10.1016/S0140-6736(02)11338-9 Center for Communication Programs Final Report Population Communication Services (PCS), School of Public Health, Johns Hopkins University, USA Visual Literacy Bangladesh Project (unpublished report) UNESCO (Asian Cultural Center) Final report: Development of audio-visual literacy materials for women in rural areas Eight Regional Workshops on the Preparation of Literacy Follow-up Materials in Asia and the Pacific, Pattaya, Thailand 9–20 October 1990 Moynihan M Mukherjee U Visual communication with non-literates: a review of current knowledge including research in northern India Int J Health Educ 1981 24 251 262 6178233 Karim QA Karim SSA Coovadia HM Susser M Informed consent for HIV testing in a South African Hospital: Is it truly informed and truly voluntary? Am J Public Health 1998 88 637 640 9551007 Reich WT ed Encyclopedia of Bioethics 1995 Revised New York: Simon Schuster and MacMillan National Family Health Survey (NFHS), International Institute for Population Sciences (IIPS) and ORC Macro National Family Health Survey (NFHS-2) 1998–1999 Chapter 7 Mumbai, India 2000 Cassileth B Zupkis R Sutton-Smith K March V Informed consent – Why are its goals imperfectly realised? New Engl J Med 1980 302 896 900 7360175 Schoepf B Ethical, methodological and political issues of AIDS research in central Africa Soc Sci Med 1991 33 749 763 1948167 10.1016/0277-9536(91)90374-L Kaufman C Informed consent and patient decision making: Two decades of research Soc Sci Med 1983 17 1657 1664 6359456 10.1016/0277-9536(83)90311-8 Meisel A Kuczewski M Legal and ethical myths about informed consent Arch Intern Med 1996 156 2521 2526 8951294 10.1001/archinte.156.22.2521 Lidz C Meisel A Osterweis M Holden J Marx J Munetz M Barriers to informed consent Ann Intern Med 1983 99 539 543 6625386 Bloom SS Wypij D Das Gupta M Dimensions of women's autonomy and the influence on maternal health care utilization in a north Indian city Demography 2001 38 67 78 11227846 Denayer M Piot P Jonckheer T Stroobant A HIV screening during pregnancy. Results of 2 attitude surveys on antenatal HIV screening in Belgium Acta Clin Belg 1990 45 299 305 2177298 Henry K Maki M Willenbring K Campbell S The impact of experience with AIDS on HIV testing and counseling practices: a study of U.S. infectious disease teaching hospitals and Minnesota hospitals AIDS Educ Prev 1991 3 313 321 1777339 Joffe S Cook EF Cleary PD Clark JW Weeks JC Quality of informed consent in cancer clinical trials: a cross-sectional survey Lancet 2001 358 1772 1777 11734235 10.1016/S0140-6736(01)06805-2 Mason SA Allmark PJ Obtaining informed consent to neonatal randomised controlled trials: interviews with parents and clinicians in the Euricon study Lancet 2000 356 2045 2051 11145490 10.1016/S0140-6736(00)03401-2

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==== Front J NeuroinflammationJournal of Neuroinflammation1742-2094BioMed Central London 1742-2094-1-141528580110.1186/1742-2094-1-14ReviewMicroglia and neuroinflammation: a pathological perspective Streit Wolfgang J 1streit@mbi.ufl.eduMrak Robert E 2MrakRobertE@uams.eduGriffin W Sue T 3griffinsuet@uams.edu1 Department of Neuroscience, University of Florida College of Medicine, P.O. Box 100244, Gainesville, Florida 32610, USA2 Department of Pathology, University of Arkansas for Medical Sciences, Little Rock, Arkansas 72205, USA3 Department of Geriatrics, University of Arkansas for Medical Sciences and GRECC/CAVHS, Little Rock, Arkansas 72205, USA2004 30 7 2004 1 14 14 8 7 2004 30 7 2004 Copyright © 2004 Streit et al; licensee BioMed Central Ltd.2004Streit et al; licensee BioMed Central Ltd.This is an open-access article distributed under the terms of the Creative Commons Attribution License (), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Microglia make up the innate immune system of the central nervous system and are key cellular mediators of neuroinflammatory processes. Their role in central nervous system diseases, including infections, is discussed in terms of a participation in both acute and chronic neuroinflammatory responses. Specific reference is made also to their involvement in Alzheimer's disease where microglial cell activation is thought to be critically important in the neurodegenerative process. ==== Body Background A role for immune responses, involving antigen presentation and immune-response-generating cytokines, in neurodegenerative diseases such as Alzheimer's disease was recognized for a decade before the term neuroinflammation came into widespread use [1,2]. A PubMed search using "neuroinflammation" as the only key word yields some 300 papers, none before 1995 [3]. While some chronic/remitting neurological diseases, such as multiple sclerosis, have long been recognized as inflammatory, the term neuroinflammation has come to denote chronic, CNS-specific, inflammation-like glial responses that do not reproduce the classic characteristics of inflammation in the periphery but that may engender neurodegenerative events; including plaque formation, dystrophic neurite growth, and excessive tau phosphorylation. In this way, neuroinflammation has been implicated in chronic unremitting neurodegenerative diseases such as Alzheimer's disease – diseases that historically have not been thought of as inflammatory diseases. This new understanding has come from rapid advances in the field of microglial and astrocytic neurobiology over the past fifteen to twenty years. These advances have led to the recognition that glia, particularly microglia, respond to tissue insult with a complex array of inflammatory cytokines and actions, and that these actions transcend the historical vision of phagocytosis and structural support that has long been enshrined in the term "reactive gliosis." Microglia are now recognized as the prime components of an intrinsic brain immune system [4], and as such they have become a main focus in cellular neuroimmunology and therefore in neuroinflammation. This is not the inflammation of the adaptive mammalian immune response, with its array of specialized T-cells and the made-to-order antibodies produced through complex gene rearrangements. This is, instead, the innate immune system, upon which adaptive immunity is built [5]. Many researchers now consider this innate immune response in the brain to be a potentially pathogenic factor in a number of CNS diseases that lack the prominent leukocytic infiltrates of adaptive immune responses, but that do have activated microglia and astrocytes, i.e., neuroinflammation. The idea that neuroinflammation is detrimental implies that glial cell activation precedes and causes neuronal degeneration [2], a sequence of events that appears to be at odds with experimental models of neurodegeneration in which glial cell activation occurs secondary to neuronal damage. What is missing from this simple linear model is the understanding that chronic neurological diseases are just that – chronic, and that this chronicity introduces complex interactions and feedback loops between neurons and glia that render attempts to construct simple, linear cascades of cause and effect inelegant. In the following, we provide some basic definitions and discussion to more precisely define the idea of neuroinflammation as a CNS tissue response to injury, and the notion of neuroinflammation as a pathogenic factor in neurodegenerative diseases. Some basic definitions Inflammation is a reaction of living tissues to injury [6]. The discipline of pathology makes a fundamental distinction between acute and chronic inflammation. Acute inflammation comprises the immediate and early response to an injurious agent and is basically a defensive response that paves the way for repair of the damaged site. Chronic inflammation results from stimuli that are persistent. In the periphery, inflammation consists of leukocytic infiltrates characterized by polymorphonuclear cells (neutrophils) in acute inflammation and mononuclear cells (macrophages, lymphocytes, plasma cells) in chronic inflammation. In order to validate these principles of general pathology within the context of neuroinflammation, one must obviously consider both acute and chronic neuroinflammation and, therefore, these are addressed separately in the following sections. Acute neuroinflammation Before "neuroinflammation" became a commonly used term, neuroscientists spoke of "reactive gliosis" in describing endogenous CNS tissue responses to injury. Reactive gliosis specifically referred to the accumulation of enlarged glial cells, notably microglia and astrocytes, appearing immediately after CNS injury has occurred. In contrast to glial reactivity, which suggests a largely passive response to injury; glial activation implies a more aggressive role in responding to activating stimuli: activated glial cells release factors that act on and engender responses in target cells analogous to the responses of activated immune cells in the periphery. Activation of immune cells in the periphery leads to leukocyte infiltration of tissues, but this is notably absent in the brain unless there has been destruction or compromise of the blood brain barrier [7,8]. In the presence of such destruction or compromise, peripheral leukocytes do enter the brain producing a scenario similar to that seen in inflammatory responses in the periphery. In limited, acute reactions to injury, in the absence of blood-brain barrier breakdown, there is the subtler response of the brain's own immune system, composed largely of rapid activation of glial cells. These responses represent the other end of the spectrum of CNS injury, where limited neuronal insults trigger glial cell activation without breakdown of the blood brain barrier and without concomitant leukocytic infiltration. This form of "pure" glial response occurs in neuronal injury caused by either loss of afferents [9] or loss of efferents [10]. Axotomy, for instance, results in neuronal chromatolysis, the classic example of potentially reversible neuronal injury [9]. It is in these situations that microglial and astrocytic responses (like their peripheral counterparts) fulfill their evolutionarily programmed functions of a reparative response to the benefit of the organism as a whole. Although such specific responses might, in a strict sense, be included in the term "neuroinflammation," neuroinflammation as generally used and understood applies to more chronic, sustained cycles of injury and response, in which the cumulative ill effects of immunological microglial and astrocytic activation contribute to and expand the initial neurodestructive effects, thus maintaining and worsening the disease process through their actions. Chronic neuroinflammation The concept of chronic inflammation (as opposed to acute inflammation) is more relevant in the context of understanding CNS disease (as opposed to CNS injury), as the very term "disease" implies chronicity. Chronic multiple sclerosis is, of course, an unequivocal and long-recognized example of an inflammatory brain disease. Although the underlying cause(s) of multiple sclerosis have not been elucidated, it is probably safe to say that the persistent injurious stimulus that accounts for neuroinflammation in multiple sclerosis is a myelin-related protein that has escaped self-tolerance and become an autoimmunogen. Consistent with the chronic persistence of this autoimmunogen is a persistent accumulation of blood-derived mononuclear leukocytes in the CNS parenchyma, a phenomenon that is similar to what is found in other autoimmune diseases such as rheumatoid arthritis or polymyositis. Infections are another group of diseases that are classically recognized as inflammatory in nature, with meningeal, perivascular, or even parenchymal infiltrates of peripheral leukocytes. There are, however, exceptions. Rabies is a disease in which the peripheral immune response is slow and inadequate, and in which classic inflammatory changes are less striking than those found in other viral encephalidites. Babes, in 1897 [11], described microglial activation in rabies infection, although he did not recognize the nodules he found as clusters of activated microglia. Similar small collections of activated microglia were subsequently found to occur in a wide variety of viral brain infections. Today, the most important example of a chronic brain infection is human immunodeficiency virus (HIV). Chronic HIV encephalitis is characterized by the same nodules of activated microglia that Babes described in rabies. HIV enters and persists in the CNS via myelomonocytic cells: monocytes, perivascular cells, and microglia [12]. HIV infection is uniquely different from most other infectious diseases affecting the CNS in that the virus targets and disables precisely those cells that are key players in neuroinflammation; microglia in the brain and T lymphocytes in the periphery. It therefore comes as no surprise that prominent T cell infiltrates do not occur in HIV encephalopathy. Prion diseases represent another chronic infectious CNS disease that is not accompanied by leukocytic infiltrates. Microglial activation, again, appears to be the most prominent inflammatory component of prion diseases [13,14], although there are a few reports describing T cell infiltration as well [15,16]. Prion diseases share interesting parallels to rabies infection in that infected cells are unrecognized by peripheral immune responses. This may explain in part the unusual patterns of neuroinflammation in prion diseases – manifest not only in atypical cellular infiltrates but also in unusual cytokine profiles [17]. Both HIV and prion infections probably produce an altered microglial physiology that is likely to translate into cycles of neurodegeneration, which could be a contributing factor in the development of dementia that occurs in these conditions. Chronic microglial neuroinflammation in neurodegenerative diseases Neurodegenerative diseases – particularly Alzheimer's disease, but also amyotrophic lateral sclerosis, Parkinson's disease, and Huntington's disease – lack the prominent infiltrates of blood-derived mononuclear cells that characterize autoimmune diseases. On the other hand, there is abundant evidence that many substances involved in the promotion of inflammatory processes are present in the CNS of patients with such neurodegenerative diseases. By far the bulk of this body of evidence is related to studies in Alzheimer's disease [18]. What distinguishes Alzheimer's disease from other neurodegenerative diseases is the conspicuous presence of extracellular deposits of amyloid in senile plaques. Senile plaques in Alzheimer brain are present in different stages of maturity, ranging from diffuse to neuritic to dense core, but they all contain the amyloid beta protein (Aβ). Aβ is a peptide that forms insoluble and pathological extracellular aggregates that seem to attract microglial cells, as suggested by the clustering of microglia at sites of Aβ deposition (see [19] for a review). There is evidence from experimental studies in animals to support the idea that microglia can phagocytose and degrade amyloid [20,21], but such phagocytosis is apparently either ineffective or inadequate in Alzheimer's disease. A key question within the current context is: "Does the amyloid in Alzheimer brain by itself represent a persistent injurious stimulus that causes neuronal injury, or are additional factors involved in eliciting this outcome?" Direct injection of Aβ into the brain produces activation of microglia and loss of specific populations of neurons [21]. Furthermore, transgenic mice that overexpress human, mutant β-amyloid precursor protein (βAPP) do develop Aβ deposits with associated evidence of neuritic injury (although they do not develop Alzheimer-type neurofibrillary tangles unless they are also transgenic for human tau protein) [22]. These Aβ deposits, born of transgenic overexpression of mutant human amyloid precursor protein, invariably contain activated microglia [22,23]. β-Amyloid precursor protein βAPP functions as a neuronal acute-phase, injury-response protein. For instance, there is excessive expression of βAPP, accompanied by microglial activation and cytokine expression, after traumatic head injury [24]. With head injury, there is also Aβ deposition, both in experimental animals [25] and in humans – particularly in individuals genetically susceptible for AD (i.e. ApoE ε4-positive) [26]. These observations emphasize the complex interactions that underlie neurodegeneration in Alzheimer's disease. Conclusions Chronic microglial activation is an important component of neurodegenerative diseases, and this chronic neuroinflammatory component likely contributes to neuronal dysfunction, injury, and loss (and hence to disease progression) in these diseases. The recognition of microglia as the brain's intrinsic immune system, and the understanding that chronic activation of this system leads to pathologic sequelae, has led to the modern concept of neuroinflammation. This vision of microglia-driven neuroinflammatory responses, with neuropathological consequences, has extended the older vision of passive glial responses that are inherent in the concept of "reactive gliosis." Abbreviations Aβ: β-amyloid peptide βAPP: Aβ precursor protein CNS: central nervous system HIV: human immunodeficiency virus MS: multiple sclerosis Competing interests None declared Authors' contributions WJS conceived this review, wrote the initial draft, modified this with the comments of REM and WSTG, and wrote the final draft. REM and WSTG contributed particularly to the sections on infections and on Alzheimer's disease. All authors read and approved the final version. Acknowledgments Supported in part by NIH R21 NINDS 049185, NIH PO1 AG 12411, NIH P30 AG 19606, NIH RO1 AG 37989, and the McKnight Brain Research Foundation at the University of Florida. ==== Refs McGeer PL Itagaki S Tago H McGeer EG Reactive microglia in patients with senile dementia of the Alzheimer type are positive for the histocompatibility glycoprotein HLA-DR Neurosci Lett 1987 79 195 200 3670729 10.1016/0304-3940(87)90696-3 Griffin WST Stanley LC Ling C White L MacLeod V Perrot LJ White CL III Araoz C Brain interleukin 1 and S-100 immunoreactivity are elevated in Down syndrome and Alzheimer disease Proc Natl Acad Sci U S A 1989 86 7611 7615 2529544 Issazadeh S Mustafa M Ljungdahl A Hojeberg B Dagerlind A Elde R Olsson T Interferon gamma, interleukin 4 and transforming growth factor beta in experimental autoimmune encephalomyelitis in Lewis rats: dynamics of cellular mRNA expression in the central nervous system and lymphoid cells J Neurosci Res 1995 40 579 590 7602612 Streit WJ Kincaid-Colton CA The brain's immune system Sci Am 1995 273 54 61 8966536 Medzhitov R Janeway C Jr Advances in immunology: innate immunity N Engl J Med 2000 343 338 344 10922424 10.1056/NEJM200008033430506 Robbins SL Angell M Kumar V Basic Pathology 1981 3 Philadelphia: W.B. 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Cell Molec Neurobiol 1999 19 19 30 10079962 10.1023/A:1006937205905

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